Closed Protozzzer closed 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! =============================================
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
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:
If i use my pretrained weights, i recieve:![image](https://user-images.githubusercontent.com/62403742/165576605-eee4bdd3-3ffa-4b45-a7e4-d48ae639a8db.png)
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
Source code for simple inference testing code
No response