Adding support for dequantizing from int32 to float32. #4130
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@yzhliu @zhiics @vinx13 @anijain2305 Can you take a look at this PR? |
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* master: (51 commits) [QNN][TFLite] Parsing QNN Add op. Adding MobilenetV2. (apache#4142) [CI] Pin NNPack pthreadtools version (apache#4152) Fix typo (apache#4144) [Relay][Frontend][TF] Add tensor array ops (apache#3798) [relay][vm] Separate VM runtime with executable (apache#4100) [PATCH] Fix undefined __floatdihf in libtvmruntime.so on aarch64. (apache#4119) [DOCKER] Pin torchvision==0.4.1 (apache#4140) [TOPI][x86] Cascade lake support. (apache#4123) [Relay] Improve build error when no lowered funcs are produced (apache#4132) [RUNTIME] Refactor object python FFI to new protocol. (apache#4128) Update PULL_REQUEST_TEMPLATE.md Adding support for dequantizing from int32 to float32. (apache#4130) [Relay][Training] Add and fix gradients (apache#4126) [QNN] Change default rouning to UPWARD. (apache#4131) Fix infer type of kernel in dense. (apache#4125) [Relay][AlterOpLayout] NHWC to NCHWc pad operator. (apache#4103) [ARITH] Fix lowering of floormod(x, y) != 0 (apache#4127) [RFC][RUNTIME] Introduce new object protocol. (apache#4115) [Relay][Topi] Disable conv NHWC pack int8. (apache#4038) Update task_cpp_unittest.sh ...
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Mxnet supports fully connected quantized layers that takes in quantized inputs and produces float32 outputs. To support this case we need to allow dequantizing directly from int32 to float32.
In this PR i am enabling this feature and also adding test case for int32 to float32 dequantization.