fix: remove legacy conv converter by chohk88 · Pull Request #3343 · pytorch/TensorRT (original) (raw)
A RuntimeError occurs in many models when the output_padding argument for deconvolution is non-zero. The current CTX converter cannot handle this case, so the legacy FX converter is used instead. However, the legacy FX converter also raises a RuntimeError for deconvolutions with non-zero output_padding. If the legacy converter is removed, it results in graph breaks but avoids RuntimeErrors.
The ideal solution would be to implement a dedicated converter for deconvolutions with non-zero output_padding. However, TensorRT's Python API does not currently support output_padding as an input for tensorrt.IDeconvolutionLayer, making this implementation very challenging. It is recommended to create a separate issue to discuss and address this limitation.
File "/usr/local/lib/python3.12/dist-packages/model_navigator/commands/execution_context.py", line 156, in _execute_function
fire.Fire(func, unwrapped_args)
File "/usr/local/lib/python3.12/dist-packages/fire/core.py", line 143, in Fire
component_trace = _Fire(component, args, parsed_flag_args, context, name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/fire/core.py", line 477, in _Fire
component, remaining_args = _CallAndUpdateTrace(
^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/fire/core.py", line 693, in _CallAndUpdateTrace
component = fn(*varargs, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/model_navigator/commands/convert/converters/ep2torchtrt.py", line 142, in convert
with TimingCacheManager(model_name=model_name, cache_path=timing_cache_dir) as timing_cache:
File "/usr/local/lib/python3.12/dist-packages/model_navigator/frameworks/tensorrt/timing_tactics.py", line 267, in __exit__
raise exc_value
File "/usr/local/lib/python3.12/dist-packages/model_navigator/commands/convert/converters/ep2torchtrt.py", line 149, in convert
tr_model_compiled = torch_tensorrt.dynamo.compile(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/_compiler.py", line 288, in compile
trt_gm = compile_module(
^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/_compiler.py", line 462, in compile_module
trt_module = convert_module(
^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/conversion/_conversion.py", line 142, in convert_module
interpreter_result = interpret_module_to_result(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/conversion/_conversion.py", line 121, in interpret_module_to_result
interpreter_result = interpreter.run()
^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py", line 610, in run
self._construct_trt_network_def()
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py", line 347, in _construct_trt_network_def
super().run()
File "/usr/local/lib/python3.12/dist-packages/torch/fx/interpreter.py", line 146, in run
self.env[node] = self.run_node(node)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py", line 676, in run_node
trt_node: torch.fx.Node = super().run_node(n)
^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch/fx/interpreter.py", line 203, in run_node
return getattr(self, n.op)(n.target, args, kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py", line 783, in call_function
return converter(self.ctx.net, target, args, kwargs, self._cur_node_name)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/dist-packages/torch_tensorrt/fx/converters/aten_ops_converters.py", line 125, in aten_ops_convolution
raise RuntimeError(f"Target {target} does not support `transposed=True` ")
RuntimeError: Target aten.convolution.default does not support `transposed=True`
While executing %convolution_15 : [num_users=1] = call_function[target=torch.ops.aten.convolution.default](args = (%cat, %model_1_submodule_1_submodule_1_submodule_2_0_conv_weight, %model_1_submodule_1_submodule_1_submodule_2_0_conv_bias, [2, 2], [1, 1], [1, 1], True, [1, 1], 1), kwargs = {_itensor_to_tensor_meta: {<tensorrt.tensorrt.ITensor object at 0x7f4269bc4770>: ((1, 1, 128, 128), torch.float32, False, (16384, 16384, 128, 1), torch.channels_last, False, {}), <tensorrt.tensorrt.ITensor object at 0x7f4269695370>: ((1, 16, 64, 64), torch.float32, False, (65536, 4096, 64, 1), torch.contiguous_format, False, {}), <tensorrt.tensorrt.ITensor object at 0x7f4269bc9b30>: ((1, 16, 64, 64), torch.float32, False, (65536, 4096, 64, 1), torch.contiguous_format, False, {}), <tensorrt.tensorrt.ITensor object at 0x7f4269bbb570>: ((1, 16, 64, 64), torch.float32, False, (65536, 4096, 64, 1), torch.contiguous_format, False, {}), <tensorrt.tensorrt.ITensor object at 0x7f4269bb8d30>: ((1, 16, 1, 1), 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Original traceback:
File "/usr/local/lib/python3.12/dist-packages/monai/networks/nets/unet.py", line 297, in forward
x = self.model(x)
File "/usr/local/lib/python3.12/dist-packages/monai/networks/layers/simplelayers.py", line 129, in forward
y = self.submodule(x)
File "/usr/local/lib/python3.12/dist-packages/monai/networks/layers/simplelayers.py", line 129, in forward
y = self.submodule(x)
File "/usr/local/lib/python3.12/dist-packages/monai/networks/layers/simplelayers.py", line 129, in forward
y = self.submodule(x)
Please delete options that are not relevant and/or add your own.