Convert operators to qdq folding #7330
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The node.args that comes from nn.Parameters in the state_dict sometimes have the requires_grad property set to True. It's seems to stem already from the export stage and .eval() doesn't change the parameter. Address it here in the pass for now. Signed-off-by: Per Åstrand <per.astrand@arm.com> Change-Id: Ie7425764f1f1865de0fc66e1d020f804c7e936b1
Quantized models might have output without quantization parameters attached to them. The assert for parameters not being None are removed and handled in order to allow for that case. numpy transpose is removed in favor of torch.permute to keep the type of the output after the operation. Signed-off-by: Per Åstrand <per.astrand@arm.com> Change-Id: I0e404062154cefa39f18b5706d72d19cac0e6d73
Signed-off-by: Per Åstrand <per.astrand@arm.com> Change-Id: I9201d8bafd543204b697c7276d6929ad3aa09f25
Signed-off-by: Per Åstrand <per.astrand@arm.com> Change-Id: I39d11cff0ef78df08e67f216b8e0bb86af9fac26
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/7330
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 Cancelled JobAs of commit 8e6570e with merge base 99d5b80 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Cancelled Check Labels (gh) due to new higher prio requests beeing raised. |
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Summary
Move more operators to use the QDQ folding pass
Test plan
Existing unit tests in the Arm backend.