| Fix documentation to point to torch.overrides instead of _overrides |
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| Core dump when checking that basic CNN works (Python 3.9) high priority module: autograd module: crash module: pybind triaged |
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| Tensor-expression fuser bugfixes for 1.7.1 |
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| [v1.7.1] Various setup.py fixes |
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| [v1.7.1] Enable Python 3.9 for Windows builds |
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| [v1.7.1] Add Python 3.9 support (linux / macOS) |
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| Add max supported SM for nvrtc-11.0 |
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| [torch][te] aten::type_as is unary, not binary |
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| [pytorch][te] Handle negative axis in chunk |
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| Constructing a ParameterDict raises a warning high priority module: nn |
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| Incorrect info about overriding torch tensors in version 1.7.0 high priority |
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| torch.arange numerics are different after 1.7 update on CPU high priority |
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| [complex] torch.{sqrt, abs}: does not match numpy high priority |
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| torch/utils/collect_env.py no longer works if pytorch is not installed |
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| libtorch 1.5.0 libiomp5.dylib contains erroneous link to /DLC/torch/libiomp5.dylib instead of using @rpath |
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| max_pool1d crashes (segfault) |
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| Fix max_pool1d on discontiguous tensor |
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torch.version.debug returns True for release builds |
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| Fix mul cuda for bool |
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| RuntimeError: "mul_cuda" not implemented for 'Bool |
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| Update pybind to 2.6.0 |
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| Fix torch.version.debug generation |
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| [quant] Quantized AdaptivePool3d is much slower for ChannelsLast3d |
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| Incorrect output loss value under specific CUDA version high priority |
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| Error out when parameters() is called on replicated models |
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| Pytorch 1.5.0 (installed from conda) errors with complaints about incompatibility between MKL and libgomp when using Pytorch's multiprocessing has workaround |
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| PyTorch 1.7.0 CUDA driver warning |
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| ProcessGroupNCCL NCCL lib version mismatch |
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| Fix incorrect signatures in get_testing_overrides for 1.7 release |
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| Fix output type of torch.max for Tensor subclasses |
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