fix: Record cudagraphs when weight streaming budget has changed #3309
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core/runtime/execute_engine.cpp
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| // Whether cudagraphs needs to record the graph on this pass | ||
| bool need_cudagraphs_record = (CUDAGRAPHS_MODE && (!_cudagraphs_validate_shapes(inputs, compiled_engine))); | ||
| bool need_cudagraphs_record = |
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Seems like we need something a bit more comprehensive than a bunch of booleans for cudagraph rerecord
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I agree with it. I'm thinking of below structure. Could you review [PR3276]?(#3276)
https://github.com/pytorch/TensorRT/pull/3276/files#diff-3d6304b0f21f64bdf7867ceac346866d505619401e9c7b6a696cfe3bb567254eR37-R63
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Will adopt proper structure for runtime states after #3276 is reviewed. |
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| def test_weight_streaming_cudagraphs(self, _, use_python_runtime): | ||
| model = SampleModel().eval().cuda() | ||
| input = [torch.randn(*INPUT_SIZE, dtype=torch.float32).cuda()] | ||
| fx_graph = torch.fx.symbolic_trace(model) |
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can you use torch.export.export() to export the model?
| name="x", | ||
| ) | ||
| model = SampleModel().eval().cuda() | ||
| fx_graph = torch.fx.symbolic_trace(model) |
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same here. Use torch.export.export()
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Description
Add flag indicates to reevaluate the runtime settings when weight streaming budget is changed.
Fixes #3308
Type of change
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Checklist: