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microsoft / MMdnn

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
MIT License
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Error converting keras model to pytorch #915

Open nischa564 opened 3 years ago

nischa564 commented 3 years ago

Platform (like ubuntu 16.04/win10): win10

Python version: 3.8.5

Source framework with version (like Tensorflow 1.4.1 with GPU): Tensorflow 2.3.0 with GPU

Destination framework with version (like CNTK 2.3 with GPU): Pytorch 1.7.1

Pre-trained model path (webpath or webdisk path): https://keras.io/examples/vision/mnist_convnet/

Running scripts: mmconvert -sf keras -iw my_h5_model.h5 -df pytorch -om pytorch_model.pth

Hello, I try to convert a keras model to a pytorch model. The error I get is:

Traceback (most recent call last): File "c:\users\nisch\anaconda3\envs\jntorchenv\lib\runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "c:\users\nisch\anaconda3\envs\jntorchenv\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\Users\Nisch\anaconda3\envs\jntorchenv\Scripts\mmconvert.exe__main.py", line 7, in File "c:\users\nisch\anaconda3\envs\jntorchenv\lib\site-packages\mmdnn\conversion_script\convert.py", line 102, in _main ret = convertToIR._convert(ir_args) File "c:\users\nisch\anaconda3\envs\jntorchenv\lib\site-packages\mmdnn\conversion_script\convertToIR.py", line 46, in _convert parser = Keras2Parser(model) File "c:\users\nisch\anaconda3\envs\jntorchenv\lib\site-packages\mmdnn\conversion\keras\keras2_parser.py", line 136, in init__ self.keras_graph.build() File "c:\users\nisch\anaconda3\envs\jntorchenv\lib\site-packages\mmdnn\conversion\keras\keras2_graph.py", line 48, in build for pred in node.inbound_layers: TypeError: 'InputLayer' object is not iterable

nischa564 commented 3 years ago

Hello, I solved this problem by using different versions:

Python version: 3.6.12

Source framework with version (like Tensorflow 1.4.1 with GPU): Tensorflow 1.15.2

Destination framework with version (like CNTK 2.3 with GPU): Pytorch 0.4.0

But now I am getting this error: Traceback (most recent call last): File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\mmdnn\conversion\keras\keras2_parser.py", line 104, in init from keras.applications.mobilenet import relu6 ImportError: cannot import name 'relu6'

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File "c:\users\nisch\anaconda3\envs\mmdnne\lib\runpy.py", line 193, in _run_module_as_main "main", mod_spec) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\runpy.py", line 85, in _run_code exec(code, run_globals) File "C:\Users\Nisch\anaconda3\envs\mmdnne\Scripts\mmconvert.exe__main.py", line 7, in File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\mmdnn\conversion_script\convert.py", line 102, in _main ret = convertToIR._convert(ir_args) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\mmdnn\conversion_script\convertToIR.py", line 46, in _convert parser = Keras2Parser(model) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\mmdnn\conversion\keras\keras2_parser.py", line 120, in init 'DepthwiseConv2D': layers.DepthwiseConv2D File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\engine\saving.py", line 419, in load_model model = _deserialize_model(f, custom_objects, compile) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\engine\saving.py", line 225, in _deserialize_model model = model_from_config(model_config, custom_objects=custom_objects) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\engine\saving.py", line 458, in model_from_config return deserialize(config, custom_objects=custom_objects) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\layers__init__.py", line 55, in deserialize printable_module_name='layer') File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\utils\generic_utils.py", line 145, in deserialize_keras_object list(custom_objects.items()))) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\engine\sequential.py", line 300, in from_config custom_objects=custom_objects) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\layers\init.py", line 55, in deserialize printable_module_name='layer') File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\utils\generic_utils.py", line 147, in deserialize_keras_object return cls.from_config(config['config']) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\engine\base_layer.py", line 1109, in from_config return cls(*config) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\legacy\interfaces.py", line 91, in wrapper return func(args, **kwargs) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\layers\convolutional.py", line 490, in init **kwargs) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\layers\convolutional.py", line 117, in init__ self.kernel_initializer = initializers.get(kernel_initializer) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\initializers.py", line 508, in get return deserialize(identifier) File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\initializers.py", line 503, in deserialize printable_module_name='initializer') File "c:\users\nisch\anaconda3\envs\mmdnne\lib\site-packages\keras\utils\generic_utils.py", line 138, in deserialize_keras_object ': ' + class_name) ValueError: Unknown initializer: GlorotUniform