OSError: SavedModel file does not exist at: saved_model/{saved_model.pbtxt|saved_model.pb}

Issue Type

Bug

OS

Ubuntu

OS architecture

x86_64

Programming Language

Python

Framework

TensorFlowLite

Download URL for tflite file

https://github.com/google/mediapipe/blob/0.8.0/mediapipe/modules/face_landmark/face_landmark.tflite

https://github.com/google/mediapipe/blob/0.8.0/mediapipe/modules/face_detection/face_detection_front.tflite

https://github.com/google/mediapipe/blob/0.8.0/mediapipe/modules/hand_landmark/hand_landmark.tflite

Convert Script

~/workdir $ tflite2tensorflow --model_path face_landmark.tflite --flatc_path ../flatc --schema_path ../schema.fbs --output_no_quant_float32_tflite

Description

docker pull ghcr.io/pinto0309/tflite2tensorflow:latest

docker run -it --rm \ -v pwd:/home/user/workdir \ ghcr.io/pinto0309/tflite2tensorflow:latest

Relevant Log Output

user@4cd1e8cc1577:~/workdir$ tflite2tensorflow --model_path tflite2tensorflow/resources/face_landmark_with_attention.tflite --flatc_path ../flatc --schema_path ../schema.fbs --output_no_quant_float32_tflite 
INFO: Created TensorFlow Lite XNNPACK delegate for CPU.
inputs:
{'dtype': <class 'numpy.float32'>,
 'index': 0,
 'name': 'input_1',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([  1, 192, 192,   3], dtype=int32),
 'shape_signature': array([  1, 192, 192,   3], dtype=int32),
 'sparsity_parameters': {}}
outputs:
{'dtype': <class 'numpy.float32'>,
 'index': 719,
 'name': 'output_mesh_identity',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([   1,    1,    1, 1404], dtype=int32),
 'shape_signature': array([   1,    1,    1, 1404], dtype=int32),
 'sparsity_parameters': {}}
{'dtype': <class 'numpy.float32'>,
 'index': 720,
 'name': 'output_lips',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([  1,   1,   1, 160], dtype=int32),
 'shape_signature': array([  1,   1,   1, 160], dtype=int32),
 'sparsity_parameters': {}}
{'dtype': <class 'numpy.float32'>,
 'index': 721,
 'name': 'output_left_eye',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([  1,   1,   1, 142], dtype=int32),
 'shape_signature': array([  1,   1,   1, 142], dtype=int32),
 'sparsity_parameters': {}}
{'dtype': <class 'numpy.float32'>,
 'index': 723,
 'name': 'output_right_eye',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([  1,   1,   1, 142], dtype=int32),
 'shape_signature': array([  1,   1,   1, 142], dtype=int32),
 'sparsity_parameters': {}}
{'dtype': <class 'numpy.float32'>,
 'index': 722,
 'name': 'output_left_iris',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([ 1,  1,  1, 10], dtype=int32),
 'shape_signature': array([ 1,  1,  1, 10], dtype=int32),
 'sparsity_parameters': {}}
{'dtype': <class 'numpy.float32'>,
 'index': 724,
 'name': 'output_right_iris',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([ 1,  1,  1, 10], dtype=int32),
 'shape_signature': array([ 1,  1,  1, 10], dtype=int32),
 'sparsity_parameters': {}}
{'dtype': <class 'numpy.float32'>,
 'index': 710,
 'name': 'conv_faceflag',
 'quantization': (0.0, 0),
 'quantization_parameters': {'quantized_dimension': 0,
                             'scales': array([], dtype=float32),
                             'zero_points': array([], dtype=int32)},
 'shape': array([1, 1, 1, 1], dtype=int32),
 'shape_signature': array([1, 1, 1, 1], dtype=int32),
 'sparsity_parameters': {}}
tflite Float32 convertion started ===================================================
ERROR: SavedModel file does not exist at: saved_model/{saved_model.pbtxt|saved_model.pb}
Traceback (most recent call last):
  File "/usr/local/bin/tflite2tensorflow", line 6046, in main
    converter = tf.lite.TFLiteConverter.from_saved_model(model_output_path)
  File "/usr/local/lib/python3.8/dist-packages/tensorflow/lite/python/lite.py", line 1786, in from_saved_model
    saved_model = _load(saved_model_dir, tags)
  File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/saved_model/load.py", line 782, in load
    result = load_partial(export_dir, None, tags, options)["root"]
  File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/saved_model/load.py", line 887, in load_partial
    loader_impl.parse_saved_model_with_debug_info(export_dir))
  File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/saved_model/loader_impl.py", line 57, in parse_saved_model_with_debug_info
    saved_model = parse_saved_model(export_dir)
  File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/saved_model/loader_impl.py", line 115, in parse_saved_model
    raise IOError(
OSError: SavedModel file does not exist at: saved_model/{saved_model.pbtxt|saved_model.pb}

Source code for simple inference testing code

No response

PINTO0309 / tflite2tensorflow

OSError: SavedModel file does not exist at: saved_model/{saved_model.pbtxt|saved_model.pb} #34