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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 <quic_amitraj@quicinc.com>
Signed-off-by: Amit Raj <quic_amitraj@quicinc.com>
Signed-off-by: Amit Raj <quic_amitraj@quicinc.com>
Signed-off-by: Amit Raj <quic_amitraj@quicinc.com>
Signed-off-by: Amit Raj <quic_amitraj@quicinc.com>
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Signed-off-by: Amit Raj <quic_amitraj@quicinc.com>
Signed-off-by: Amit Raj <quic_amitraj@quicinc.com>
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1. Mllama single qpc support added 2. Simplified generate inputs for single and dual qpc --------- Signed-off-by: Amit Raj <quic_amitraj@quicinc.com> Co-authored-by: asmigosw <asmigosw@qti.qualcomm.com> Signed-off-by: Amit Raj <quic_amitraj@quicinc.com>
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