Tensors and Dynamic neural networks in Python with strong GPU acceleration
This release is meant to fix the following issues (regressions / silent correctness):
RuntimeError: cannot create std::vector larger than max_size()
in torch.nn.functional.conv1d
on non-contiguous cpu inputs by patching OneDNN (https://github.com/pytorch/builder/pull/1742) (https://github.com/pytorch/builder/pull/1744)torch.distributed.fsdp.StateDictType.FULL_STATE_DICT
for when using torch.distributed.fsdp.FullyShardedDataParallel
with the device_mesh
argument (https://github.com/pytorch/pytorch/pull/120837)make triton
command on release branch for users building the release branch from source (https://github.com/pytorch/pytorch/pull/121169)Release tracker https://github.com/pytorch/pytorch/issues/120999 contains all relevant pull requests related to this release as well as links to related issues.
This release is meant to fix the following issues (regressions / silent correctness):
_to_copy
operation (https://github.com/pytorch/pytorch/pull/116426)param.grad_fn
for next forward (https://github.com/pytorch/pytorch/pull/116792)AsyncCollectiveTensor
in FSDP Extension (https://github.com/pytorch/pytorch/pull/116122)AssertionError
on tensor subclass when setting sync_module_states=True
(https://github.com/pytorch/pytorch/pull/117336)_gather_state_dict()
to be synchronous with respect to the mian stream. (https://github.com/pytorch/pytorch/pull/118197) (https://github.com/pytorch/pytorch/pull/119716)torch.distributed.DistNetworkError
: [WinError 32] The process cannot access the file because it is being used by another process (https://github.com/pytorch/pytorch/pull/118860)import torch
on CPUs that do not support SSE4.1 (https://github.com/pytorch/pytorch/issues/116623)get_state_dict
and set_state_dict
(https://github.com/pytorch/pytorch/pull/119573)mixedmm
on NVIDIA V100 (https://github.com/pytorch/pytorch/pull/118591)DTensor.from_local
in trace_rule_look up (https://github.com/pytorch/pytorch/pull/119659)Release tracker https://github.com/pytorch/pytorch/issues/119295 contains all relevant pull requests related to this release as well as links to related issues.
This release is meant to fix the following issues (regressions / silent correctness):
torch.set_num_threads
(https://github.com/pytorch/pytorch/pull/113684)The Cherry pick tracker https://github.com/pytorch/pytorch/issues/113962 contains all relevant pull requests related to this release as well as links to related issues.
This release is meant to fix the following issues (regressions / silent correctness):
torch.distributed.checkpoint.optimizer.load_sharded_optimizer_state_dict
(#111687)planner
argument to torch.distributed.checkpoint.optimizer.load_sharded_optimizer_state_dict
(#111393)torch.distributed.FSDP
(#109116)torch.nn.functional.scaled_dot_product_attention
(#112673)nn.functional.scaled_dot_product_attention
(#110893)torch.sparse.mm
for non-contiguous inputs (#111742)The https://github.com/pytorch/pytorch/issues/110961 contains all relevant pull requests related to this release as well as links to related issues.
This release is meant to fix the following issues (regressions / silent correctness):
_canonical_mask
throws warning when bool masks passed as input to TransformerEncoder/TransformerDecoder (#96009, #96286)is_causal
paremeter for torch.nn.TransformerEncoderLayer.forward #97214The release tracker should contain all relevant pull requests related to this release as well as links to related issues
This release is meant to fix the following issues (regressions / silent correctness):
The release tracker should contain all relevant pull requests related to this release as well as links to related issues