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PINTO0309 / openvino2tensorflow

This script converts the ONNX/OpenVINO IR model to Tensorflow's saved_model, tflite, h5, tfjs, tftrt(TensorRT), CoreML, EdgeTPU, ONNX and pb. PyTorch (NCHW) -> ONNX (NCHW) -> OpenVINO (NCHW) -> openvino2tensorflow -> Tensorflow/Keras (NHWC/NCHW) -> TFLite (NHWC/NCHW). And the conversion from .pb to saved_model and from saved_model to .pb and from .pb to .tflite and saved_model to .tflite and saved_model to onnx. Support for building environments with Docker. It is possible to directly access the host PC GUI and the camera to verify the operation. NVIDIA GPU (dGPU) support. Intel iHD GPU (iGPU) support.
MIT License
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Yolov5-Lite S conversion problem #102

Closed Protozzzer closed 2 years ago

Protozzzer commented 2 years ago

Issue Type

Others

OS

Ubuntu, Other

OS architecture

x86_64

Programming Language

Python

Framework

OpenVINO, PyTorch, ONNX, TensorFlow, TensorFlowLite

Download URL for ONNX / OpenVINO IR

https://github.com/PINTO0309/PINTO_model_zoo/blob/main/180_YOLOv5-Lite/download.sh

Convert Script

openvino2tensorflow \
--model_path saved_model/openvino/FP32/${MODEL}_${H}x${W}.xml \
--output_saved_model \
--output_pb \
--output_no_quant_float32_tflite \
--output_dynamic_range_quant_tflite \
--output_weight_quant_tflite \
--output_float16_quant_tflite \
--output_integer_quant_tflite \
--output_integer_quant_type 'uint8' \
--string_formulas_for_normalization 'data / 255.0' \
--output_tfjs \
--output_coreml \
--weight_replacement_config replace.json

In docker and local both

Description

I try to convert pretrained Yolov5 lite s model weights ( 'pt' converted to OpenVino format ) to tflite format to run Coral Edge TPU via your instructions in forder with Yolov5-Lite. If i use your .xml weights, i receive the next errors:

image image image

If i use my pretrained weights, i recieve: image

Yes, i have read your instructions about steps 6-7, but i assumed that your replace.json file should be right for Yolov5-Lite model S.

What steps can I take to fix the problem?

Relevant Log Output

Traceback (most recent call last):
  File "/home/gotie/.local/bin/openvino2tensorflow", line 1046, in convert
    tf_layers_dict[layer_id] = tf.math.add(tf_layers_dict[edge_id0], tf_layers_dict[edge_id1].transpose(0,2,3,1))
ValueError: axes don't match array

Source code for simple inference testing code

No response

PINTO0309 commented 2 years ago

Since more than six months have passed, the internal behavior of the tool has changed due to bug fixes, etc. The JSON needs to be modified. VariadicSplit https://github.com/PINTO0309/PINTO_model_zoo/blob/main/180_YOLOv5-Lite/replace.json

{
    "format_version": 2,
    "layers": [
        {
            "layer_id": "509",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                0,
                3,
                1,
                2,
                4
            ]
        },
        {
            "layer_id": "512",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                4
            ]
        },
        {
            "layer_id": "513",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                2,
                2,
                81
            ]
        },
        {
            "layer_id": "570",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                0,
                3,
                1,
                2,
                4
            ]
        },
        {
            "layer_id": "573",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                4
            ]
        },
        {
            "layer_id": "574",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                2,
                2,
                81
            ]
        },
        {
            "layer_id": "631",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                0,
                3,
                1,
                2,
                4
            ]
        },
        {
            "layer_id": "634",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                4
            ]
        },
        {
            "layer_id": "635",
            "type": "Const",
            "replace_mode": "direct",
            "values": [
                2,
                2,
                81
            ]
        }
    ]
}
H=640
W=640
MODEL=v5lite_s
openvino2tensorflow \
--model_path saved_model_${H}x${W}/openvino/FP32/${MODEL}_${H}x${W}.xml \
--output_saved_model \
--output_pb \
--output_no_quant_float32_tflite \
--output_dynamic_range_quant_tflite \
--output_weight_quant_tflite \
--output_float16_quant_tflite \
--output_integer_quant_tflite \
--output_integer_quant_type 'uint8' \
--string_formulas_for_normalization 'data / 255.0' \
--output_tfjs \
--output_coreml \
--non_verbose \
--weight_replacement_config replace.json
TensorFlow/Keras model building process starts ======================================
WARNING:root:scikit-learn version 1.0.2 is not supported. Minimum required version: 0.17. Maximum required version: 0.19.2. Disabling scikit-learn conversion API.
WARNING:root:TensorFlow version 2.8.0 has not been tested with coremltools. You may run into unexpected errors. TensorFlow 2.6.2 is the most recent version that has been tested.
WARNING:root:Keras version 2.7.0 has not been tested with coremltools. You may run into unexpected errors. Keras 2.6.0 is the most recent version that has been tested.
weight_replacement_config format_version: 2
Replace the value of Const for each layer_id with the value below.
{'509': {'layer_id': '509',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [0, 3, 1, 2, 4]},
 '512': {'layer_id': '512',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [4]},
 '513': {'layer_id': '513',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [2, 2, 81]},
 '570': {'layer_id': '570',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [0, 3, 1, 2, 4]},
 '573': {'layer_id': '573',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [4]},
 '574': {'layer_id': '574',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [2, 2, 81]},
 '631': {'layer_id': '631',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [0, 3, 1, 2, 4]},
 '634': {'layer_id': '634',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [4]},
 '635': {'layer_id': '635',
         'replace_mode': 'direct',
         'type': 'Const',
         'values': [2, 2, 81]}}
Layer structure =====================================================================
layer_type: Input
layer_id: 0
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 640, 640, 3), dtype=tf.float32, name='images'), name='images', description="created by layer 'images'")
====================================================================================
layer_type: Const
layer_id: 1
tf_layers_dict_shape: (32, 3, 3, 3)
====================================================================================
layer_type: Convolution
layer_id: 2
input_layer0: layer_id=0: KerasTensor(type_spec=TensorSpec(shape=(1, 640, 640, 3), dtype=tf.float32, name='images'), name='images', description="created by layer 'images'")
input_layer1_shape: layer_id=1: (32, 3, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 320, 320, 32), dtype=tf.float32, name=None), name='conv2d/Conv2D:0', description="created by layer 'conv2d'")
====================================================================================
layer_type: Const
layer_id: 3
tf_layers_dict_shape: (1, 32, 1, 1)
====================================================================================
layer_type: Add
layer_id: 4
input_layer0: layer_id=2: KerasTensor(type_spec=TensorSpec(shape=(1, 320, 320, 32), dtype=tf.float32, name=None), name='conv2d/Conv2D:0', description="created by layer 'conv2d'")
input_layer1_shape: layer_id=3: (1, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 320, 320, 32), dtype=tf.float32, name=None), name='tf.math.add/Add:0', description="created by layer 'tf.math.add'")
====================================================================================
layer_type: ReLU
layer_id: 5
input_layer0: layer_id=4: KerasTensor(type_spec=TensorSpec(shape=(1, 320, 320, 32), dtype=tf.float32, name=None), name='tf.math.add/Add:0', description="created by layer 'tf.math.add'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 320, 320, 32), dtype=tf.float32, name=None), name='tf.nn.relu/Relu:0', description="created by layer 'tf.nn.relu'")
====================================================================================
layer_type: MaxPool
layer_id: 6
input_layer0: layer_id=5: KerasTensor(type_spec=TensorSpec(shape=(1, 320, 320, 32), dtype=tf.float32, name=None), name='tf.nn.relu/Relu:0', description="created by layer 'tf.nn.relu'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 32), dtype=tf.float32, name=None), name='tf.nn.max_pool2d/MaxPool2d:0', description="created by layer 'tf.nn.max_pool2d'")
====================================================================================
layer_type: Const
layer_id: 7
tf_layers_dict_shape: (32, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 8
input_layer0: layer_id=6: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 32), dtype=tf.float32, name=None), name='tf.nn.max_pool2d/MaxPool2d:0', description="created by layer 'tf.nn.max_pool2d'")
input_layer1_shape: layer_id=7: (32, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='depthwise_conv2d/depthwise:0', description="created by layer 'depthwise_conv2d'")
====================================================================================
layer_type: Const
layer_id: 9
tf_layers_dict_shape: (1, 32, 1, 1)
====================================================================================
layer_type: Add
layer_id: 10
input_layer0: layer_id=8: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='depthwise_conv2d/depthwise:0', description="created by layer 'depthwise_conv2d'")
input_layer1_shape: layer_id=9: (1, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_1/Add:0', description="created by layer 'tf.math.add_1'")
====================================================================================
layer_type: Const
layer_id: 11
tf_layers_dict_shape: (60, 32, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 12
input_layer0: layer_id=10: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_1/Add:0', description="created by layer 'tf.math.add_1'")
input_layer1_shape: layer_id=11: (60, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_1/Conv2D:0', description="created by layer 'conv2d_1'")
====================================================================================
layer_type: Const
layer_id: 13
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 14
input_layer0: layer_id=12: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_1/Conv2D:0', description="created by layer 'conv2d_1'")
input_layer1_shape: layer_id=13: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_2/Add:0', description="created by layer 'tf.math.add_2'")
====================================================================================
layer_type: ReLU
layer_id: 15
input_layer0: layer_id=14: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_2/Add:0', description="created by layer 'tf.math.add_2'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_1/Relu:0', description="created by layer 'tf.nn.relu_1'")
====================================================================================
layer_type: Const
layer_id: 16
tf_layers_dict_shape: (60, 32, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 17
input_layer0: layer_id=6: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 32), dtype=tf.float32, name=None), name='tf.nn.max_pool2d/MaxPool2d:0', description="created by layer 'tf.nn.max_pool2d'")
input_layer1_shape: layer_id=16: (60, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 60), dtype=tf.float32, name=None), name='conv2d_2/Conv2D:0', description="created by layer 'conv2d_2'")
====================================================================================
layer_type: Const
layer_id: 18
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 19
input_layer0: layer_id=17: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 60), dtype=tf.float32, name=None), name='conv2d_2/Conv2D:0', description="created by layer 'conv2d_2'")
input_layer1_shape: layer_id=18: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 60), dtype=tf.float32, name=None), name='tf.math.add_3/Add:0', description="created by layer 'tf.math.add_3'")
====================================================================================
layer_type: ReLU
layer_id: 20
input_layer0: layer_id=19: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 60), dtype=tf.float32, name=None), name='tf.math.add_3/Add:0', description="created by layer 'tf.math.add_3'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 60), dtype=tf.float32, name=None), name='tf.nn.relu_2/Relu:0', description="created by layer 'tf.nn.relu_2'")
====================================================================================
layer_type: Const
layer_id: 21
tf_layers_dict_shape: (60, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 22
input_layer0: layer_id=20: KerasTensor(type_spec=TensorSpec(shape=(1, 160, 160, 60), dtype=tf.float32, name=None), name='tf.nn.relu_2/Relu:0', description="created by layer 'tf.nn.relu_2'")
input_layer1_shape: layer_id=21: (60, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_1/depthwise:0', description="created by layer 'depthwise_conv2d_1'")
====================================================================================
layer_type: Const
layer_id: 23
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 24
input_layer0: layer_id=22: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_1/depthwise:0', description="created by layer 'depthwise_conv2d_1'")
input_layer1_shape: layer_id=23: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_4/Add:0', description="created by layer 'tf.math.add_4'")
====================================================================================
layer_type: Const
layer_id: 25
tf_layers_dict_shape: (60, 60, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 26
input_layer0: layer_id=24: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_4/Add:0', description="created by layer 'tf.math.add_4'")
input_layer1_shape: layer_id=25: (60, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_3/Conv2D:0', description="created by layer 'conv2d_3'")
====================================================================================
layer_type: Const
layer_id: 27
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 28
input_layer0: layer_id=26: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_3/Conv2D:0', description="created by layer 'conv2d_3'")
input_layer1_shape: layer_id=27: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_5/Add:0', description="created by layer 'tf.math.add_5'")
====================================================================================
layer_type: ReLU
layer_id: 29
input_layer0: layer_id=28: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_5/Add:0', description="created by layer 'tf.math.add_5'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_3/Relu:0', description="created by layer 'tf.nn.relu_3'")
====================================================================================
layer_type: Concat
layer_id: 30
input_layer0: layer_id=15: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_1/Relu:0', description="created by layer 'tf.nn.relu_1'")
input_layer1: layer_id=29: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_3/Relu:0', description="created by layer 'tf.nn.relu_3'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat/concat:0', description="created by layer 'tf.concat'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 31
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 32
input_layer0: layer_id=30: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat/concat:0', description="created by layer 'tf.concat'")
input_layer1_shape: layer_id=31: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape/Reshape:0', description="created by layer 'tf.reshape'")
====================================================================================
layer_type: Const
layer_id: 33
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 34
input_layer0: layer_id=32: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape/Reshape:0', description="created by layer 'tf.reshape'")
input_layer1_shape: layer_id=33: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose/transpose:0', description="created by layer 'tf.compat.v1.transpose'")
====================================================================================
layer_type: Const
layer_id: 35
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 36
input_layer0: layer_id=34: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose/transpose:0', description="created by layer 'tf.compat.v1.transpose'")
input_layer1_shape: layer_id=35: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_1/Reshape:0', description="created by layer 'tf.reshape_1'")
====================================================================================
layer_type: Const
layer_id: 37
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 38
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 39
input_layer0: layer_id=36: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_1/Reshape:0', description="created by layer 'tf.reshape_1'")
input_layer1: layer_id=37: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 39:3 KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda/Split:0', description="created by layer 'lambda'")
tf_layers_dict1: layer_id_port: 39:4 KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda/Split:1', description="created by layer 'lambda'")
====================================================================================
layer_type: Const
layer_id: 40
tf_layers_dict_shape: (60, 60, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 41
input_layer0: layer_id=39:4: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda/Split:1', description="created by layer 'lambda'")
input_layer1_shape: layer_id=40: (60, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_4/Conv2D:0', description="created by layer 'conv2d_4'")
====================================================================================
layer_type: Const
layer_id: 42
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 43
input_layer0: layer_id=41: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_4/Conv2D:0', description="created by layer 'conv2d_4'")
input_layer1_shape: layer_id=42: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_6/Add:0', description="created by layer 'tf.math.add_6'")
====================================================================================
layer_type: ReLU
layer_id: 44
input_layer0: layer_id=43: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_6/Add:0', description="created by layer 'tf.math.add_6'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_4/Relu:0', description="created by layer 'tf.nn.relu_4'")
====================================================================================
layer_type: Const
layer_id: 45
tf_layers_dict_shape: (60, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 46
input_layer0: layer_id=44: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_4/Relu:0', description="created by layer 'tf.nn.relu_4'")
input_layer1_shape: layer_id=45: (60, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_2/depthwise:0', description="created by layer 'depthwise_conv2d_2'")
====================================================================================
layer_type: Const
layer_id: 47
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 48
input_layer0: layer_id=46: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_2/depthwise:0', description="created by layer 'depthwise_conv2d_2'")
input_layer1_shape: layer_id=47: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_7/Add:0', description="created by layer 'tf.math.add_7'")
====================================================================================
layer_type: Const
layer_id: 49
tf_layers_dict_shape: (60, 60, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 50
input_layer0: layer_id=48: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_7/Add:0', description="created by layer 'tf.math.add_7'")
input_layer1_shape: layer_id=49: (60, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_5/Conv2D:0', description="created by layer 'conv2d_5'")
====================================================================================
layer_type: Const
layer_id: 51
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 52
input_layer0: layer_id=50: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_5/Conv2D:0', description="created by layer 'conv2d_5'")
input_layer1_shape: layer_id=51: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_8/Add:0', description="created by layer 'tf.math.add_8'")
====================================================================================
layer_type: ReLU
layer_id: 53
input_layer0: layer_id=52: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_8/Add:0', description="created by layer 'tf.math.add_8'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_5/Relu:0', description="created by layer 'tf.nn.relu_5'")
====================================================================================
layer_type: Concat
layer_id: 54
input_layer0: layer_id=39:3: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda/Split:0', description="created by layer 'lambda'")
input_layer1: layer_id=53: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_5/Relu:0', description="created by layer 'tf.nn.relu_5'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat_1/concat:0', description="created by layer 'tf.concat_1'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 55
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 56
input_layer0: layer_id=54: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat_1/concat:0', description="created by layer 'tf.concat_1'")
input_layer1_shape: layer_id=55: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape_2/Reshape:0', description="created by layer 'tf.reshape_2'")
====================================================================================
layer_type: Const
layer_id: 57
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 58
input_layer0: layer_id=56: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape_2/Reshape:0', description="created by layer 'tf.reshape_2'")
input_layer1_shape: layer_id=57: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_1/transpose:0', description="created by layer 'tf.compat.v1.transpose_1'")
====================================================================================
layer_type: Const
layer_id: 59
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 60
input_layer0: layer_id=58: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_1/transpose:0', description="created by layer 'tf.compat.v1.transpose_1'")
input_layer1_shape: layer_id=59: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_3/Reshape:0', description="created by layer 'tf.reshape_3'")
====================================================================================
layer_type: Const
layer_id: 61
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 62
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 63
input_layer0: layer_id=60: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_3/Reshape:0', description="created by layer 'tf.reshape_3'")
input_layer1: layer_id=61: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 63:3 KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_1/Split:0', description="created by layer 'lambda_1'")
tf_layers_dict1: layer_id_port: 63:4 KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_1/Split:1', description="created by layer 'lambda_1'")
====================================================================================
layer_type: Const
layer_id: 64
tf_layers_dict_shape: (60, 60, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 65
input_layer0: layer_id=63:4: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_1/Split:1', description="created by layer 'lambda_1'")
input_layer1_shape: layer_id=64: (60, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_6/Conv2D:0', description="created by layer 'conv2d_6'")
====================================================================================
layer_type: Const
layer_id: 66
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 67
input_layer0: layer_id=65: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_6/Conv2D:0', description="created by layer 'conv2d_6'")
input_layer1_shape: layer_id=66: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_9/Add:0', description="created by layer 'tf.math.add_9'")
====================================================================================
layer_type: ReLU
layer_id: 68
input_layer0: layer_id=67: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_9/Add:0', description="created by layer 'tf.math.add_9'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_6/Relu:0', description="created by layer 'tf.nn.relu_6'")
====================================================================================
layer_type: Const
layer_id: 69
tf_layers_dict_shape: (60, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 70
input_layer0: layer_id=68: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_6/Relu:0', description="created by layer 'tf.nn.relu_6'")
input_layer1_shape: layer_id=69: (60, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_3/depthwise:0', description="created by layer 'depthwise_conv2d_3'")
====================================================================================
layer_type: Const
layer_id: 71
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 72
input_layer0: layer_id=70: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_3/depthwise:0', description="created by layer 'depthwise_conv2d_3'")
input_layer1_shape: layer_id=71: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_10/Add:0', description="created by layer 'tf.math.add_10'")
====================================================================================
layer_type: Const
layer_id: 73
tf_layers_dict_shape: (60, 60, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 74
input_layer0: layer_id=72: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_10/Add:0', description="created by layer 'tf.math.add_10'")
input_layer1_shape: layer_id=73: (60, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_7/Conv2D:0', description="created by layer 'conv2d_7'")
====================================================================================
layer_type: Const
layer_id: 75
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 76
input_layer0: layer_id=74: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_7/Conv2D:0', description="created by layer 'conv2d_7'")
input_layer1_shape: layer_id=75: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_11/Add:0', description="created by layer 'tf.math.add_11'")
====================================================================================
layer_type: ReLU
layer_id: 77
input_layer0: layer_id=76: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_11/Add:0', description="created by layer 'tf.math.add_11'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_7/Relu:0', description="created by layer 'tf.nn.relu_7'")
====================================================================================
layer_type: Concat
layer_id: 78
input_layer0: layer_id=63:3: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_1/Split:0', description="created by layer 'lambda_1'")
input_layer1: layer_id=77: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_7/Relu:0', description="created by layer 'tf.nn.relu_7'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat_2/concat:0', description="created by layer 'tf.concat_2'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 79
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 80
input_layer0: layer_id=78: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat_2/concat:0', description="created by layer 'tf.concat_2'")
input_layer1_shape: layer_id=79: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape_4/Reshape:0', description="created by layer 'tf.reshape_4'")
====================================================================================
layer_type: Const
layer_id: 81
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 82
input_layer0: layer_id=80: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape_4/Reshape:0', description="created by layer 'tf.reshape_4'")
input_layer1_shape: layer_id=81: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_2/transpose:0', description="created by layer 'tf.compat.v1.transpose_2'")
====================================================================================
layer_type: Const
layer_id: 83
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 84
input_layer0: layer_id=82: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_2/transpose:0', description="created by layer 'tf.compat.v1.transpose_2'")
input_layer1_shape: layer_id=83: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_5/Reshape:0', description="created by layer 'tf.reshape_5'")
====================================================================================
layer_type: Const
layer_id: 85
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 86
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 87
input_layer0: layer_id=84: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_5/Reshape:0', description="created by layer 'tf.reshape_5'")
input_layer1: layer_id=85: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 87:3 KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_2/Split:0', description="created by layer 'lambda_2'")
tf_layers_dict1: layer_id_port: 87:4 KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_2/Split:1', description="created by layer 'lambda_2'")
====================================================================================
layer_type: Const
layer_id: 88
tf_layers_dict_shape: (60, 60, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 89
input_layer0: layer_id=87:4: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_2/Split:1', description="created by layer 'lambda_2'")
input_layer1_shape: layer_id=88: (60, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_8/Conv2D:0', description="created by layer 'conv2d_8'")
====================================================================================
layer_type: Const
layer_id: 90
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 91
input_layer0: layer_id=89: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_8/Conv2D:0', description="created by layer 'conv2d_8'")
input_layer1_shape: layer_id=90: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_12/Add:0', description="created by layer 'tf.math.add_12'")
====================================================================================
layer_type: ReLU
layer_id: 92
input_layer0: layer_id=91: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_12/Add:0', description="created by layer 'tf.math.add_12'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_8/Relu:0', description="created by layer 'tf.nn.relu_8'")
====================================================================================
layer_type: Const
layer_id: 93
tf_layers_dict_shape: (60, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 94
input_layer0: layer_id=92: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_8/Relu:0', description="created by layer 'tf.nn.relu_8'")
input_layer1_shape: layer_id=93: (60, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_4/depthwise:0', description="created by layer 'depthwise_conv2d_4'")
====================================================================================
layer_type: Const
layer_id: 95
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 96
input_layer0: layer_id=94: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='depthwise_conv2d_4/depthwise:0', description="created by layer 'depthwise_conv2d_4'")
input_layer1_shape: layer_id=95: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_13/Add:0', description="created by layer 'tf.math.add_13'")
====================================================================================
layer_type: Const
layer_id: 97
tf_layers_dict_shape: (60, 60, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 98
input_layer0: layer_id=96: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_13/Add:0', description="created by layer 'tf.math.add_13'")
input_layer1_shape: layer_id=97: (60, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_9/Conv2D:0', description="created by layer 'conv2d_9'")
====================================================================================
layer_type: Const
layer_id: 99
tf_layers_dict_shape: (1, 60, 1, 1)
====================================================================================
layer_type: Add
layer_id: 100
input_layer0: layer_id=98: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='conv2d_9/Conv2D:0', description="created by layer 'conv2d_9'")
input_layer1_shape: layer_id=99: (1, 60, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_14/Add:0', description="created by layer 'tf.math.add_14'")
====================================================================================
layer_type: ReLU
layer_id: 101
input_layer0: layer_id=100: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.math.add_14/Add:0', description="created by layer 'tf.math.add_14'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_9/Relu:0', description="created by layer 'tf.nn.relu_9'")
====================================================================================
layer_type: Concat
layer_id: 102
input_layer0: layer_id=87:3: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='lambda_2/Split:0', description="created by layer 'lambda_2'")
input_layer1: layer_id=101: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60), dtype=tf.float32, name=None), name='tf.nn.relu_9/Relu:0', description="created by layer 'tf.nn.relu_9'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat_3/concat:0', description="created by layer 'tf.concat_3'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 103
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 104
input_layer0: layer_id=102: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.concat_3/concat:0', description="created by layer 'tf.concat_3'")
input_layer1_shape: layer_id=103: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape_6/Reshape:0', description="created by layer 'tf.reshape_6'")
====================================================================================
layer_type: Const
layer_id: 105
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 106
input_layer0: layer_id=104: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 2, 60), dtype=tf.float32, name=None), name='tf.reshape_6/Reshape:0', description="created by layer 'tf.reshape_6'")
input_layer1_shape: layer_id=105: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_3/transpose:0', description="created by layer 'tf.compat.v1.transpose_3'")
====================================================================================
layer_type: Const
layer_id: 107
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 108
input_layer0: layer_id=106: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 60, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_3/transpose:0', description="created by layer 'tf.compat.v1.transpose_3'")
input_layer1_shape: layer_id=107: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_7/Reshape:0', description="created by layer 'tf.reshape_7'")
====================================================================================
layer_type: Const
layer_id: 109
tf_layers_dict_shape: (120, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 110
input_layer0: layer_id=108: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_7/Reshape:0', description="created by layer 'tf.reshape_7'")
input_layer1_shape: layer_id=109: (120, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 120), dtype=tf.float32, name=None), name='depthwise_conv2d_5/depthwise:0', description="created by layer 'depthwise_conv2d_5'")
====================================================================================
layer_type: Const
layer_id: 111
tf_layers_dict_shape: (1, 120, 1, 1)
====================================================================================
layer_type: Add
layer_id: 112
input_layer0: layer_id=110: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 120), dtype=tf.float32, name=None), name='depthwise_conv2d_5/depthwise:0', description="created by layer 'depthwise_conv2d_5'")
input_layer1_shape: layer_id=111: (1, 120, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 120), dtype=tf.float32, name=None), name='tf.math.add_15/Add:0', description="created by layer 'tf.math.add_15'")
====================================================================================
layer_type: Const
layer_id: 113
tf_layers_dict_shape: (116, 120, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 114
input_layer0: layer_id=112: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 120), dtype=tf.float32, name=None), name='tf.math.add_15/Add:0', description="created by layer 'tf.math.add_15'")
input_layer1_shape: layer_id=113: (116, 120, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_10/Conv2D:0', description="created by layer 'conv2d_10'")
====================================================================================
layer_type: Const
layer_id: 115
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 116
input_layer0: layer_id=114: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_10/Conv2D:0', description="created by layer 'conv2d_10'")
input_layer1_shape: layer_id=115: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_16/Add:0', description="created by layer 'tf.math.add_16'")
====================================================================================
layer_type: ReLU
layer_id: 117
input_layer0: layer_id=116: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_16/Add:0', description="created by layer 'tf.math.add_16'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_10/Relu:0', description="created by layer 'tf.nn.relu_10'")
====================================================================================
layer_type: Const
layer_id: 118
tf_layers_dict_shape: (116, 120, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 119
input_layer0: layer_id=108: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_7/Reshape:0', description="created by layer 'tf.reshape_7'")
input_layer1_shape: layer_id=118: (116, 120, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 116), dtype=tf.float32, name=None), name='conv2d_11/Conv2D:0', description="created by layer 'conv2d_11'")
====================================================================================
layer_type: Const
layer_id: 120
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 121
input_layer0: layer_id=119: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 116), dtype=tf.float32, name=None), name='conv2d_11/Conv2D:0', description="created by layer 'conv2d_11'")
input_layer1_shape: layer_id=120: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 116), dtype=tf.float32, name=None), name='tf.math.add_17/Add:0', description="created by layer 'tf.math.add_17'")
====================================================================================
layer_type: ReLU
layer_id: 122
input_layer0: layer_id=121: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 116), dtype=tf.float32, name=None), name='tf.math.add_17/Add:0', description="created by layer 'tf.math.add_17'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 116), dtype=tf.float32, name=None), name='tf.nn.relu_11/Relu:0', description="created by layer 'tf.nn.relu_11'")
====================================================================================
layer_type: Const
layer_id: 123
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 124
input_layer0: layer_id=122: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 116), dtype=tf.float32, name=None), name='tf.nn.relu_11/Relu:0', description="created by layer 'tf.nn.relu_11'")
input_layer1_shape: layer_id=123: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_6/depthwise:0', description="created by layer 'depthwise_conv2d_6'")
====================================================================================
layer_type: Const
layer_id: 125
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 126
input_layer0: layer_id=124: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_6/depthwise:0', description="created by layer 'depthwise_conv2d_6'")
input_layer1_shape: layer_id=125: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_18/Add:0', description="created by layer 'tf.math.add_18'")
====================================================================================
layer_type: Const
layer_id: 127
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 128
input_layer0: layer_id=126: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_18/Add:0', description="created by layer 'tf.math.add_18'")
input_layer1_shape: layer_id=127: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_12/Conv2D:0', description="created by layer 'conv2d_12'")
====================================================================================
layer_type: Const
layer_id: 129
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 130
input_layer0: layer_id=128: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_12/Conv2D:0', description="created by layer 'conv2d_12'")
input_layer1_shape: layer_id=129: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_19/Add:0', description="created by layer 'tf.math.add_19'")
====================================================================================
layer_type: ReLU
layer_id: 131
input_layer0: layer_id=130: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_19/Add:0', description="created by layer 'tf.math.add_19'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_12/Relu:0', description="created by layer 'tf.nn.relu_12'")
====================================================================================
layer_type: Concat
layer_id: 132
input_layer0: layer_id=117: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_10/Relu:0', description="created by layer 'tf.nn.relu_10'")
input_layer1: layer_id=131: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_12/Relu:0', description="created by layer 'tf.nn.relu_12'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_4/concat:0', description="created by layer 'tf.concat_4'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 133
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 134
input_layer0: layer_id=132: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_4/concat:0', description="created by layer 'tf.concat_4'")
input_layer1_shape: layer_id=133: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_8/Reshape:0', description="created by layer 'tf.reshape_8'")
====================================================================================
layer_type: Const
layer_id: 135
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 136
input_layer0: layer_id=134: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_8/Reshape:0', description="created by layer 'tf.reshape_8'")
input_layer1_shape: layer_id=135: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_4/transpose:0', description="created by layer 'tf.compat.v1.transpose_4'")
====================================================================================
layer_type: Const
layer_id: 137
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 138
input_layer0: layer_id=136: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_4/transpose:0', description="created by layer 'tf.compat.v1.transpose_4'")
input_layer1_shape: layer_id=137: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_9/Reshape:0', description="created by layer 'tf.reshape_9'")
====================================================================================
layer_type: Const
layer_id: 139
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 140
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 141
input_layer0: layer_id=138: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_9/Reshape:0', description="created by layer 'tf.reshape_9'")
input_layer1: layer_id=139: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 141:3 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_3/Split:0', description="created by layer 'lambda_3'")
tf_layers_dict1: layer_id_port: 141:4 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_3/Split:1', description="created by layer 'lambda_3'")
====================================================================================
layer_type: Const
layer_id: 142
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 143
input_layer0: layer_id=141:4: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_3/Split:1', description="created by layer 'lambda_3'")
input_layer1_shape: layer_id=142: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_13/Conv2D:0', description="created by layer 'conv2d_13'")
====================================================================================
layer_type: Const
layer_id: 144
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 145
input_layer0: layer_id=143: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_13/Conv2D:0', description="created by layer 'conv2d_13'")
input_layer1_shape: layer_id=144: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_20/Add:0', description="created by layer 'tf.math.add_20'")
====================================================================================
layer_type: ReLU
layer_id: 146
input_layer0: layer_id=145: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_20/Add:0', description="created by layer 'tf.math.add_20'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_13/Relu:0', description="created by layer 'tf.nn.relu_13'")
====================================================================================
layer_type: Const
layer_id: 147
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 148
input_layer0: layer_id=146: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_13/Relu:0', description="created by layer 'tf.nn.relu_13'")
input_layer1_shape: layer_id=147: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_7/depthwise:0', description="created by layer 'depthwise_conv2d_7'")
====================================================================================
layer_type: Const
layer_id: 149
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 150
input_layer0: layer_id=148: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_7/depthwise:0', description="created by layer 'depthwise_conv2d_7'")
input_layer1_shape: layer_id=149: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_21/Add:0', description="created by layer 'tf.math.add_21'")
====================================================================================
layer_type: Const
layer_id: 151
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 152
input_layer0: layer_id=150: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_21/Add:0', description="created by layer 'tf.math.add_21'")
input_layer1_shape: layer_id=151: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_14/Conv2D:0', description="created by layer 'conv2d_14'")
====================================================================================
layer_type: Const
layer_id: 153
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 154
input_layer0: layer_id=152: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_14/Conv2D:0', description="created by layer 'conv2d_14'")
input_layer1_shape: layer_id=153: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_22/Add:0', description="created by layer 'tf.math.add_22'")
====================================================================================
layer_type: ReLU
layer_id: 155
input_layer0: layer_id=154: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_22/Add:0', description="created by layer 'tf.math.add_22'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_14/Relu:0', description="created by layer 'tf.nn.relu_14'")
====================================================================================
layer_type: Concat
layer_id: 156
input_layer0: layer_id=141:3: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_3/Split:0', description="created by layer 'lambda_3'")
input_layer1: layer_id=155: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_14/Relu:0', description="created by layer 'tf.nn.relu_14'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_5/concat:0', description="created by layer 'tf.concat_5'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 157
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 158
input_layer0: layer_id=156: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_5/concat:0', description="created by layer 'tf.concat_5'")
input_layer1_shape: layer_id=157: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_10/Reshape:0', description="created by layer 'tf.reshape_10'")
====================================================================================
layer_type: Const
layer_id: 159
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 160
input_layer0: layer_id=158: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_10/Reshape:0', description="created by layer 'tf.reshape_10'")
input_layer1_shape: layer_id=159: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_5/transpose:0', description="created by layer 'tf.compat.v1.transpose_5'")
====================================================================================
layer_type: Const
layer_id: 161
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 162
input_layer0: layer_id=160: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_5/transpose:0', description="created by layer 'tf.compat.v1.transpose_5'")
input_layer1_shape: layer_id=161: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_11/Reshape:0', description="created by layer 'tf.reshape_11'")
====================================================================================
layer_type: Const
layer_id: 163
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 164
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 165
input_layer0: layer_id=162: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_11/Reshape:0', description="created by layer 'tf.reshape_11'")
input_layer1: layer_id=163: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 165:3 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_4/Split:0', description="created by layer 'lambda_4'")
tf_layers_dict1: layer_id_port: 165:4 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_4/Split:1', description="created by layer 'lambda_4'")
====================================================================================
layer_type: Const
layer_id: 166
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 167
input_layer0: layer_id=165:4: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_4/Split:1', description="created by layer 'lambda_4'")
input_layer1_shape: layer_id=166: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_15/Conv2D:0', description="created by layer 'conv2d_15'")
====================================================================================
layer_type: Const
layer_id: 168
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 169
input_layer0: layer_id=167: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_15/Conv2D:0', description="created by layer 'conv2d_15'")
input_layer1_shape: layer_id=168: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_23/Add:0', description="created by layer 'tf.math.add_23'")
====================================================================================
layer_type: ReLU
layer_id: 170
input_layer0: layer_id=169: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_23/Add:0', description="created by layer 'tf.math.add_23'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_15/Relu:0', description="created by layer 'tf.nn.relu_15'")
====================================================================================
layer_type: Const
layer_id: 171
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 172
input_layer0: layer_id=170: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_15/Relu:0', description="created by layer 'tf.nn.relu_15'")
input_layer1_shape: layer_id=171: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_8/depthwise:0', description="created by layer 'depthwise_conv2d_8'")
====================================================================================
layer_type: Const
layer_id: 173
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 174
input_layer0: layer_id=172: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_8/depthwise:0', description="created by layer 'depthwise_conv2d_8'")
input_layer1_shape: layer_id=173: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_24/Add:0', description="created by layer 'tf.math.add_24'")
====================================================================================
layer_type: Const
layer_id: 175
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 176
input_layer0: layer_id=174: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_24/Add:0', description="created by layer 'tf.math.add_24'")
input_layer1_shape: layer_id=175: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_16/Conv2D:0', description="created by layer 'conv2d_16'")
====================================================================================
layer_type: Const
layer_id: 177
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 178
input_layer0: layer_id=176: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_16/Conv2D:0', description="created by layer 'conv2d_16'")
input_layer1_shape: layer_id=177: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_25/Add:0', description="created by layer 'tf.math.add_25'")
====================================================================================
layer_type: ReLU
layer_id: 179
input_layer0: layer_id=178: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_25/Add:0', description="created by layer 'tf.math.add_25'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_16/Relu:0', description="created by layer 'tf.nn.relu_16'")
====================================================================================
layer_type: Concat
layer_id: 180
input_layer0: layer_id=165:3: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_4/Split:0', description="created by layer 'lambda_4'")
input_layer1: layer_id=179: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_16/Relu:0', description="created by layer 'tf.nn.relu_16'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_6/concat:0', description="created by layer 'tf.concat_6'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 181
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 182
input_layer0: layer_id=180: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_6/concat:0', description="created by layer 'tf.concat_6'")
input_layer1_shape: layer_id=181: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_12/Reshape:0', description="created by layer 'tf.reshape_12'")
====================================================================================
layer_type: Const
layer_id: 183
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 184
input_layer0: layer_id=182: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_12/Reshape:0', description="created by layer 'tf.reshape_12'")
input_layer1_shape: layer_id=183: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_6/transpose:0', description="created by layer 'tf.compat.v1.transpose_6'")
====================================================================================
layer_type: Const
layer_id: 185
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 186
input_layer0: layer_id=184: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_6/transpose:0', description="created by layer 'tf.compat.v1.transpose_6'")
input_layer1_shape: layer_id=185: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_13/Reshape:0', description="created by layer 'tf.reshape_13'")
====================================================================================
layer_type: Const
layer_id: 187
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 188
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 189
input_layer0: layer_id=186: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_13/Reshape:0', description="created by layer 'tf.reshape_13'")
input_layer1: layer_id=187: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 189:3 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_5/Split:0', description="created by layer 'lambda_5'")
tf_layers_dict1: layer_id_port: 189:4 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_5/Split:1', description="created by layer 'lambda_5'")
====================================================================================
layer_type: Const
layer_id: 190
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 191
input_layer0: layer_id=189:4: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_5/Split:1', description="created by layer 'lambda_5'")
input_layer1_shape: layer_id=190: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_17/Conv2D:0', description="created by layer 'conv2d_17'")
====================================================================================
layer_type: Const
layer_id: 192
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 193
input_layer0: layer_id=191: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_17/Conv2D:0', description="created by layer 'conv2d_17'")
input_layer1_shape: layer_id=192: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_26/Add:0', description="created by layer 'tf.math.add_26'")
====================================================================================
layer_type: ReLU
layer_id: 194
input_layer0: layer_id=193: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_26/Add:0', description="created by layer 'tf.math.add_26'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_17/Relu:0', description="created by layer 'tf.nn.relu_17'")
====================================================================================
layer_type: Const
layer_id: 195
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 196
input_layer0: layer_id=194: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_17/Relu:0', description="created by layer 'tf.nn.relu_17'")
input_layer1_shape: layer_id=195: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_9/depthwise:0', description="created by layer 'depthwise_conv2d_9'")
====================================================================================
layer_type: Const
layer_id: 197
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 198
input_layer0: layer_id=196: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_9/depthwise:0', description="created by layer 'depthwise_conv2d_9'")
input_layer1_shape: layer_id=197: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_27/Add:0', description="created by layer 'tf.math.add_27'")
====================================================================================
layer_type: Const
layer_id: 199
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 200
input_layer0: layer_id=198: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_27/Add:0', description="created by layer 'tf.math.add_27'")
input_layer1_shape: layer_id=199: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_18/Conv2D:0', description="created by layer 'conv2d_18'")
====================================================================================
layer_type: Const
layer_id: 201
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 202
input_layer0: layer_id=200: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_18/Conv2D:0', description="created by layer 'conv2d_18'")
input_layer1_shape: layer_id=201: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_28/Add:0', description="created by layer 'tf.math.add_28'")
====================================================================================
layer_type: ReLU
layer_id: 203
input_layer0: layer_id=202: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_28/Add:0', description="created by layer 'tf.math.add_28'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_18/Relu:0', description="created by layer 'tf.nn.relu_18'")
====================================================================================
layer_type: Concat
layer_id: 204
input_layer0: layer_id=189:3: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_5/Split:0', description="created by layer 'lambda_5'")
input_layer1: layer_id=203: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_18/Relu:0', description="created by layer 'tf.nn.relu_18'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_7/concat:0', description="created by layer 'tf.concat_7'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 205
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 206
input_layer0: layer_id=204: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_7/concat:0', description="created by layer 'tf.concat_7'")
input_layer1_shape: layer_id=205: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_14/Reshape:0', description="created by layer 'tf.reshape_14'")
====================================================================================
layer_type: Const
layer_id: 207
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 208
input_layer0: layer_id=206: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_14/Reshape:0', description="created by layer 'tf.reshape_14'")
input_layer1_shape: layer_id=207: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_7/transpose:0', description="created by layer 'tf.compat.v1.transpose_7'")
====================================================================================
layer_type: Const
layer_id: 209
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 210
input_layer0: layer_id=208: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_7/transpose:0', description="created by layer 'tf.compat.v1.transpose_7'")
input_layer1_shape: layer_id=209: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_15/Reshape:0', description="created by layer 'tf.reshape_15'")
====================================================================================
layer_type: Const
layer_id: 211
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 212
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 213
input_layer0: layer_id=210: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_15/Reshape:0', description="created by layer 'tf.reshape_15'")
input_layer1: layer_id=211: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 213:3 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_6/Split:0', description="created by layer 'lambda_6'")
tf_layers_dict1: layer_id_port: 213:4 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_6/Split:1', description="created by layer 'lambda_6'")
====================================================================================
layer_type: Const
layer_id: 214
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 215
input_layer0: layer_id=213:4: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_6/Split:1', description="created by layer 'lambda_6'")
input_layer1_shape: layer_id=214: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_19/Conv2D:0', description="created by layer 'conv2d_19'")
====================================================================================
layer_type: Const
layer_id: 216
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 217
input_layer0: layer_id=215: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_19/Conv2D:0', description="created by layer 'conv2d_19'")
input_layer1_shape: layer_id=216: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_29/Add:0', description="created by layer 'tf.math.add_29'")
====================================================================================
layer_type: ReLU
layer_id: 218
input_layer0: layer_id=217: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_29/Add:0', description="created by layer 'tf.math.add_29'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_19/Relu:0', description="created by layer 'tf.nn.relu_19'")
====================================================================================
layer_type: Const
layer_id: 219
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 220
input_layer0: layer_id=218: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_19/Relu:0', description="created by layer 'tf.nn.relu_19'")
input_layer1_shape: layer_id=219: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_10/depthwise:0', description="created by layer 'depthwise_conv2d_10'")
====================================================================================
layer_type: Const
layer_id: 221
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 222
input_layer0: layer_id=220: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_10/depthwise:0', description="created by layer 'depthwise_conv2d_10'")
input_layer1_shape: layer_id=221: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_30/Add:0', description="created by layer 'tf.math.add_30'")
====================================================================================
layer_type: Const
layer_id: 223
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 224
input_layer0: layer_id=222: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_30/Add:0', description="created by layer 'tf.math.add_30'")
input_layer1_shape: layer_id=223: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_20/Conv2D:0', description="created by layer 'conv2d_20'")
====================================================================================
layer_type: Const
layer_id: 225
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 226
input_layer0: layer_id=224: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_20/Conv2D:0', description="created by layer 'conv2d_20'")
input_layer1_shape: layer_id=225: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_31/Add:0', description="created by layer 'tf.math.add_31'")
====================================================================================
layer_type: ReLU
layer_id: 227
input_layer0: layer_id=226: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_31/Add:0', description="created by layer 'tf.math.add_31'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_20/Relu:0', description="created by layer 'tf.nn.relu_20'")
====================================================================================
layer_type: Concat
layer_id: 228
input_layer0: layer_id=213:3: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_6/Split:0', description="created by layer 'lambda_6'")
input_layer1: layer_id=227: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_20/Relu:0', description="created by layer 'tf.nn.relu_20'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_8/concat:0', description="created by layer 'tf.concat_8'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 229
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 230
input_layer0: layer_id=228: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_8/concat:0', description="created by layer 'tf.concat_8'")
input_layer1_shape: layer_id=229: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_16/Reshape:0', description="created by layer 'tf.reshape_16'")
====================================================================================
layer_type: Const
layer_id: 231
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 232
input_layer0: layer_id=230: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_16/Reshape:0', description="created by layer 'tf.reshape_16'")
input_layer1_shape: layer_id=231: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_8/transpose:0', description="created by layer 'tf.compat.v1.transpose_8'")
====================================================================================
layer_type: Const
layer_id: 233
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 234
input_layer0: layer_id=232: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_8/transpose:0', description="created by layer 'tf.compat.v1.transpose_8'")
input_layer1_shape: layer_id=233: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_17/Reshape:0', description="created by layer 'tf.reshape_17'")
====================================================================================
layer_type: Const
layer_id: 235
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 236
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 237
input_layer0: layer_id=234: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_17/Reshape:0', description="created by layer 'tf.reshape_17'")
input_layer1: layer_id=235: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 237:3 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_7/Split:0', description="created by layer 'lambda_7'")
tf_layers_dict1: layer_id_port: 237:4 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_7/Split:1', description="created by layer 'lambda_7'")
====================================================================================
layer_type: Const
layer_id: 238
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 239
input_layer0: layer_id=237:4: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_7/Split:1', description="created by layer 'lambda_7'")
input_layer1_shape: layer_id=238: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_21/Conv2D:0', description="created by layer 'conv2d_21'")
====================================================================================
layer_type: Const
layer_id: 240
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 241
input_layer0: layer_id=239: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_21/Conv2D:0', description="created by layer 'conv2d_21'")
input_layer1_shape: layer_id=240: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_32/Add:0', description="created by layer 'tf.math.add_32'")
====================================================================================
layer_type: ReLU
layer_id: 242
input_layer0: layer_id=241: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_32/Add:0', description="created by layer 'tf.math.add_32'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_21/Relu:0', description="created by layer 'tf.nn.relu_21'")
====================================================================================
layer_type: Const
layer_id: 243
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 244
input_layer0: layer_id=242: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_21/Relu:0', description="created by layer 'tf.nn.relu_21'")
input_layer1_shape: layer_id=243: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_11/depthwise:0', description="created by layer 'depthwise_conv2d_11'")
====================================================================================
layer_type: Const
layer_id: 245
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 246
input_layer0: layer_id=244: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_11/depthwise:0', description="created by layer 'depthwise_conv2d_11'")
input_layer1_shape: layer_id=245: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_33/Add:0', description="created by layer 'tf.math.add_33'")
====================================================================================
layer_type: Const
layer_id: 247
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 248
input_layer0: layer_id=246: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_33/Add:0', description="created by layer 'tf.math.add_33'")
input_layer1_shape: layer_id=247: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_22/Conv2D:0', description="created by layer 'conv2d_22'")
====================================================================================
layer_type: Const
layer_id: 249
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 250
input_layer0: layer_id=248: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_22/Conv2D:0', description="created by layer 'conv2d_22'")
input_layer1_shape: layer_id=249: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_34/Add:0', description="created by layer 'tf.math.add_34'")
====================================================================================
layer_type: ReLU
layer_id: 251
input_layer0: layer_id=250: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_34/Add:0', description="created by layer 'tf.math.add_34'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_22/Relu:0', description="created by layer 'tf.nn.relu_22'")
====================================================================================
layer_type: Concat
layer_id: 252
input_layer0: layer_id=237:3: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_7/Split:0', description="created by layer 'lambda_7'")
input_layer1: layer_id=251: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_22/Relu:0', description="created by layer 'tf.nn.relu_22'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_9/concat:0', description="created by layer 'tf.concat_9'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 253
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 254
input_layer0: layer_id=252: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_9/concat:0', description="created by layer 'tf.concat_9'")
input_layer1_shape: layer_id=253: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_18/Reshape:0', description="created by layer 'tf.reshape_18'")
====================================================================================
layer_type: Const
layer_id: 255
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 256
input_layer0: layer_id=254: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_18/Reshape:0', description="created by layer 'tf.reshape_18'")
input_layer1_shape: layer_id=255: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_9/transpose:0', description="created by layer 'tf.compat.v1.transpose_9'")
====================================================================================
layer_type: Const
layer_id: 257
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 258
input_layer0: layer_id=256: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_9/transpose:0', description="created by layer 'tf.compat.v1.transpose_9'")
input_layer1_shape: layer_id=257: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_19/Reshape:0', description="created by layer 'tf.reshape_19'")
====================================================================================
layer_type: Const
layer_id: 259
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 260
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 261
input_layer0: layer_id=258: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_19/Reshape:0', description="created by layer 'tf.reshape_19'")
input_layer1: layer_id=259: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 261:3 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_8/Split:0', description="created by layer 'lambda_8'")
tf_layers_dict1: layer_id_port: 261:4 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_8/Split:1', description="created by layer 'lambda_8'")
====================================================================================
layer_type: Const
layer_id: 262
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 263
input_layer0: layer_id=261:4: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_8/Split:1', description="created by layer 'lambda_8'")
input_layer1_shape: layer_id=262: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_23/Conv2D:0', description="created by layer 'conv2d_23'")
====================================================================================
layer_type: Const
layer_id: 264
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 265
input_layer0: layer_id=263: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_23/Conv2D:0', description="created by layer 'conv2d_23'")
input_layer1_shape: layer_id=264: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_35/Add:0', description="created by layer 'tf.math.add_35'")
====================================================================================
layer_type: ReLU
layer_id: 266
input_layer0: layer_id=265: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_35/Add:0', description="created by layer 'tf.math.add_35'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_23/Relu:0', description="created by layer 'tf.nn.relu_23'")
====================================================================================
layer_type: Const
layer_id: 267
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 268
input_layer0: layer_id=266: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_23/Relu:0', description="created by layer 'tf.nn.relu_23'")
input_layer1_shape: layer_id=267: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_12/depthwise:0', description="created by layer 'depthwise_conv2d_12'")
====================================================================================
layer_type: Const
layer_id: 269
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 270
input_layer0: layer_id=268: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_12/depthwise:0', description="created by layer 'depthwise_conv2d_12'")
input_layer1_shape: layer_id=269: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_36/Add:0', description="created by layer 'tf.math.add_36'")
====================================================================================
layer_type: Const
layer_id: 271
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 272
input_layer0: layer_id=270: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_36/Add:0', description="created by layer 'tf.math.add_36'")
input_layer1_shape: layer_id=271: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_24/Conv2D:0', description="created by layer 'conv2d_24'")
====================================================================================
layer_type: Const
layer_id: 273
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 274
input_layer0: layer_id=272: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_24/Conv2D:0', description="created by layer 'conv2d_24'")
input_layer1_shape: layer_id=273: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_37/Add:0', description="created by layer 'tf.math.add_37'")
====================================================================================
layer_type: ReLU
layer_id: 275
input_layer0: layer_id=274: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_37/Add:0', description="created by layer 'tf.math.add_37'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_24/Relu:0', description="created by layer 'tf.nn.relu_24'")
====================================================================================
layer_type: Concat
layer_id: 276
input_layer0: layer_id=261:3: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_8/Split:0', description="created by layer 'lambda_8'")
input_layer1: layer_id=275: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_24/Relu:0', description="created by layer 'tf.nn.relu_24'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_10/concat:0', description="created by layer 'tf.concat_10'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 277
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 278
input_layer0: layer_id=276: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_10/concat:0', description="created by layer 'tf.concat_10'")
input_layer1_shape: layer_id=277: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_20/Reshape:0', description="created by layer 'tf.reshape_20'")
====================================================================================
layer_type: Const
layer_id: 279
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 280
input_layer0: layer_id=278: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_20/Reshape:0', description="created by layer 'tf.reshape_20'")
input_layer1_shape: layer_id=279: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_10/transpose:0', description="created by layer 'tf.compat.v1.transpose_10'")
====================================================================================
layer_type: Const
layer_id: 281
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 282
input_layer0: layer_id=280: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_10/transpose:0', description="created by layer 'tf.compat.v1.transpose_10'")
input_layer1_shape: layer_id=281: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_21/Reshape:0', description="created by layer 'tf.reshape_21'")
====================================================================================
layer_type: Const
layer_id: 283
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 284
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 285
input_layer0: layer_id=282: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_21/Reshape:0', description="created by layer 'tf.reshape_21'")
input_layer1: layer_id=283: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 285:3 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_9/Split:0', description="created by layer 'lambda_9'")
tf_layers_dict1: layer_id_port: 285:4 KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_9/Split:1', description="created by layer 'lambda_9'")
====================================================================================
layer_type: Const
layer_id: 286
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 287
input_layer0: layer_id=285:4: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_9/Split:1', description="created by layer 'lambda_9'")
input_layer1_shape: layer_id=286: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_25/Conv2D:0', description="created by layer 'conv2d_25'")
====================================================================================
layer_type: Const
layer_id: 288
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 289
input_layer0: layer_id=287: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_25/Conv2D:0', description="created by layer 'conv2d_25'")
input_layer1_shape: layer_id=288: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_38/Add:0', description="created by layer 'tf.math.add_38'")
====================================================================================
layer_type: ReLU
layer_id: 290
input_layer0: layer_id=289: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_38/Add:0', description="created by layer 'tf.math.add_38'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_25/Relu:0', description="created by layer 'tf.nn.relu_25'")
====================================================================================
layer_type: Const
layer_id: 291
tf_layers_dict_shape: (116, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 292
input_layer0: layer_id=290: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_25/Relu:0', description="created by layer 'tf.nn.relu_25'")
input_layer1_shape: layer_id=291: (116, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_13/depthwise:0', description="created by layer 'depthwise_conv2d_13'")
====================================================================================
layer_type: Const
layer_id: 293
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 294
input_layer0: layer_id=292: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='depthwise_conv2d_13/depthwise:0', description="created by layer 'depthwise_conv2d_13'")
input_layer1_shape: layer_id=293: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_39/Add:0', description="created by layer 'tf.math.add_39'")
====================================================================================
layer_type: Const
layer_id: 295
tf_layers_dict_shape: (116, 116, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 296
input_layer0: layer_id=294: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_39/Add:0', description="created by layer 'tf.math.add_39'")
input_layer1_shape: layer_id=295: (116, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_26/Conv2D:0', description="created by layer 'conv2d_26'")
====================================================================================
layer_type: Const
layer_id: 297
tf_layers_dict_shape: (1, 116, 1, 1)
====================================================================================
layer_type: Add
layer_id: 298
input_layer0: layer_id=296: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='conv2d_26/Conv2D:0', description="created by layer 'conv2d_26'")
input_layer1_shape: layer_id=297: (1, 116, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_40/Add:0', description="created by layer 'tf.math.add_40'")
====================================================================================
layer_type: ReLU
layer_id: 299
input_layer0: layer_id=298: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.math.add_40/Add:0', description="created by layer 'tf.math.add_40'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_26/Relu:0', description="created by layer 'tf.nn.relu_26'")
====================================================================================
layer_type: Concat
layer_id: 300
input_layer0: layer_id=285:3: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='lambda_9/Split:0', description="created by layer 'lambda_9'")
input_layer1: layer_id=299: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116), dtype=tf.float32, name=None), name='tf.nn.relu_26/Relu:0', description="created by layer 'tf.nn.relu_26'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_11/concat:0', description="created by layer 'tf.concat_11'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 301
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 302
input_layer0: layer_id=300: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.concat_11/concat:0', description="created by layer 'tf.concat_11'")
input_layer1_shape: layer_id=301: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_22/Reshape:0', description="created by layer 'tf.reshape_22'")
====================================================================================
layer_type: Const
layer_id: 303
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 304
input_layer0: layer_id=302: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 2, 116), dtype=tf.float32, name=None), name='tf.reshape_22/Reshape:0', description="created by layer 'tf.reshape_22'")
input_layer1_shape: layer_id=303: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_11/transpose:0', description="created by layer 'tf.compat.v1.transpose_11'")
====================================================================================
layer_type: Const
layer_id: 305
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 306
input_layer0: layer_id=304: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 116, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_11/transpose:0', description="created by layer 'tf.compat.v1.transpose_11'")
input_layer1_shape: layer_id=305: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_23/Reshape:0', description="created by layer 'tf.reshape_23'")
====================================================================================
layer_type: Const
layer_id: 307
tf_layers_dict_shape: (232, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 308
input_layer0: layer_id=306: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_23/Reshape:0', description="created by layer 'tf.reshape_23'")
input_layer1_shape: layer_id=307: (232, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_14/depthwise:0', description="created by layer 'depthwise_conv2d_14'")
====================================================================================
layer_type: Const
layer_id: 309
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 310
input_layer0: layer_id=308: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_14/depthwise:0', description="created by layer 'depthwise_conv2d_14'")
input_layer1_shape: layer_id=309: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_41/Add:0', description="created by layer 'tf.math.add_41'")
====================================================================================
layer_type: Const
layer_id: 311
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 312
input_layer0: layer_id=310: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_41/Add:0', description="created by layer 'tf.math.add_41'")
input_layer1_shape: layer_id=311: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_27/Conv2D:0', description="created by layer 'conv2d_27'")
====================================================================================
layer_type: Const
layer_id: 313
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 314
input_layer0: layer_id=312: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_27/Conv2D:0', description="created by layer 'conv2d_27'")
input_layer1_shape: layer_id=313: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_42/Add:0', description="created by layer 'tf.math.add_42'")
====================================================================================
layer_type: ReLU
layer_id: 315
input_layer0: layer_id=314: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_42/Add:0', description="created by layer 'tf.math.add_42'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_27/Relu:0', description="created by layer 'tf.nn.relu_27'")
====================================================================================
layer_type: Const
layer_id: 316
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 317
input_layer0: layer_id=306: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_23/Reshape:0', description="created by layer 'tf.reshape_23'")
input_layer1_shape: layer_id=316: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='conv2d_28/Conv2D:0', description="created by layer 'conv2d_28'")
====================================================================================
layer_type: Const
layer_id: 318
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 319
input_layer0: layer_id=317: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='conv2d_28/Conv2D:0', description="created by layer 'conv2d_28'")
input_layer1_shape: layer_id=318: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.math.add_43/Add:0', description="created by layer 'tf.math.add_43'")
====================================================================================
layer_type: ReLU
layer_id: 320
input_layer0: layer_id=319: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.math.add_43/Add:0', description="created by layer 'tf.math.add_43'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.nn.relu_28/Relu:0', description="created by layer 'tf.nn.relu_28'")
====================================================================================
layer_type: Const
layer_id: 321
tf_layers_dict_shape: (232, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 322
input_layer0: layer_id=320: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.nn.relu_28/Relu:0', description="created by layer 'tf.nn.relu_28'")
input_layer1_shape: layer_id=321: (232, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_15/depthwise:0', description="created by layer 'depthwise_conv2d_15'")
====================================================================================
layer_type: Const
layer_id: 323
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 324
input_layer0: layer_id=322: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_15/depthwise:0', description="created by layer 'depthwise_conv2d_15'")
input_layer1_shape: layer_id=323: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_44/Add:0', description="created by layer 'tf.math.add_44'")
====================================================================================
layer_type: Const
layer_id: 325
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 326
input_layer0: layer_id=324: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_44/Add:0', description="created by layer 'tf.math.add_44'")
input_layer1_shape: layer_id=325: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_29/Conv2D:0', description="created by layer 'conv2d_29'")
====================================================================================
layer_type: Const
layer_id: 327
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 328
input_layer0: layer_id=326: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_29/Conv2D:0', description="created by layer 'conv2d_29'")
input_layer1_shape: layer_id=327: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_45/Add:0', description="created by layer 'tf.math.add_45'")
====================================================================================
layer_type: ReLU
layer_id: 329
input_layer0: layer_id=328: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_45/Add:0', description="created by layer 'tf.math.add_45'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_29/Relu:0', description="created by layer 'tf.nn.relu_29'")
====================================================================================
layer_type: Concat
layer_id: 330
input_layer0: layer_id=315: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_27/Relu:0', description="created by layer 'tf.nn.relu_27'")
input_layer1: layer_id=329: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_29/Relu:0', description="created by layer 'tf.nn.relu_29'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_12/concat:0', description="created by layer 'tf.concat_12'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 331
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 332
input_layer0: layer_id=330: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_12/concat:0', description="created by layer 'tf.concat_12'")
input_layer1_shape: layer_id=331: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_24/Reshape:0', description="created by layer 'tf.reshape_24'")
====================================================================================
layer_type: Const
layer_id: 333
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 334
input_layer0: layer_id=332: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_24/Reshape:0', description="created by layer 'tf.reshape_24'")
input_layer1_shape: layer_id=333: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_12/transpose:0', description="created by layer 'tf.compat.v1.transpose_12'")
====================================================================================
layer_type: Const
layer_id: 335
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 336
input_layer0: layer_id=334: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_12/transpose:0', description="created by layer 'tf.compat.v1.transpose_12'")
input_layer1_shape: layer_id=335: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_25/Reshape:0', description="created by layer 'tf.reshape_25'")
====================================================================================
layer_type: Const
layer_id: 337
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 338
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 339
input_layer0: layer_id=336: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_25/Reshape:0', description="created by layer 'tf.reshape_25'")
input_layer1: layer_id=337: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 339:3 KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_10/Split:0', description="created by layer 'lambda_10'")
tf_layers_dict1: layer_id_port: 339:4 KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_10/Split:1', description="created by layer 'lambda_10'")
====================================================================================
layer_type: Const
layer_id: 340
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 341
input_layer0: layer_id=339:4: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_10/Split:1', description="created by layer 'lambda_10'")
input_layer1_shape: layer_id=340: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_30/Conv2D:0', description="created by layer 'conv2d_30'")
====================================================================================
layer_type: Const
layer_id: 342
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 343
input_layer0: layer_id=341: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_30/Conv2D:0', description="created by layer 'conv2d_30'")
input_layer1_shape: layer_id=342: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_46/Add:0', description="created by layer 'tf.math.add_46'")
====================================================================================
layer_type: ReLU
layer_id: 344
input_layer0: layer_id=343: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_46/Add:0', description="created by layer 'tf.math.add_46'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_30/Relu:0', description="created by layer 'tf.nn.relu_30'")
====================================================================================
layer_type: Const
layer_id: 345
tf_layers_dict_shape: (232, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 346
input_layer0: layer_id=344: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_30/Relu:0', description="created by layer 'tf.nn.relu_30'")
input_layer1_shape: layer_id=345: (232, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_16/depthwise:0', description="created by layer 'depthwise_conv2d_16'")
====================================================================================
layer_type: Const
layer_id: 347
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 348
input_layer0: layer_id=346: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_16/depthwise:0', description="created by layer 'depthwise_conv2d_16'")
input_layer1_shape: layer_id=347: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_47/Add:0', description="created by layer 'tf.math.add_47'")
====================================================================================
layer_type: Const
layer_id: 349
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 350
input_layer0: layer_id=348: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_47/Add:0', description="created by layer 'tf.math.add_47'")
input_layer1_shape: layer_id=349: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_31/Conv2D:0', description="created by layer 'conv2d_31'")
====================================================================================
layer_type: Const
layer_id: 351
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 352
input_layer0: layer_id=350: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_31/Conv2D:0', description="created by layer 'conv2d_31'")
input_layer1_shape: layer_id=351: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_48/Add:0', description="created by layer 'tf.math.add_48'")
====================================================================================
layer_type: ReLU
layer_id: 353
input_layer0: layer_id=352: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_48/Add:0', description="created by layer 'tf.math.add_48'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_31/Relu:0', description="created by layer 'tf.nn.relu_31'")
====================================================================================
layer_type: Concat
layer_id: 354
input_layer0: layer_id=339:3: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_10/Split:0', description="created by layer 'lambda_10'")
input_layer1: layer_id=353: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_31/Relu:0', description="created by layer 'tf.nn.relu_31'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_13/concat:0', description="created by layer 'tf.concat_13'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 355
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 356
input_layer0: layer_id=354: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_13/concat:0', description="created by layer 'tf.concat_13'")
input_layer1_shape: layer_id=355: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_26/Reshape:0', description="created by layer 'tf.reshape_26'")
====================================================================================
layer_type: Const
layer_id: 357
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 358
input_layer0: layer_id=356: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_26/Reshape:0', description="created by layer 'tf.reshape_26'")
input_layer1_shape: layer_id=357: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_13/transpose:0', description="created by layer 'tf.compat.v1.transpose_13'")
====================================================================================
layer_type: Const
layer_id: 359
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 360
input_layer0: layer_id=358: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_13/transpose:0', description="created by layer 'tf.compat.v1.transpose_13'")
input_layer1_shape: layer_id=359: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_27/Reshape:0', description="created by layer 'tf.reshape_27'")
====================================================================================
layer_type: Const
layer_id: 361
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 362
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 363
input_layer0: layer_id=360: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_27/Reshape:0', description="created by layer 'tf.reshape_27'")
input_layer1: layer_id=361: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 363:3 KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_11/Split:0', description="created by layer 'lambda_11'")
tf_layers_dict1: layer_id_port: 363:4 KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_11/Split:1', description="created by layer 'lambda_11'")
====================================================================================
layer_type: Const
layer_id: 364
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 365
input_layer0: layer_id=363:4: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_11/Split:1', description="created by layer 'lambda_11'")
input_layer1_shape: layer_id=364: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_32/Conv2D:0', description="created by layer 'conv2d_32'")
====================================================================================
layer_type: Const
layer_id: 366
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 367
input_layer0: layer_id=365: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_32/Conv2D:0', description="created by layer 'conv2d_32'")
input_layer1_shape: layer_id=366: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_49/Add:0', description="created by layer 'tf.math.add_49'")
====================================================================================
layer_type: ReLU
layer_id: 368
input_layer0: layer_id=367: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_49/Add:0', description="created by layer 'tf.math.add_49'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_32/Relu:0', description="created by layer 'tf.nn.relu_32'")
====================================================================================
layer_type: Const
layer_id: 369
tf_layers_dict_shape: (232, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 370
input_layer0: layer_id=368: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_32/Relu:0', description="created by layer 'tf.nn.relu_32'")
input_layer1_shape: layer_id=369: (232, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_17/depthwise:0', description="created by layer 'depthwise_conv2d_17'")
====================================================================================
layer_type: Const
layer_id: 371
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 372
input_layer0: layer_id=370: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_17/depthwise:0', description="created by layer 'depthwise_conv2d_17'")
input_layer1_shape: layer_id=371: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_50/Add:0', description="created by layer 'tf.math.add_50'")
====================================================================================
layer_type: Const
layer_id: 373
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 374
input_layer0: layer_id=372: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_50/Add:0', description="created by layer 'tf.math.add_50'")
input_layer1_shape: layer_id=373: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_33/Conv2D:0', description="created by layer 'conv2d_33'")
====================================================================================
layer_type: Const
layer_id: 375
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 376
input_layer0: layer_id=374: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_33/Conv2D:0', description="created by layer 'conv2d_33'")
input_layer1_shape: layer_id=375: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_51/Add:0', description="created by layer 'tf.math.add_51'")
====================================================================================
layer_type: ReLU
layer_id: 377
input_layer0: layer_id=376: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_51/Add:0', description="created by layer 'tf.math.add_51'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_33/Relu:0', description="created by layer 'tf.nn.relu_33'")
====================================================================================
layer_type: Concat
layer_id: 378
input_layer0: layer_id=363:3: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_11/Split:0', description="created by layer 'lambda_11'")
input_layer1: layer_id=377: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_33/Relu:0', description="created by layer 'tf.nn.relu_33'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_14/concat:0', description="created by layer 'tf.concat_14'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 379
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 380
input_layer0: layer_id=378: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_14/concat:0', description="created by layer 'tf.concat_14'")
input_layer1_shape: layer_id=379: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_28/Reshape:0', description="created by layer 'tf.reshape_28'")
====================================================================================
layer_type: Const
layer_id: 381
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 382
input_layer0: layer_id=380: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_28/Reshape:0', description="created by layer 'tf.reshape_28'")
input_layer1_shape: layer_id=381: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_14/transpose:0', description="created by layer 'tf.compat.v1.transpose_14'")
====================================================================================
layer_type: Const
layer_id: 383
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 384
input_layer0: layer_id=382: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_14/transpose:0', description="created by layer 'tf.compat.v1.transpose_14'")
input_layer1_shape: layer_id=383: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_29/Reshape:0', description="created by layer 'tf.reshape_29'")
====================================================================================
layer_type: Const
layer_id: 385
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 386
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: VariadicSplit
layer_id: 387
input_layer0: layer_id=384: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_29/Reshape:0', description="created by layer 'tf.reshape_29'")
input_layer1: layer_id=385: Const(ndarray).shape (1,)
tf_layers_dict0: layer_id_port: 387:3 KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_12/Split:0', description="created by layer 'lambda_12'")
tf_layers_dict1: layer_id_port: 387:4 KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_12/Split:1', description="created by layer 'lambda_12'")
====================================================================================
layer_type: Const
layer_id: 388
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 389
input_layer0: layer_id=387:4: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_12/Split:1', description="created by layer 'lambda_12'")
input_layer1_shape: layer_id=388: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_34/Conv2D:0', description="created by layer 'conv2d_34'")
====================================================================================
layer_type: Const
layer_id: 390
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 391
input_layer0: layer_id=389: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_34/Conv2D:0', description="created by layer 'conv2d_34'")
input_layer1_shape: layer_id=390: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_52/Add:0', description="created by layer 'tf.math.add_52'")
====================================================================================
layer_type: ReLU
layer_id: 392
input_layer0: layer_id=391: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_52/Add:0', description="created by layer 'tf.math.add_52'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_34/Relu:0', description="created by layer 'tf.nn.relu_34'")
====================================================================================
layer_type: Const
layer_id: 393
tf_layers_dict_shape: (232, 1, 1, 3, 3)
====================================================================================
layer_type: GroupConvolution
layer_id: 394
input_layer0: layer_id=392: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_34/Relu:0', description="created by layer 'tf.nn.relu_34'")
input_layer1_shape: layer_id=393: (232, 1, 1, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_18/depthwise:0', description="created by layer 'depthwise_conv2d_18'")
====================================================================================
layer_type: Const
layer_id: 395
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 396
input_layer0: layer_id=394: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='depthwise_conv2d_18/depthwise:0', description="created by layer 'depthwise_conv2d_18'")
input_layer1_shape: layer_id=395: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_53/Add:0', description="created by layer 'tf.math.add_53'")
====================================================================================
layer_type: Const
layer_id: 397
tf_layers_dict_shape: (232, 232, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 398
input_layer0: layer_id=396: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_53/Add:0', description="created by layer 'tf.math.add_53'")
input_layer1_shape: layer_id=397: (232, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_35/Conv2D:0', description="created by layer 'conv2d_35'")
====================================================================================
layer_type: Const
layer_id: 399
tf_layers_dict_shape: (1, 232, 1, 1)
====================================================================================
layer_type: Add
layer_id: 400
input_layer0: layer_id=398: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='conv2d_35/Conv2D:0', description="created by layer 'conv2d_35'")
input_layer1_shape: layer_id=399: (1, 232, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_54/Add:0', description="created by layer 'tf.math.add_54'")
====================================================================================
layer_type: ReLU
layer_id: 401
input_layer0: layer_id=400: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.math.add_54/Add:0', description="created by layer 'tf.math.add_54'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_35/Relu:0', description="created by layer 'tf.nn.relu_35'")
====================================================================================
layer_type: Concat
layer_id: 402
input_layer0: layer_id=387:3: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='lambda_12/Split:0', description="created by layer 'lambda_12'")
input_layer1: layer_id=401: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232), dtype=tf.float32, name=None), name='tf.nn.relu_35/Relu:0', description="created by layer 'tf.nn.relu_35'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_15/concat:0', description="created by layer 'tf.concat_15'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 403
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 404
input_layer0: layer_id=402: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.concat_15/concat:0', description="created by layer 'tf.concat_15'")
input_layer1_shape: layer_id=403: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_30/Reshape:0', description="created by layer 'tf.reshape_30'")
====================================================================================
layer_type: Const
layer_id: 405
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 406
input_layer0: layer_id=404: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 2, 232), dtype=tf.float32, name=None), name='tf.reshape_30/Reshape:0', description="created by layer 'tf.reshape_30'")
input_layer1_shape: layer_id=405: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_15/transpose:0', description="created by layer 'tf.compat.v1.transpose_15'")
====================================================================================
layer_type: Const
layer_id: 407
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Reshape
layer_id: 408
input_layer0: layer_id=406: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 232, 2), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_15/transpose:0', description="created by layer 'tf.compat.v1.transpose_15'")
input_layer1_shape: layer_id=407: (4,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_31/Reshape:0', description="created by layer 'tf.reshape_31'")
====================================================================================
layer_type: Const
layer_id: 409
tf_layers_dict_shape: (128, 464, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 410
input_layer0: layer_id=408: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 464), dtype=tf.float32, name=None), name='tf.reshape_31/Reshape:0', description="created by layer 'tf.reshape_31'")
input_layer1_shape: layer_id=409: (128, 464, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_36/Conv2D:0', description="created by layer 'conv2d_36'")
====================================================================================
layer_type: Const
layer_id: 411
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 412
input_layer0: layer_id=410: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_36/Conv2D:0', description="created by layer 'conv2d_36'")
input_layer1_shape: layer_id=411: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_55/Add:0', description="created by layer 'tf.math.add_55'")
====================================================================================
layer_type: Swish
layer_id: 413
input_layer0: layer_id=412: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_55/Add:0', description="created by layer 'tf.math.add_55'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu/IdentityN:0', description="created by layer 'tf.nn.silu'")
====================================================================================
layer_type: ShapeOf
layer_id: 414
input_layer0_shape: layer_id=413: Const(ndarray).shape (1, 20, 20, 128)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1  20  20 128]
====================================================================================
layer_type: Convert
layer_id: 415
input_layer0_shape: layer_id=414: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1.  20.  20. 128.]
====================================================================================
layer_type: Const
layer_id: 416
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Multiply
layer_id: 417
input_layer0_shape: layer_id=415: Const(ndarray).shape (4,)
input_layer1_shape: layer_id=416: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1.  20.  40. 256.]
====================================================================================
layer_type: Const
layer_id: 418
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Add
layer_id: 419
input_layer0_shape: layer_id=417: Const(ndarray).shape (4,)
input_layer1_shape: layer_id=418: Const(ndarray).shape (1,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1.00001  20.00001  40.00001 256.     ]
====================================================================================
layer_type: Floor
layer_id: 420
input_layer0_shape: layer_id=419: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1.  20.  40. 256.]
====================================================================================
layer_type: Convert
layer_id: 421
input_layer0_shape: layer_id=420: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1  20  40 256]
====================================================================================
layer_type: Const
layer_id: 422
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 423
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 424
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: StridedSlice
layer_id: 425
input_layer0_shape: layer_id=421: Const(ndarray).shape (4,)
input_layer1_shape: layer_id=422: Const(ndarray).shape (1,)
input_layer2_shape: layer_id=423: Const(ndarray).shape (1,)
input_layer3_shape: layer_id=424: Const(ndarray).shape (1,)
tf_layers_dict_shape: (2,)
tf_layers_dict: [ 40 256]
====================================================================================
layer_type: Const
layer_id: 426
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: Const
layer_id: 427
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: Interpolate
layer_id: 428
input_layer0: layer_id=413: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu/IdentityN:0', description="created by layer 'tf.nn.silu'")
input_layer1: layer_id=425: [ 40 256]
input_layer2_shape: layer_id=426: (2,)
input_layer3_shape: layer_id=427: (2,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='lambda_13/ResizeNearestNeighbor:0', description="created by layer 'lambda_13'")
====================================================================================
layer_type: Concat
layer_id: 429
input_layer0: layer_id=428: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='lambda_13/ResizeNearestNeighbor:0', description="created by layer 'lambda_13'")
input_layer1: layer_id=306: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 232), dtype=tf.float32, name=None), name='tf.reshape_23/Reshape:0', description="created by layer 'tf.reshape_23'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 360), dtype=tf.float32, name=None), name='tf.concat_16/concat:0', description="created by layer 'tf.concat_16'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 430
tf_layers_dict_shape: (64, 360, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 431
input_layer0: layer_id=429: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 360), dtype=tf.float32, name=None), name='tf.concat_16/concat:0', description="created by layer 'tf.concat_16'")
input_layer1_shape: layer_id=430: (64, 360, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_37/Conv2D:0', description="created by layer 'conv2d_37'")
====================================================================================
layer_type: Const
layer_id: 432
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 433
input_layer0: layer_id=431: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_37/Conv2D:0', description="created by layer 'conv2d_37'")
input_layer1_shape: layer_id=432: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_56/Add:0', description="created by layer 'tf.math.add_56'")
====================================================================================
layer_type: Swish
layer_id: 434
input_layer0: layer_id=433: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_56/Add:0', description="created by layer 'tf.math.add_56'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_1/IdentityN:0', description="created by layer 'tf.nn.silu_1'")
====================================================================================
layer_type: Const
layer_id: 435
tf_layers_dict_shape: (64, 64, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 436
input_layer0: layer_id=434: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_1/IdentityN:0', description="created by layer 'tf.nn.silu_1'")
input_layer1_shape: layer_id=435: (64, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_38/Conv2D:0', description="created by layer 'conv2d_38'")
====================================================================================
layer_type: Const
layer_id: 437
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 438
input_layer0: layer_id=436: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_38/Conv2D:0', description="created by layer 'conv2d_38'")
input_layer1_shape: layer_id=437: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_57/Add:0', description="created by layer 'tf.math.add_57'")
====================================================================================
layer_type: Swish
layer_id: 439
input_layer0: layer_id=438: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_57/Add:0', description="created by layer 'tf.math.add_57'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_2/IdentityN:0', description="created by layer 'tf.nn.silu_2'")
====================================================================================
layer_type: Const
layer_id: 440
tf_layers_dict_shape: (64, 64, 3, 3)
====================================================================================
layer_type: Convolution
layer_id: 441
input_layer0: layer_id=439: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_2/IdentityN:0', description="created by layer 'tf.nn.silu_2'")
input_layer1_shape: layer_id=440: (64, 64, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_39/Conv2D:0', description="created by layer 'conv2d_39'")
====================================================================================
layer_type: Const
layer_id: 442
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 443
input_layer0: layer_id=441: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_39/Conv2D:0', description="created by layer 'conv2d_39'")
input_layer1_shape: layer_id=442: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_58/Add:0', description="created by layer 'tf.math.add_58'")
====================================================================================
layer_type: Swish
layer_id: 444
input_layer0: layer_id=443: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_58/Add:0', description="created by layer 'tf.math.add_58'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_3/IdentityN:0', description="created by layer 'tf.nn.silu_3'")
====================================================================================
layer_type: Const
layer_id: 445
tf_layers_dict_shape: (64, 360, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 446
input_layer0: layer_id=429: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 360), dtype=tf.float32, name=None), name='tf.concat_16/concat:0', description="created by layer 'tf.concat_16'")
input_layer1_shape: layer_id=445: (64, 360, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_40/Conv2D:0', description="created by layer 'conv2d_40'")
====================================================================================
layer_type: Const
layer_id: 447
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 448
input_layer0: layer_id=446: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_40/Conv2D:0', description="created by layer 'conv2d_40'")
input_layer1_shape: layer_id=447: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_59/Add:0', description="created by layer 'tf.math.add_59'")
====================================================================================
layer_type: Swish
layer_id: 449
input_layer0: layer_id=448: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_59/Add:0', description="created by layer 'tf.math.add_59'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_4/IdentityN:0', description="created by layer 'tf.nn.silu_4'")
====================================================================================
layer_type: Concat
layer_id: 450
input_layer0: layer_id=444: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_3/IdentityN:0', description="created by layer 'tf.nn.silu_3'")
input_layer1: layer_id=449: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_4/IdentityN:0', description="created by layer 'tf.nn.silu_4'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.concat_17/concat:0', description="created by layer 'tf.concat_17'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 451
tf_layers_dict_shape: (128, 128, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 452
input_layer0: layer_id=450: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.concat_17/concat:0', description="created by layer 'tf.concat_17'")
input_layer1_shape: layer_id=451: (128, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='conv2d_41/Conv2D:0', description="created by layer 'conv2d_41'")
====================================================================================
layer_type: Const
layer_id: 453
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 454
input_layer0: layer_id=452: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='conv2d_41/Conv2D:0', description="created by layer 'conv2d_41'")
input_layer1_shape: layer_id=453: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.math.add_60/Add:0', description="created by layer 'tf.math.add_60'")
====================================================================================
layer_type: Swish
layer_id: 455
input_layer0: layer_id=454: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.math.add_60/Add:0', description="created by layer 'tf.math.add_60'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.nn.silu_5/IdentityN:0', description="created by layer 'tf.nn.silu_5'")
====================================================================================
layer_type: Const
layer_id: 456
tf_layers_dict_shape: (64, 128, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 457
input_layer0: layer_id=455: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.nn.silu_5/IdentityN:0', description="created by layer 'tf.nn.silu_5'")
input_layer1_shape: layer_id=456: (64, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_42/Conv2D:0', description="created by layer 'conv2d_42'")
====================================================================================
layer_type: Const
layer_id: 458
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 459
input_layer0: layer_id=457: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_42/Conv2D:0', description="created by layer 'conv2d_42'")
input_layer1_shape: layer_id=458: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_61/Add:0', description="created by layer 'tf.math.add_61'")
====================================================================================
layer_type: Swish
layer_id: 460
input_layer0: layer_id=459: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_61/Add:0', description="created by layer 'tf.math.add_61'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_6/IdentityN:0', description="created by layer 'tf.nn.silu_6'")
====================================================================================
layer_type: ShapeOf
layer_id: 461
input_layer0_shape: layer_id=460: Const(ndarray).shape (1, 40, 40, 64)
tf_layers_dict_shape: (4,)
tf_layers_dict: [ 1 40 40 64]
====================================================================================
layer_type: Convert
layer_id: 462
input_layer0_shape: layer_id=461: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [ 1. 40. 40. 64.]
====================================================================================
layer_type: Const
layer_id: 463
tf_layers_dict_shape: (4,)
====================================================================================
layer_type: Multiply
layer_id: 464
input_layer0_shape: layer_id=462: Const(ndarray).shape (4,)
input_layer1_shape: layer_id=463: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1.  40.  80. 128.]
====================================================================================
layer_type: Const
layer_id: 465
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Add
layer_id: 466
input_layer0_shape: layer_id=464: Const(ndarray).shape (4,)
input_layer1_shape: layer_id=465: Const(ndarray).shape (1,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1.00001  40.00001  80.00001 128.00002]
====================================================================================
layer_type: Floor
layer_id: 467
input_layer0_shape: layer_id=466: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1.  40.  80. 128.]
====================================================================================
layer_type: Convert
layer_id: 468
input_layer0_shape: layer_id=467: Const(ndarray).shape (4,)
tf_layers_dict_shape: (4,)
tf_layers_dict: [  1  40  80 128]
====================================================================================
layer_type: Const
layer_id: 469
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 470
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 471
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: StridedSlice
layer_id: 472
input_layer0_shape: layer_id=468: Const(ndarray).shape (4,)
input_layer1_shape: layer_id=469: Const(ndarray).shape (1,)
input_layer2_shape: layer_id=470: Const(ndarray).shape (1,)
input_layer3_shape: layer_id=471: Const(ndarray).shape (1,)
tf_layers_dict_shape: (2,)
tf_layers_dict: [ 80 128]
====================================================================================
layer_type: Const
layer_id: 473
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: Const
layer_id: 474
tf_layers_dict_shape: (2,)
====================================================================================
layer_type: Interpolate
layer_id: 475
input_layer0: layer_id=460: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_6/IdentityN:0', description="created by layer 'tf.nn.silu_6'")
input_layer1: layer_id=472: [ 80 128]
input_layer2_shape: layer_id=473: (2,)
input_layer3_shape: layer_id=474: (2,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='lambda_14/ResizeNearestNeighbor:0', description="created by layer 'lambda_14'")
====================================================================================
layer_type: Concat
layer_id: 476
input_layer0: layer_id=475: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='lambda_14/ResizeNearestNeighbor:0', description="created by layer 'lambda_14'")
input_layer1: layer_id=108: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 120), dtype=tf.float32, name=None), name='tf.reshape_7/Reshape:0', description="created by layer 'tf.reshape_7'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 184), dtype=tf.float32, name=None), name='tf.concat_18/concat:0', description="created by layer 'tf.concat_18'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 477
tf_layers_dict_shape: (32, 184, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 478
input_layer0: layer_id=476: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 184), dtype=tf.float32, name=None), name='tf.concat_18/concat:0', description="created by layer 'tf.concat_18'")
input_layer1_shape: layer_id=477: (32, 184, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_43/Conv2D:0', description="created by layer 'conv2d_43'")
====================================================================================
layer_type: Const
layer_id: 479
tf_layers_dict_shape: (1, 32, 1, 1)
====================================================================================
layer_type: Add
layer_id: 480
input_layer0: layer_id=478: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_43/Conv2D:0', description="created by layer 'conv2d_43'")
input_layer1_shape: layer_id=479: (1, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_62/Add:0', description="created by layer 'tf.math.add_62'")
====================================================================================
layer_type: Swish
layer_id: 481
input_layer0: layer_id=480: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_62/Add:0', description="created by layer 'tf.math.add_62'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_7/IdentityN:0', description="created by layer 'tf.nn.silu_7'")
====================================================================================
layer_type: Const
layer_id: 482
tf_layers_dict_shape: (32, 32, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 483
input_layer0: layer_id=481: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_7/IdentityN:0', description="created by layer 'tf.nn.silu_7'")
input_layer1_shape: layer_id=482: (32, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_44/Conv2D:0', description="created by layer 'conv2d_44'")
====================================================================================
layer_type: Const
layer_id: 484
tf_layers_dict_shape: (1, 32, 1, 1)
====================================================================================
layer_type: Add
layer_id: 485
input_layer0: layer_id=483: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_44/Conv2D:0', description="created by layer 'conv2d_44'")
input_layer1_shape: layer_id=484: (1, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_63/Add:0', description="created by layer 'tf.math.add_63'")
====================================================================================
layer_type: Swish
layer_id: 486
input_layer0: layer_id=485: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_63/Add:0', description="created by layer 'tf.math.add_63'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_8/IdentityN:0', description="created by layer 'tf.nn.silu_8'")
====================================================================================
layer_type: Const
layer_id: 487
tf_layers_dict_shape: (32, 32, 3, 3)
====================================================================================
layer_type: Convolution
layer_id: 488
input_layer0: layer_id=486: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_8/IdentityN:0', description="created by layer 'tf.nn.silu_8'")
input_layer1_shape: layer_id=487: (32, 32, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_45/Conv2D:0', description="created by layer 'conv2d_45'")
====================================================================================
layer_type: Const
layer_id: 489
tf_layers_dict_shape: (1, 32, 1, 1)
====================================================================================
layer_type: Add
layer_id: 490
input_layer0: layer_id=488: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_45/Conv2D:0', description="created by layer 'conv2d_45'")
input_layer1_shape: layer_id=489: (1, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_64/Add:0', description="created by layer 'tf.math.add_64'")
====================================================================================
layer_type: Swish
layer_id: 491
input_layer0: layer_id=490: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_64/Add:0', description="created by layer 'tf.math.add_64'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_9/IdentityN:0', description="created by layer 'tf.nn.silu_9'")
====================================================================================
layer_type: Const
layer_id: 492
tf_layers_dict_shape: (32, 184, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 493
input_layer0: layer_id=476: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 184), dtype=tf.float32, name=None), name='tf.concat_18/concat:0', description="created by layer 'tf.concat_18'")
input_layer1_shape: layer_id=492: (32, 184, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_46/Conv2D:0', description="created by layer 'conv2d_46'")
====================================================================================
layer_type: Const
layer_id: 494
tf_layers_dict_shape: (1, 32, 1, 1)
====================================================================================
layer_type: Add
layer_id: 495
input_layer0: layer_id=493: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='conv2d_46/Conv2D:0', description="created by layer 'conv2d_46'")
input_layer1_shape: layer_id=494: (1, 32, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_65/Add:0', description="created by layer 'tf.math.add_65'")
====================================================================================
layer_type: Swish
layer_id: 496
input_layer0: layer_id=495: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.math.add_65/Add:0', description="created by layer 'tf.math.add_65'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_10/IdentityN:0', description="created by layer 'tf.nn.silu_10'")
====================================================================================
layer_type: Concat
layer_id: 497
input_layer0: layer_id=491: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_9/IdentityN:0', description="created by layer 'tf.nn.silu_9'")
input_layer1: layer_id=496: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 32), dtype=tf.float32, name=None), name='tf.nn.silu_10/IdentityN:0', description="created by layer 'tf.nn.silu_10'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='tf.concat_19/concat:0', description="created by layer 'tf.concat_19'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 498
tf_layers_dict_shape: (64, 64, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 499
input_layer0: layer_id=497: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='tf.concat_19/concat:0', description="created by layer 'tf.concat_19'")
input_layer1_shape: layer_id=498: (64, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='conv2d_47/Conv2D:0', description="created by layer 'conv2d_47'")
====================================================================================
layer_type: Const
layer_id: 500
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 501
input_layer0: layer_id=499: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='conv2d_47/Conv2D:0', description="created by layer 'conv2d_47'")
input_layer1_shape: layer_id=500: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='tf.math.add_66/Add:0', description="created by layer 'tf.math.add_66'")
====================================================================================
layer_type: Swish
layer_id: 502
input_layer0: layer_id=501: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='tf.math.add_66/Add:0', description="created by layer 'tf.math.add_66'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='tf.nn.silu_11/IdentityN:0', description="created by layer 'tf.nn.silu_11'")
====================================================================================
layer_type: Const
layer_id: 503
tf_layers_dict_shape: (255, 64, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 504
input_layer0: layer_id=502: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='tf.nn.silu_11/IdentityN:0', description="created by layer 'tf.nn.silu_11'")
input_layer1_shape: layer_id=503: (255, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 255), dtype=tf.float32, name=None), name='conv2d_48/Conv2D:0', description="created by layer 'conv2d_48'")
====================================================================================
layer_type: Const
layer_id: 505
tf_layers_dict_shape: (1, 255, 1, 1)
====================================================================================
layer_type: Add
layer_id: 506
input_layer0: layer_id=504: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 255), dtype=tf.float32, name=None), name='conv2d_48/Conv2D:0', description="created by layer 'conv2d_48'")
input_layer1_shape: layer_id=505: (1, 255, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 255), dtype=tf.float32, name=None), name='tf.math.add_67/Add:0', description="created by layer 'tf.math.add_67'")
====================================================================================
layer_type: Const
layer_id: 507
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 508
input_layer0: layer_id=506: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 255), dtype=tf.float32, name=None), name='tf.math.add_67/Add:0', description="created by layer 'tf.math.add_67'")
input_layer1_shape: layer_id=507: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 3, 85), dtype=tf.float32, name=None), name='tf.reshape_32/Reshape:0', description="created by layer 'tf.reshape_32'")
====================================================================================
layer_type: Const
layer_id: 509
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 510
input_layer0: layer_id=508: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 3, 85), dtype=tf.float32, name=None), name='tf.reshape_32/Reshape:0', description="created by layer 'tf.reshape_32'")
input_layer1_shape: layer_id=509: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 85), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_16/transpose:0', description="created by layer 'tf.compat.v1.transpose_16'")
====================================================================================
layer_type: Sigmoid
layer_id: 511
input_layer0: layer_id=510: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 85), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_16/transpose:0', description="created by layer 'tf.compat.v1.transpose_16'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 85), dtype=tf.float32, name=None), name='tf.math.sigmoid/Sigmoid:0', description="created by layer 'tf.math.sigmoid'")
====================================================================================
layer_type: Const
layer_id: 512
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 513
tf_layers_dict_shape: (3,)
====================================================================================
layer_type: VariadicSplit
layer_id: 514
input_layer0: layer_id=511: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 85), dtype=tf.float32, name=None), name='tf.math.sigmoid/Sigmoid:0', description="created by layer 'tf.math.sigmoid'")
input_layer1: layer_id=512: Const(ndarray).shape (1,)
input_layer2: layer_id=513: Const(ndarray).shape (3,)
tf_layers_dict0: layer_id_port: 514:3 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.slice/Slice:0', description="created by layer 'tf.slice'")
tf_layers_dict1: layer_id_port: 514:4 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.slice_1/Slice:0', description="created by layer 'tf.slice_1'")
tf_layers_dict2: layer_id_port: 514:5 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 81), dtype=tf.float32, name=None), name='tf.slice_2/Slice:0', description="created by layer 'tf.slice_2'")
====================================================================================
layer_type: Const
layer_id: 515
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 516
input_layer0: layer_id=514:3: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.slice/Slice:0', description="created by layer 'tf.slice'")
input_layer1_shape: layer_id=515: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply/Mul:0', description="created by layer 'tf.math.multiply'")
====================================================================================
layer_type: Const
layer_id: 517
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Add
layer_id: 518
input_layer0: layer_id=516: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply/Mul:0', description="created by layer 'tf.math.multiply'")
input_layer1_shape: layer_id=517: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.add_68/Add:0', description="created by layer 'tf.math.add_68'")
====================================================================================
layer_type: Const
layer_id: 519
tf_layers_dict_shape: (1, 3, 80, 80, 2)
====================================================================================
layer_type: Add
layer_id: 520
input_layer0: layer_id=518: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.add_68/Add:0', description="created by layer 'tf.math.add_68'")
input_layer1_shape: layer_id=519: (1, 3, 80, 80, 2)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.add_69/Add:0', description="created by layer 'tf.math.add_69'")
====================================================================================
layer_type: Const
layer_id: 521
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 522
input_layer0: layer_id=520: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.add_69/Add:0', description="created by layer 'tf.math.add_69'")
input_layer1_shape: layer_id=521: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply_1/Mul:0', description="created by layer 'tf.math.multiply_1'")
====================================================================================
layer_type: Const
layer_id: 523
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 524
input_layer0: layer_id=514:4: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.slice_1/Slice:0', description="created by layer 'tf.slice_1'")
input_layer1_shape: layer_id=523: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply_2/Mul:0', description="created by layer 'tf.math.multiply_2'")
====================================================================================
layer_type: Const
layer_id: 525
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Power
layer_id: 526
input_layer0: layer_id=524: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply_2/Mul:0', description="created by layer 'tf.math.multiply_2'")
input_layer1_shape: layer_id=525: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.pow/Pow:0', description="created by layer 'tf.math.pow'")
====================================================================================
layer_type: Const
layer_id: 527
tf_layers_dict_shape: (1, 3, 80, 80, 2)
====================================================================================
layer_type: Multiply
layer_id: 528
input_layer0: layer_id=526: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.pow/Pow:0', description="created by layer 'tf.math.pow'")
input_layer1_shape: layer_id=527: (1, 3, 80, 80, 2)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply_3/Mul:0', description="created by layer 'tf.math.multiply_3'")
====================================================================================
layer_type: Concat
layer_id: 529
input_layer0: layer_id=522: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply_1/Mul:0', description="created by layer 'tf.math.multiply_1'")
input_layer1: layer_id=528: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 2), dtype=tf.float32, name=None), name='tf.math.multiply_3/Mul:0', description="created by layer 'tf.math.multiply_3'")
input_layer2: layer_id=514:5: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 81), dtype=tf.float32, name=None), name='tf.slice_2/Slice:0', description="created by layer 'tf.slice_2'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 85), dtype=tf.float32, name=None), name='tf.concat_20/concat:0', description="created by layer 'tf.concat_20'")
axis: 4
====================================================================================
layer_type: Const
layer_id: 530
tf_layers_dict_shape: (3,)
====================================================================================
layer_type: Reshape
layer_id: 531
input_layer0: layer_id=529: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 80, 80, 85), dtype=tf.float32, name=None), name='tf.concat_20/concat:0', description="created by layer 'tf.concat_20'")
input_layer1_shape: layer_id=530: (3,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 19200, 85), dtype=tf.float32, name=None), name='tf.reshape_33/Reshape:0', description="created by layer 'tf.reshape_33'")
====================================================================================
layer_type: Const
layer_id: 532
tf_layers_dict_shape: (64, 64, 3, 3)
====================================================================================
layer_type: Convolution
layer_id: 533
input_layer0: layer_id=502: KerasTensor(type_spec=TensorSpec(shape=(1, 80, 80, 64), dtype=tf.float32, name=None), name='tf.nn.silu_11/IdentityN:0', description="created by layer 'tf.nn.silu_11'")
input_layer1_shape: layer_id=532: (64, 64, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_49/Conv2D:0', description="created by layer 'conv2d_49'")
====================================================================================
layer_type: Const
layer_id: 534
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 535
input_layer0: layer_id=533: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_49/Conv2D:0', description="created by layer 'conv2d_49'")
input_layer1_shape: layer_id=534: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_70/Add:0', description="created by layer 'tf.math.add_70'")
====================================================================================
layer_type: Swish
layer_id: 536
input_layer0: layer_id=535: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_70/Add:0', description="created by layer 'tf.math.add_70'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_12/IdentityN:0', description="created by layer 'tf.nn.silu_12'")
====================================================================================
layer_type: Concat
layer_id: 537
input_layer0: layer_id=536: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_12/IdentityN:0', description="created by layer 'tf.nn.silu_12'")
input_layer1: layer_id=460: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_6/IdentityN:0', description="created by layer 'tf.nn.silu_6'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.concat_21/concat:0', description="created by layer 'tf.concat_21'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 538
tf_layers_dict_shape: (64, 128, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 539
input_layer0: layer_id=537: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.concat_21/concat:0', description="created by layer 'tf.concat_21'")
input_layer1_shape: layer_id=538: (64, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_50/Conv2D:0', description="created by layer 'conv2d_50'")
====================================================================================
layer_type: Const
layer_id: 540
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 541
input_layer0: layer_id=539: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_50/Conv2D:0', description="created by layer 'conv2d_50'")
input_layer1_shape: layer_id=540: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_71/Add:0', description="created by layer 'tf.math.add_71'")
====================================================================================
layer_type: Swish
layer_id: 542
input_layer0: layer_id=541: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_71/Add:0', description="created by layer 'tf.math.add_71'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_13/IdentityN:0', description="created by layer 'tf.nn.silu_13'")
====================================================================================
layer_type: Const
layer_id: 543
tf_layers_dict_shape: (64, 64, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 544
input_layer0: layer_id=542: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_13/IdentityN:0', description="created by layer 'tf.nn.silu_13'")
input_layer1_shape: layer_id=543: (64, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_51/Conv2D:0', description="created by layer 'conv2d_51'")
====================================================================================
layer_type: Const
layer_id: 545
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 546
input_layer0: layer_id=544: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_51/Conv2D:0', description="created by layer 'conv2d_51'")
input_layer1_shape: layer_id=545: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_72/Add:0', description="created by layer 'tf.math.add_72'")
====================================================================================
layer_type: Swish
layer_id: 547
input_layer0: layer_id=546: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_72/Add:0', description="created by layer 'tf.math.add_72'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_14/IdentityN:0', description="created by layer 'tf.nn.silu_14'")
====================================================================================
layer_type: Const
layer_id: 548
tf_layers_dict_shape: (64, 64, 3, 3)
====================================================================================
layer_type: Convolution
layer_id: 549
input_layer0: layer_id=547: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_14/IdentityN:0', description="created by layer 'tf.nn.silu_14'")
input_layer1_shape: layer_id=548: (64, 64, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_52/Conv2D:0', description="created by layer 'conv2d_52'")
====================================================================================
layer_type: Const
layer_id: 550
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 551
input_layer0: layer_id=549: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_52/Conv2D:0', description="created by layer 'conv2d_52'")
input_layer1_shape: layer_id=550: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_73/Add:0', description="created by layer 'tf.math.add_73'")
====================================================================================
layer_type: Swish
layer_id: 552
input_layer0: layer_id=551: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_73/Add:0', description="created by layer 'tf.math.add_73'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_15/IdentityN:0', description="created by layer 'tf.nn.silu_15'")
====================================================================================
layer_type: Const
layer_id: 553
tf_layers_dict_shape: (64, 128, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 554
input_layer0: layer_id=537: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.concat_21/concat:0', description="created by layer 'tf.concat_21'")
input_layer1_shape: layer_id=553: (64, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_53/Conv2D:0', description="created by layer 'conv2d_53'")
====================================================================================
layer_type: Const
layer_id: 555
tf_layers_dict_shape: (1, 64, 1, 1)
====================================================================================
layer_type: Add
layer_id: 556
input_layer0: layer_id=554: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='conv2d_53/Conv2D:0', description="created by layer 'conv2d_53'")
input_layer1_shape: layer_id=555: (1, 64, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_74/Add:0', description="created by layer 'tf.math.add_74'")
====================================================================================
layer_type: Swish
layer_id: 557
input_layer0: layer_id=556: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.math.add_74/Add:0', description="created by layer 'tf.math.add_74'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_16/IdentityN:0', description="created by layer 'tf.nn.silu_16'")
====================================================================================
layer_type: Concat
layer_id: 558
input_layer0: layer_id=552: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_15/IdentityN:0', description="created by layer 'tf.nn.silu_15'")
input_layer1: layer_id=557: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 64), dtype=tf.float32, name=None), name='tf.nn.silu_16/IdentityN:0', description="created by layer 'tf.nn.silu_16'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.concat_22/concat:0', description="created by layer 'tf.concat_22'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 559
tf_layers_dict_shape: (128, 128, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 560
input_layer0: layer_id=558: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.concat_22/concat:0', description="created by layer 'tf.concat_22'")
input_layer1_shape: layer_id=559: (128, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='conv2d_54/Conv2D:0', description="created by layer 'conv2d_54'")
====================================================================================
layer_type: Const
layer_id: 561
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 562
input_layer0: layer_id=560: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='conv2d_54/Conv2D:0', description="created by layer 'conv2d_54'")
input_layer1_shape: layer_id=561: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.math.add_75/Add:0', description="created by layer 'tf.math.add_75'")
====================================================================================
layer_type: Swish
layer_id: 563
input_layer0: layer_id=562: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.math.add_75/Add:0', description="created by layer 'tf.math.add_75'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.nn.silu_17/IdentityN:0', description="created by layer 'tf.nn.silu_17'")
====================================================================================
layer_type: Const
layer_id: 564
tf_layers_dict_shape: (255, 128, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 565
input_layer0: layer_id=563: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.nn.silu_17/IdentityN:0', description="created by layer 'tf.nn.silu_17'")
input_layer1_shape: layer_id=564: (255, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 255), dtype=tf.float32, name=None), name='conv2d_55/Conv2D:0', description="created by layer 'conv2d_55'")
====================================================================================
layer_type: Const
layer_id: 566
tf_layers_dict_shape: (1, 255, 1, 1)
====================================================================================
layer_type: Add
layer_id: 567
input_layer0: layer_id=565: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 255), dtype=tf.float32, name=None), name='conv2d_55/Conv2D:0', description="created by layer 'conv2d_55'")
input_layer1_shape: layer_id=566: (1, 255, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 255), dtype=tf.float32, name=None), name='tf.math.add_76/Add:0', description="created by layer 'tf.math.add_76'")
====================================================================================
layer_type: Const
layer_id: 568
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 569
input_layer0: layer_id=567: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 255), dtype=tf.float32, name=None), name='tf.math.add_76/Add:0', description="created by layer 'tf.math.add_76'")
input_layer1_shape: layer_id=568: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 3, 85), dtype=tf.float32, name=None), name='tf.reshape_34/Reshape:0', description="created by layer 'tf.reshape_34'")
====================================================================================
layer_type: Const
layer_id: 570
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 571
input_layer0: layer_id=569: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 3, 85), dtype=tf.float32, name=None), name='tf.reshape_34/Reshape:0', description="created by layer 'tf.reshape_34'")
input_layer1_shape: layer_id=570: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 85), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_17/transpose:0', description="created by layer 'tf.compat.v1.transpose_17'")
====================================================================================
layer_type: Sigmoid
layer_id: 572
input_layer0: layer_id=571: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 85), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_17/transpose:0', description="created by layer 'tf.compat.v1.transpose_17'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 85), dtype=tf.float32, name=None), name='tf.math.sigmoid_1/Sigmoid:0', description="created by layer 'tf.math.sigmoid_1'")
====================================================================================
layer_type: Const
layer_id: 573
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 574
tf_layers_dict_shape: (3,)
====================================================================================
layer_type: VariadicSplit
layer_id: 575
input_layer0: layer_id=572: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 85), dtype=tf.float32, name=None), name='tf.math.sigmoid_1/Sigmoid:0', description="created by layer 'tf.math.sigmoid_1'")
input_layer1: layer_id=573: Const(ndarray).shape (1,)
input_layer2: layer_id=574: Const(ndarray).shape (3,)
tf_layers_dict0: layer_id_port: 575:3 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.slice_3/Slice:0', description="created by layer 'tf.slice_3'")
tf_layers_dict1: layer_id_port: 575:4 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.slice_4/Slice:0', description="created by layer 'tf.slice_4'")
tf_layers_dict2: layer_id_port: 575:5 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 81), dtype=tf.float32, name=None), name='tf.slice_5/Slice:0', description="created by layer 'tf.slice_5'")
====================================================================================
layer_type: Const
layer_id: 576
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 577
input_layer0: layer_id=575:3: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.slice_3/Slice:0', description="created by layer 'tf.slice_3'")
input_layer1_shape: layer_id=576: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_4/Mul:0', description="created by layer 'tf.math.multiply_4'")
====================================================================================
layer_type: Const
layer_id: 578
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Add
layer_id: 579
input_layer0: layer_id=577: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_4/Mul:0', description="created by layer 'tf.math.multiply_4'")
input_layer1_shape: layer_id=578: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.add_77/Add:0', description="created by layer 'tf.math.add_77'")
====================================================================================
layer_type: Const
layer_id: 580
tf_layers_dict_shape: (1, 3, 40, 40, 2)
====================================================================================
layer_type: Add
layer_id: 581
input_layer0: layer_id=579: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.add_77/Add:0', description="created by layer 'tf.math.add_77'")
input_layer1_shape: layer_id=580: (1, 3, 40, 40, 2)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.add_78/Add:0', description="created by layer 'tf.math.add_78'")
====================================================================================
layer_type: Const
layer_id: 582
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 583
input_layer0: layer_id=581: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.add_78/Add:0', description="created by layer 'tf.math.add_78'")
input_layer1_shape: layer_id=582: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_5/Mul:0', description="created by layer 'tf.math.multiply_5'")
====================================================================================
layer_type: Const
layer_id: 584
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 585
input_layer0: layer_id=575:4: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.slice_4/Slice:0', description="created by layer 'tf.slice_4'")
input_layer1_shape: layer_id=584: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_6/Mul:0', description="created by layer 'tf.math.multiply_6'")
====================================================================================
layer_type: Const
layer_id: 586
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Power
layer_id: 587
input_layer0: layer_id=585: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_6/Mul:0', description="created by layer 'tf.math.multiply_6'")
input_layer1_shape: layer_id=586: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.pow_1/Pow:0', description="created by layer 'tf.math.pow_1'")
====================================================================================
layer_type: Const
layer_id: 588
tf_layers_dict_shape: (1, 3, 40, 40, 2)
====================================================================================
layer_type: Multiply
layer_id: 589
input_layer0: layer_id=587: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.pow_1/Pow:0', description="created by layer 'tf.math.pow_1'")
input_layer1_shape: layer_id=588: (1, 3, 40, 40, 2)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_7/Mul:0', description="created by layer 'tf.math.multiply_7'")
====================================================================================
layer_type: Concat
layer_id: 590
input_layer0: layer_id=583: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_5/Mul:0', description="created by layer 'tf.math.multiply_5'")
input_layer1: layer_id=589: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 2), dtype=tf.float32, name=None), name='tf.math.multiply_7/Mul:0', description="created by layer 'tf.math.multiply_7'")
input_layer2: layer_id=575:5: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 81), dtype=tf.float32, name=None), name='tf.slice_5/Slice:0', description="created by layer 'tf.slice_5'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 85), dtype=tf.float32, name=None), name='tf.concat_23/concat:0', description="created by layer 'tf.concat_23'")
axis: 4
====================================================================================
layer_type: Const
layer_id: 591
tf_layers_dict_shape: (3,)
====================================================================================
layer_type: Reshape
layer_id: 592
input_layer0: layer_id=590: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 40, 40, 85), dtype=tf.float32, name=None), name='tf.concat_23/concat:0', description="created by layer 'tf.concat_23'")
input_layer1_shape: layer_id=591: (3,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 4800, 85), dtype=tf.float32, name=None), name='tf.reshape_35/Reshape:0', description="created by layer 'tf.reshape_35'")
====================================================================================
layer_type: Const
layer_id: 593
tf_layers_dict_shape: (128, 128, 3, 3)
====================================================================================
layer_type: Convolution
layer_id: 594
input_layer0: layer_id=563: KerasTensor(type_spec=TensorSpec(shape=(1, 40, 40, 128), dtype=tf.float32, name=None), name='tf.nn.silu_17/IdentityN:0', description="created by layer 'tf.nn.silu_17'")
input_layer1_shape: layer_id=593: (128, 128, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_56/Conv2D:0', description="created by layer 'conv2d_56'")
====================================================================================
layer_type: Const
layer_id: 595
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 596
input_layer0: layer_id=594: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_56/Conv2D:0', description="created by layer 'conv2d_56'")
input_layer1_shape: layer_id=595: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_79/Add:0', description="created by layer 'tf.math.add_79'")
====================================================================================
layer_type: Swish
layer_id: 597
input_layer0: layer_id=596: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_79/Add:0', description="created by layer 'tf.math.add_79'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_18/IdentityN:0', description="created by layer 'tf.nn.silu_18'")
====================================================================================
layer_type: Concat
layer_id: 598
input_layer0: layer_id=597: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_18/IdentityN:0', description="created by layer 'tf.nn.silu_18'")
input_layer1: layer_id=413: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu/IdentityN:0', description="created by layer 'tf.nn.silu'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.concat_24/concat:0', description="created by layer 'tf.concat_24'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 599
tf_layers_dict_shape: (128, 256, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 600
input_layer0: layer_id=598: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.concat_24/concat:0', description="created by layer 'tf.concat_24'")
input_layer1_shape: layer_id=599: (128, 256, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_57/Conv2D:0', description="created by layer 'conv2d_57'")
====================================================================================
layer_type: Const
layer_id: 601
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 602
input_layer0: layer_id=600: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_57/Conv2D:0', description="created by layer 'conv2d_57'")
input_layer1_shape: layer_id=601: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_80/Add:0', description="created by layer 'tf.math.add_80'")
====================================================================================
layer_type: Swish
layer_id: 603
input_layer0: layer_id=602: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_80/Add:0', description="created by layer 'tf.math.add_80'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_19/IdentityN:0', description="created by layer 'tf.nn.silu_19'")
====================================================================================
layer_type: Const
layer_id: 604
tf_layers_dict_shape: (128, 128, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 605
input_layer0: layer_id=603: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_19/IdentityN:0', description="created by layer 'tf.nn.silu_19'")
input_layer1_shape: layer_id=604: (128, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_58/Conv2D:0', description="created by layer 'conv2d_58'")
====================================================================================
layer_type: Const
layer_id: 606
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 607
input_layer0: layer_id=605: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_58/Conv2D:0', description="created by layer 'conv2d_58'")
input_layer1_shape: layer_id=606: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_81/Add:0', description="created by layer 'tf.math.add_81'")
====================================================================================
layer_type: Swish
layer_id: 608
input_layer0: layer_id=607: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_81/Add:0', description="created by layer 'tf.math.add_81'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_20/IdentityN:0', description="created by layer 'tf.nn.silu_20'")
====================================================================================
layer_type: Const
layer_id: 609
tf_layers_dict_shape: (128, 128, 3, 3)
====================================================================================
layer_type: Convolution
layer_id: 610
input_layer0: layer_id=608: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_20/IdentityN:0', description="created by layer 'tf.nn.silu_20'")
input_layer1_shape: layer_id=609: (128, 128, 3, 3)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_59/Conv2D:0', description="created by layer 'conv2d_59'")
====================================================================================
layer_type: Const
layer_id: 611
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 612
input_layer0: layer_id=610: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_59/Conv2D:0', description="created by layer 'conv2d_59'")
input_layer1_shape: layer_id=611: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_82/Add:0', description="created by layer 'tf.math.add_82'")
====================================================================================
layer_type: Swish
layer_id: 613
input_layer0: layer_id=612: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_82/Add:0', description="created by layer 'tf.math.add_82'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_21/IdentityN:0', description="created by layer 'tf.nn.silu_21'")
====================================================================================
layer_type: Const
layer_id: 614
tf_layers_dict_shape: (128, 256, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 615
input_layer0: layer_id=598: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.concat_24/concat:0', description="created by layer 'tf.concat_24'")
input_layer1_shape: layer_id=614: (128, 256, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_60/Conv2D:0', description="created by layer 'conv2d_60'")
====================================================================================
layer_type: Const
layer_id: 616
tf_layers_dict_shape: (1, 128, 1, 1)
====================================================================================
layer_type: Add
layer_id: 617
input_layer0: layer_id=615: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='conv2d_60/Conv2D:0', description="created by layer 'conv2d_60'")
input_layer1_shape: layer_id=616: (1, 128, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_83/Add:0', description="created by layer 'tf.math.add_83'")
====================================================================================
layer_type: Swish
layer_id: 618
input_layer0: layer_id=617: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.math.add_83/Add:0', description="created by layer 'tf.math.add_83'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_22/IdentityN:0', description="created by layer 'tf.nn.silu_22'")
====================================================================================
layer_type: Concat
layer_id: 619
input_layer0: layer_id=613: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_21/IdentityN:0', description="created by layer 'tf.nn.silu_21'")
input_layer1: layer_id=618: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 128), dtype=tf.float32, name=None), name='tf.nn.silu_22/IdentityN:0', description="created by layer 'tf.nn.silu_22'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.concat_25/concat:0', description="created by layer 'tf.concat_25'")
axis: -1
====================================================================================
layer_type: Const
layer_id: 620
tf_layers_dict_shape: (256, 256, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 621
input_layer0: layer_id=619: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.concat_25/concat:0', description="created by layer 'tf.concat_25'")
input_layer1_shape: layer_id=620: (256, 256, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='conv2d_61/Conv2D:0', description="created by layer 'conv2d_61'")
====================================================================================
layer_type: Const
layer_id: 622
tf_layers_dict_shape: (1, 256, 1, 1)
====================================================================================
layer_type: Add
layer_id: 623
input_layer0: layer_id=621: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='conv2d_61/Conv2D:0', description="created by layer 'conv2d_61'")
input_layer1_shape: layer_id=622: (1, 256, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.math.add_84/Add:0', description="created by layer 'tf.math.add_84'")
====================================================================================
layer_type: Swish
layer_id: 624
input_layer0: layer_id=623: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.math.add_84/Add:0', description="created by layer 'tf.math.add_84'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.nn.silu_23/IdentityN:0', description="created by layer 'tf.nn.silu_23'")
====================================================================================
layer_type: Const
layer_id: 625
tf_layers_dict_shape: (255, 256, 1, 1)
====================================================================================
layer_type: Convolution
layer_id: 626
input_layer0: layer_id=624: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 256), dtype=tf.float32, name=None), name='tf.nn.silu_23/IdentityN:0', description="created by layer 'tf.nn.silu_23'")
input_layer1_shape: layer_id=625: (255, 256, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 255), dtype=tf.float32, name=None), name='conv2d_62/Conv2D:0', description="created by layer 'conv2d_62'")
====================================================================================
layer_type: Const
layer_id: 627
tf_layers_dict_shape: (1, 255, 1, 1)
====================================================================================
layer_type: Add
layer_id: 628
input_layer0: layer_id=626: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 255), dtype=tf.float32, name=None), name='conv2d_62/Conv2D:0', description="created by layer 'conv2d_62'")
input_layer1_shape: layer_id=627: (1, 255, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 255), dtype=tf.float32, name=None), name='tf.math.add_85/Add:0', description="created by layer 'tf.math.add_85'")
====================================================================================
layer_type: Const
layer_id: 629
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Reshape
layer_id: 630
input_layer0: layer_id=628: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 255), dtype=tf.float32, name=None), name='tf.math.add_85/Add:0', description="created by layer 'tf.math.add_85'")
input_layer1_shape: layer_id=629: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 3, 85), dtype=tf.float32, name=None), name='tf.reshape_36/Reshape:0', description="created by layer 'tf.reshape_36'")
====================================================================================
layer_type: Const
layer_id: 631
tf_layers_dict_shape: (5,)
====================================================================================
layer_type: Transpose
layer_id: 632
input_layer0: layer_id=630: KerasTensor(type_spec=TensorSpec(shape=(1, 20, 20, 3, 85), dtype=tf.float32, name=None), name='tf.reshape_36/Reshape:0', description="created by layer 'tf.reshape_36'")
input_layer1_shape: layer_id=631: (5,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 85), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_18/transpose:0', description="created by layer 'tf.compat.v1.transpose_18'")
====================================================================================
layer_type: Sigmoid
layer_id: 633
input_layer0: layer_id=632: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 85), dtype=tf.float32, name=None), name='tf.compat.v1.transpose_18/transpose:0', description="created by layer 'tf.compat.v1.transpose_18'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 85), dtype=tf.float32, name=None), name='tf.math.sigmoid_2/Sigmoid:0', description="created by layer 'tf.math.sigmoid_2'")
====================================================================================
layer_type: Const
layer_id: 634
tf_layers_dict_shape: (1,)
====================================================================================
layer_type: Const
layer_id: 635
tf_layers_dict_shape: (3,)
====================================================================================
layer_type: VariadicSplit
layer_id: 636
input_layer0: layer_id=633: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 85), dtype=tf.float32, name=None), name='tf.math.sigmoid_2/Sigmoid:0', description="created by layer 'tf.math.sigmoid_2'")
input_layer1: layer_id=634: Const(ndarray).shape (1,)
input_layer2: layer_id=635: Const(ndarray).shape (3,)
tf_layers_dict0: layer_id_port: 636:3 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.slice_6/Slice:0', description="created by layer 'tf.slice_6'")
tf_layers_dict1: layer_id_port: 636:4 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.slice_7/Slice:0', description="created by layer 'tf.slice_7'")
tf_layers_dict2: layer_id_port: 636:5 KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 81), dtype=tf.float32, name=None), name='tf.slice_8/Slice:0', description="created by layer 'tf.slice_8'")
====================================================================================
layer_type: Const
layer_id: 637
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 638
input_layer0: layer_id=636:3: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.slice_6/Slice:0', description="created by layer 'tf.slice_6'")
input_layer1_shape: layer_id=637: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_8/Mul:0', description="created by layer 'tf.math.multiply_8'")
====================================================================================
layer_type: Const
layer_id: 639
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Add
layer_id: 640
input_layer0: layer_id=638: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_8/Mul:0', description="created by layer 'tf.math.multiply_8'")
input_layer1_shape: layer_id=639: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.add_86/Add:0', description="created by layer 'tf.math.add_86'")
====================================================================================
layer_type: Const
layer_id: 641
tf_layers_dict_shape: (1, 3, 20, 20, 2)
====================================================================================
layer_type: Add
layer_id: 642
input_layer0: layer_id=640: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.add_86/Add:0', description="created by layer 'tf.math.add_86'")
input_layer1_shape: layer_id=641: (1, 3, 20, 20, 2)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.add_87/Add:0', description="created by layer 'tf.math.add_87'")
====================================================================================
layer_type: Const
layer_id: 643
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 644
input_layer0: layer_id=642: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.add_87/Add:0', description="created by layer 'tf.math.add_87'")
input_layer1_shape: layer_id=643: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_9/Mul:0', description="created by layer 'tf.math.multiply_9'")
====================================================================================
layer_type: Const
layer_id: 645
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Multiply
layer_id: 646
input_layer0: layer_id=636:4: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.slice_7/Slice:0', description="created by layer 'tf.slice_7'")
input_layer1_shape: layer_id=645: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_10/Mul:0', description="created by layer 'tf.math.multiply_10'")
====================================================================================
layer_type: Const
layer_id: 647
tf_layers_dict_shape: (1, 1, 1, 1, 1)
====================================================================================
layer_type: Power
layer_id: 648
input_layer0: layer_id=646: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_10/Mul:0', description="created by layer 'tf.math.multiply_10'")
input_layer1_shape: layer_id=647: (1, 1, 1, 1, 1)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.pow_2/Pow:0', description="created by layer 'tf.math.pow_2'")
====================================================================================
layer_type: Const
layer_id: 649
tf_layers_dict_shape: (1, 3, 20, 20, 2)
====================================================================================
layer_type: Multiply
layer_id: 650
input_layer0: layer_id=648: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.pow_2/Pow:0', description="created by layer 'tf.math.pow_2'")
input_layer1_shape: layer_id=649: (1, 3, 20, 20, 2)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_11/Mul:0', description="created by layer 'tf.math.multiply_11'")
====================================================================================
layer_type: Concat
layer_id: 651
input_layer0: layer_id=644: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_9/Mul:0', description="created by layer 'tf.math.multiply_9'")
input_layer1: layer_id=650: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 2), dtype=tf.float32, name=None), name='tf.math.multiply_11/Mul:0', description="created by layer 'tf.math.multiply_11'")
input_layer2: layer_id=636:5: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 81), dtype=tf.float32, name=None), name='tf.slice_8/Slice:0', description="created by layer 'tf.slice_8'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 85), dtype=tf.float32, name=None), name='tf.concat_26/concat:0', description="created by layer 'tf.concat_26'")
axis: 4
====================================================================================
layer_type: Const
layer_id: 652
tf_layers_dict_shape: (3,)
====================================================================================
layer_type: Reshape
layer_id: 653
input_layer0: layer_id=651: KerasTensor(type_spec=TensorSpec(shape=(1, 3, 20, 20, 85), dtype=tf.float32, name=None), name='tf.concat_26/concat:0', description="created by layer 'tf.concat_26'")
input_layer1_shape: layer_id=652: (3,)
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 1200, 85), dtype=tf.float32, name=None), name='tf.reshape_37/Reshape:0', description="created by layer 'tf.reshape_37'")
====================================================================================
layer_type: Concat
layer_id: 654
input_layer0: layer_id=531: KerasTensor(type_spec=TensorSpec(shape=(1, 19200, 85), dtype=tf.float32, name=None), name='tf.reshape_33/Reshape:0', description="created by layer 'tf.reshape_33'")
input_layer1: layer_id=592: KerasTensor(type_spec=TensorSpec(shape=(1, 4800, 85), dtype=tf.float32, name=None), name='tf.reshape_35/Reshape:0', description="created by layer 'tf.reshape_35'")
input_layer2: layer_id=653: KerasTensor(type_spec=TensorSpec(shape=(1, 1200, 85), dtype=tf.float32, name=None), name='tf.reshape_37/Reshape:0', description="created by layer 'tf.reshape_37'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 25200, 85), dtype=tf.float32, name=None), name='tf.concat_27/concat:0', description="created by layer 'tf.concat_27'")
axis: 1
====================================================================================
layer_type: Result
layer_id: 655
input_layer0: layer_id=654: KerasTensor(type_spec=TensorSpec(shape=(1, 25200, 85), dtype=tf.float32, name=None), name='tf.concat_27/concat:0', description="created by layer 'tf.concat_27'")
tf_layers_dict: KerasTensor(type_spec=TensorSpec(shape=(1, 25200, 85), dtype=tf.float32, name=None), name='tf.identity/Identity:0', description="created by layer 'tf.identity'")
====================================================================================
TensorFlow/Keras model building process complete!
saved_model output started ==========================================================
saved_model output complete!
.pb output started ==================================================================
.pb output complete! - saved_model/model_float32.pb
tflite Float32 convertion started ===================================================
Estimated count of arithmetic ops: 4.256 G  ops, equivalently 2.128 G  MACs
WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded
tflite Float32 convertion complete! - saved_model/model_float32.tflite
Dynamic Range Quantization started ==================================================
Estimated count of arithmetic ops: 4.256 G  ops, equivalently 2.128 G  MACs
WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded
Dynamic Range Quantization complete! - saved_model/model_dynamic_range_quant.tflite
Weight Quantization started =========================================================
WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.
WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.
WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.
Estimated count of arithmetic ops: 4.256 G  ops, equivalently 2.128 G  MACs
WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded
Weight Quantization complete! - saved_model/model_weight_quant.tflite
Float16 Quantization started ========================================================
Estimated count of arithmetic ops: 4.256 G  ops, equivalently 2.128 G  MACs
WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded
Float16 Quantization complete! - saved_model/model_float16_quant.tflite
numpy dataset load started ==========================================================
numpy dataset load complete!
Integer Quantization started ========================================================
Estimated count of arithmetic ops: 4.256 G  ops, equivalently 2.128 G  MACs
fully_quantize: 0, inference_type: 6, input_inference_type: 0, output_inference_type: 0
Estimated count of arithmetic ops: 4.256 G  ops, equivalently 2.128 G  MACs
WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded
Integer Quantization complete! - saved_model/model_integer_quant.tflite
TensorFlow.js Float32 convertion started ============================================
Writing weight file saved_model/tfjs_model_float32/model.json...

TensorFlow.js convertion complete! - saved_model/tfjs_model_float32
TensorFlow.js Float16 convertion started ============================================
Writing weight file saved_model/tfjs_model_float16/model.json...

TensorFlow.js convertion complete! - saved_model/tfjs_model_float16
CoreML convertion started ===========================================================
Running TensorFlow Graph Passes: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:00<00:00, 10.16 passes/s]
Converting Frontend ==> MIL Ops: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 761/761 [00:00<00:00, 1025.80 ops/s]
Running MIL Common passes: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 34/34 [00:00<00:00, 37.28 passes/s]
Running MIL Clean up passes: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 9/9 [00:00<00:00, 39.13 passes/s]
Translating MIL ==> NeuralNetwork Ops: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1243/1243 [00:00<00:00, 12653.74 ops/s]
CoreML convertion complete! - saved_model/model_coreml_float32.mlmodel
All the conversion process is finished! =============================================