pytorch

03342af3 - Add env variable to bypass CUDACachingAllocator for debugging (#45294)

Add env variable to bypass CUDACachingAllocator for debugging (#45294) Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/45294 While tracking down a recent memory corruption bug we found that cuda-memcheck wasn't finding the bad accesses, and ngimel pointed out that it's because we use a caching allocator so a lot of "out of bounds" accesses land in a valid slab. This PR adds a runtime knob (`PYTORCH_NO_CUDA_MEMORY_CACHING`) that, when set, bypasses the caching allocator's caching logic so that allocations go straight to cudaMalloc. This way, cuda-memcheck will actually work. Test Plan: Insert some memory errors and run a test under cuda-memcheck; observe that cuda-memcheck flags an error where expected. Specifically I removed the output-masking logic here: https://github.com/pytorch/pytorch/blob/master/torch/csrc/jit/tensorexpr/cuda_codegen.cpp#L819-L826 And ran: ``` PYTORCH_NO_CUDA_MEMORY_CACHING=1 cuda-memcheck pytest -k test_superslomo test_jit_fuser_te.py ``` Reviewed By: ngimel Differential Revision: D23964734 Pulled By: bertmaher fbshipit-source-id: 04efd11e8aff037b9edde80c70585cb820ee6e39