[Frontend][PyTorch] support for quantized conv_transpose2d op #9133
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PyTorch uses the same underlying function to pack and unpack the params for conv2d and conv_transpose2d ops. This change adds support for quantized conv_transpose2d op by reusing the ConvPackedParam and adding the output_padding param to it. This output_padding param will remain unused in case of conv2d. Also added test for above with specific condition for torch v1.7.1 and below.
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AndrewZhaoLuo
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* main: Fix flaky NMS test by making sure scores are unique (apache#9140) [Relay] Merge analysis/context_analysis.cc and transforms/device_annotation.cc (apache#9038) [LLVM] Make changes needed for opaque pointers (apache#9138) Arm(R) Ethos(TM)-U NPU codegen integration (apache#8849) [CI] Split Integration tests out of first phase of pipeline (apache#9128) [Meta Schedule][M3b] Runner (apache#9111) Fix Google Mock differences between Ubuntu 18.04 and 16.04 (apache#9141) [TIR] add loop partition hint pragma (apache#9121) fix things (apache#9146) [Meta Schedule][M3a] SearchStrategy (apache#9132) [Frontend][PyTorch] support for quantized conv_transpose2d op (apache#9133) [UnitTest] Parametrized test_conv2d_int8_intrinsics (apache#9143) [OpenCL] Remove redundant visit statement in CodeGen. (apache#9144) [BYOC] support arbitrary input dims for add/mul/relu of dnnl c_src codegen (apache#9127) [Relay][ConvertLayout] Support for qnn.conv2d_transpose (apache#9139) add nn.global_avgpool to fq2i (apache#9137) [UnitTests] Enable minimum testing on Vulkan target in CI (apache#9093) [Torch] Support returning quantized weights and bias for BYOC use cases (apache#9135) [Relay] Prepare for new plan_devices.cc (part II) (apache#9130) [microTVM][Zephyr] Add MIMXRT1050 board support (apache#9068)
AndrewZhaoLuo
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* main: (80 commits) Introduce centralised name transformation functions (apache#9088) [OpenCL] Add vectorization to cuda conv2d_nhwc schedule (apache#8636) [6/6] Arm(R) Ethos(TM)-U NPU codegen integration with `tvmc` (apache#8854) [microTVM] Add wrapper for creating project using a MLF (apache#9090) Fix typo (apache#9156) [Hotfix][Testing] Wait for RPCServer to be established (apache#9150) Update find cublas so it search default path if needed. (apache#9149) [TIR][LowerMatchBuffer] Fix lowering strides when source region has higher dimension than the buffer (apache#9145) Fix flaky NMS test by making sure scores are unique (apache#9140) [Relay] Merge analysis/context_analysis.cc and transforms/device_annotation.cc (apache#9038) [LLVM] Make changes needed for opaque pointers (apache#9138) Arm(R) Ethos(TM)-U NPU codegen integration (apache#8849) [CI] Split Integration tests out of first phase of pipeline (apache#9128) [Meta Schedule][M3b] Runner (apache#9111) Fix Google Mock differences between Ubuntu 18.04 and 16.04 (apache#9141) [TIR] add loop partition hint pragma (apache#9121) fix things (apache#9146) [Meta Schedule][M3a] SearchStrategy (apache#9132) [Frontend][PyTorch] support for quantized conv_transpose2d op (apache#9133) [UnitTest] Parametrized test_conv2d_int8_intrinsics (apache#9143) ...
ylc
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…#9133) * [Frontend][PyTorch] support for quantized conv_transpose2d op PyTorch uses the same underlying function to pack and unpack the params for conv2d and conv_transpose2d ops. This change adds support for quantized conv_transpose2d op by reusing the ConvPackedParam and adding the output_padding param to it. This output_padding param will remain unused in case of conv2d. Also added test for above with specific condition for torch v1.7.1 and below. * fix after merging main
ylc
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…#9133) * [Frontend][PyTorch] support for quantized conv_transpose2d op PyTorch uses the same underlying function to pack and unpack the params for conv2d and conv_transpose2d ops. This change adds support for quantized conv_transpose2d op by reusing the ConvPackedParam and adding the output_padding param to it. This output_padding param will remain unused in case of conv2d. Also added test for above with specific condition for torch v1.7.1 and below. * fix after merging main
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PyTorch uses the same underlying function to pack and unpack the params for conv2d and conv_transpose2d ops.
This change adds support for quantized conv_transpose2d op by reusing the ConvPackedParam and adding the output_padding param to it.
This output_padding param will remain unused in case of conv2d.
Also added test for above with specific condition for torch v1.7.1 and below.