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Tentatively eliminate graph break overhead #3741
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self.cudagraphs_enabled = torch_tensorrt.runtime.get_cudagraphs_mode() | ||
self.requires_unique_output = False |
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what do these do ?
# assert ( | ||
# contiguous_inputs[i].dtype == self.input_dtypes[i] | ||
# ), f"Dtype mismatch for {i}th input({input_name}). Expect {self.input_dtypes[i]}, got {contiguous_inputs[i].dtype}." |
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why is this commented ?
if self.sync_stream: | ||
self._engine_stream.wait_stream(self._caller_stream) |
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So if pytorch is not on default stream, both Pyt and TRT can run on same stream and outputs matched ?
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Do you know if there is a performance benefit of running Pytorch & TRT on a different stream vs (Pytorch on default and TRT on a separate stream ) ?
def set_requires_unique_output(self, requires_unique_output: bool) -> None: | ||
self.requires_unique_output = requires_unique_output |
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what does this do ? Consider adding a docstring for this
Description
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Fixes # (issue)
Type of change
Please delete options that are not relevant and/or add your own.
Checklist: