fix/feat: Add and repair multiple converters for SD + other models #2353
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gs-olive
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Sep 29, 2023
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gs-olive
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Oct 3, 2023
zewenli98
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Oct 4, 2023
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Looks good overall. I was wondering if we add a prims decorator for those converters similar to aten, how should we specify source_ir? It doesn't seem appropriate to keep SourceIR.ATEN. Maybe write them again in prims_ops_converters? It feels sort of redundant...
| @@ -51,7 +51,7 @@ def sum( | |||
| ): | |||
| input_val = cast_trt_tensor(ctx, input_val, trt.float32, name) | |||
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| if dim is None: | |||
| if dim is None or (isinstance(dim, (tuple, list)) and len(dim) == 0): | |||
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Should we consider dim is [] or ()? In this case, the dim passed into axes will be 0.
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I thought that dim being empty implies the same thing as dim being None, which is to reduce over all axes
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This is the behavior in torch, at least with torch.sum
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- Focus on SD-performance-accelerating converters - Add test cases for converters to avoid regressions - Add prims sum converter
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Description
broadcast_in_dimprims.divsupportsumwhereFixes: #2346
Type of change
Checklist: