feat: support aten.copy dynamo converter #2550
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component: api [Python]
gs-olive
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Dec 19, 2023
gs-olive
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Dec 19, 2023
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| return impl.cast.to_copy( | ||
| ctx, | ||
| target, | ||
| SourceIR.ATEN, | ||
| name, | ||
| src, | ||
| src.dtype, | ||
| force_layer=True, | ||
| ) |
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The force_layer=True does seem useful for the purpose of the test case, but in a normal model we should prefer force_layer=False. This should be a future feature, but to_copy should have an intelligent force_layer mechanism which can select whether to insert the layer based on whether the node is an input node to the TRTEngine.
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Yes, I agree with you, but for now TensorRT doesn't support the same input and output.
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I added #2561 to track this proposed feature (in Torch-TRT)
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gs-olive
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Dec 28, 2023
Comment on lines
+2560
to
+2574
| return impl.cast.to_copy( | ||
| ctx, | ||
| target, | ||
| SourceIR.ATEN, | ||
| name, | ||
| src, | ||
| src.dtype, | ||
| force_layer=True, | ||
| ) |
There was a problem hiding this comment.
I added #2561 to track this proposed feature (in Torch-TRT)
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Description
Support
aten.copydynamo converter.Fixes #2435
Type of change
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