fix zero-batch handling in convtranspose (#24341)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/24341
ConvTransposeOp doesn't crash for zero-batch, but it doesn't modify the output blob. This leads to buggy behaviour especially when running the same network twice using different input, or backprop during training.
Seems `ConvTransposeUnpoolBase<Context>::GetOutputSize` works for zero-batch, so I remove the check for `input.numel() > 0`, and reshape the output blob before returning.
For CudnnConvTransposeGradientOp, it's a bit verbose to set `dfilter` and `dbias`, it's a seems the Cudnn can handle it, so simply remove the `X.numel() == 0` branch.
Test Plan: buck test mode/dev-nosan caffe2/caffe2/python/operator_test:conv_transpose_test -- --run-disabled
Reviewed By: BIT-silence
Differential Revision: D16807606
fbshipit-source-id: 0d72c5bd8f2e03c34465e7b530cca548d9bdd5e1
