Traceback (most recent call last):
File "test.py", line 10, in <module>
tf_model.run({'input_signal': input_example, 'input_signal_length': input_example_size})
File "venv/lib/python3.8/site-packages/onnx_tf/backend_rep.py", line 93, in run
output_values = self.tf_module(**input_dict)
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 828, in __call__
result = self._call(*args, **kwds)
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 871, in _call
self._initialize(args, kwds, add_initializers_to=initializers)
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 725, in _initialize
self._stateful_fn._get_concrete_function_internal_garbage_collected( # pylint: disable=protected-access
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2969, in _get_concrete_function_internal_garbage_collected
graph_function, _ = self._maybe_define_function(args, kwargs)
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3361, in _maybe_define_function
graph_function = self._create_graph_function(args, kwargs)
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3196, in _create_graph_function
func_graph_module.func_graph_from_py_func(
File "venv/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 990, in func_graph_from_py_func
func_outputs = python_func(*func_args, **func_kwargs)
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 634, in wrapped_fn
out = weak_wrapped_fn().__wrapped__(*args, **kwds)
File "venv/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3887, in bound_method_wrapper
return wrapped_fn(*args, **kwargs)
File "venv/lib/python3.8/site-packages/tensorflow/python/framework/func_graph.py", line 977, in wrapper
raise e.ag_error_metadata.to_exception(e)
ValueError: in user code:
venv/lib/python3.8/site-packages/onnx_tf/backend_tf_module.py:98 __call__ *
output_ops = self.backend._onnx_node_to_tensorflow_op(onnx_node,
venv/lib/python3.8/site-packages/onnx_tf/backend.py:289 _onnx_node_to_tensorflow_op *
return handler.handle(node, tensor_dict=tensor_dict, strict=strict)
venv/lib/python3.8/site-packages/onnx_tf/handlers/handler.py:59 handle *
return ver_handle(node, **kwargs)
venv/lib/python3.8/site-packages/onnx_tf/handlers/backend/conv.py:15 version_11 *
return cls.conv(node, kwargs["tensor_dict"])
venv/lib/python3.8/site-packages/onnx_tf/handlers/backend/conv_mixin.py:30 conv *
x_rank = len(x.get_shape())
venv/lib/python3.8/site-packages/tensorflow/python/autograph/operators/py_builtins.py:252 len_ **
return _py_len(s)
venv/lib/python3.8/site-packages/tensorflow/python/autograph/operators/py_builtins.py:317 _py_len
return len(s)
venv/lib/python3.8/site-packages/tensorflow/python/framework/tensor_shape.py:848 __len__
raise ValueError("Cannot take the length of shape with unknown rank.")
ValueError: Cannot take the length of shape with unknown rank.
Python, ONNX, ONNX-TF, Tensorflow version
Python version: 3.8.5 (default, Jan 27 2021, 15:41:15) [GCC 9.3.0]
ONNX version: 1.8.1
ONNX-TF version: 1.7.0
Tensorflow version: 2.4.1
Additional context
The ONNX file has been generated using Torch 1.8 with ONNX opset 12.
The ONNX file is valid according to the onnx library validator and evaluated without problems with onnxruntime.
Describe the bug
ValueError: Cannot take the length of shape with unknown rank.
exception is raised from convolution implementation during ONNX evaluation.ONNX model file
stt_fr_quartznet15x5.onnx
To Reproduce
Backtrace
Python, ONNX, ONNX-TF, Tensorflow version
Additional context
The ONNX file has been generated using Torch 1.8 with ONNX opset 12. The ONNX file is valid according to the
onnx
library validator and evaluated without problems withonnxruntime
.