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Mllama single qpc support added #258
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# Out-of-place Scatter new into old | ||
# out-of-place is important so the original tensor is not affected, | ||
# otherwise leads to same operations in both graphs | ||
indices = (torch.arange(bsz),) |
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add a brief documentation on why these changes are required for single qpc and how does it create the graph.
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Sure, will update in final version.
return outputs | ||
return outputs | ||
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||
def generate_mllama_single(self, processor): |
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this is just required for the onnx export right?
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Yes, it is. As processor output varies model to model, this function will help to get the model specific processor output. Now I have also removed
the dependency of processor
by creating dummy inputs and made it generic for the single and dual qpcs
.
Signed-off-by: Amit Raj <[email protected]>
Signed-off-by: Amit Raj <[email protected]>
Signed-off-by: Amit Raj <[email protected]>
Signed-off-by: Amit Raj <[email protected]>
Signed-off-by: Amit Raj <[email protected]>
Signed-off-by: Amit Raj <[email protected]>
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Signed-off-by: Amit Raj <[email protected]>
Signed-off-by: Amit Raj <[email protected]>
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1. Mllama single qpc support added 2. Simplified generate inputs for single and dual qpc --------- Signed-off-by: Amit Raj <[email protected]> Co-authored-by: asmigosw <[email protected]> Signed-off-by: Amit Raj <[email protected]>
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