12/8/2023 0 Comments TAGR 2.0![]() ![]() This next-generation release includes a Stable version of Accelerated Transformers (formerly called Better Transformers) Beta includes pile as the main API for PyTorch 2.0, the scaled_dot_product_attention function as part of torch.nn.functional, the MPS backend, functorch APIs in the torch.func module and other Beta/Prototype improvements across various inferences, performance and training optimization features on GPUs and CPUs. We are excited to announce the release of PyTorch® 2.0 ( release note) which we highlighted during the PyTorch Conference on 12/2/22! PyTorch 2.0 offers the same eager-mode development and user experience, while fundamentally changing and supercharging how PyTorch operates at compiler level under the hood with faster performance and support for Dynamic Shapes and Distributed. The release tracker should contain all relevant pull requests related to this release as well as links to related issues Fix Fused AdamW has worse loss than Apex and unfused AdamW for fp16/AMP #98620.Illegal instruction (core dumped) on Raspberry Pi 4.0 8gb - pytorch/builder#1370.PyTorch cannot be installed at the same time as numpy in a conda env on osx-64 / Python 3.11 #97031.Enable ROCm 5.4.2 manywheel and python 3.11 builds #99552.Linux aarch64 torchtext 0.15.1 wheels are missing for aarch64_linux platform - pytorch/builder#1375.Linux aarch64 wheels are missing the mkldnn+acl backend support - 54931c2.Fix Import torchaudio + pile crashes on exit #96231.Fix Convolutions for CUDA-11.8 wheel builds #99451.Fix Exception thrown when running Migration guide example for jacrev #97746.Improve docs for autograd.Function support #98020.Fix index_select support when dim is negative #97916.Fix Segmentation Fault for vmaped function accessing BatchedTensor.data #97237.Fix issue with setting BatchNorm to non-trainable #98794.Add support for cumsum on int64 input #96733.Fix LayerNorm crash when input is in float16 #96208.Fix Ppotentially backwards incompatible change with DataLoader and is_shardable Datapipes #97287.Fix regression for pin_memory recursion when operating on bytes #97737.Fix nn.MultiheadAttention mask handling #98375.Fix error for SDPA on sm86 and sm89 hardware #99105.Fix incorrect behavior of is_causal paremeter for torch.nn.TransformerEncoderLayer.forward #97214.Update Multi-Head Attention's doc string #97046.Fix MPI backend not properly initialized #98545.Fix distributed_c10d's handling of custom backends #95072.Fix Sequential nn module with duplicated submodule #98880.Fix improper guards with on list variables.Add support for Modules with custom getitem method to pile #97932.cuDNN V8 API, Fix incorrect use of emplace in the benchmark cache #97838.Warn once for TypedStorage deprecation #98777.Fix load_sharded_optimizer_state_dict error on multi node #98063.Fix module backward pre-hooks to actually update gradient #97983.Revisit torch._six.string_classes removal #97863.Can’t convert float to int when the input is a scalar np.ndarray.Fix type hint for _fn, which can be a or None.Fix Embedding bag max_norm=-1 causes leaf Variable that requires grad is being used in an in-place operation #95980.Fix _canonical_mask throws warning when bool masks passed as input to TransformerEncoder/TransformerDecoder ( #96009, #96286).This release is meant to fix the following issues (regressions / silent correctness): ![]()
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