StephanAkkerman / crypto-forecasting-benchmark

This repository contains the codebase used in the research conducted for the paper titled "Benchmarking Cryptocurrency Forecasting Models in the Context of Data Properties and Market Factors." The study involved a rigorous assessment of thirteen different time series forecasting models over twenty-one cryptocurrencies and four distinct time frames.
MIT License
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Bump torch from 1.12.1 to 2.0.1 #8

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Bumps torch from 1.12.1 to 2.0.1.

Release notes

Sourced from torch's releases.

PyTorch 2.0.1 Release, bug fix release

This release is meant to fix the following issues (regressions / silent correctness):

  • Fix _canonical_mask throws warning when bool masks passed as input to TransformerEncoder/TransformerDecoder (#96009, #96286)
  • Fix Embedding bag max_norm=-1 causes leaf Variable that requires grad is being used in an in-place operation #95980
  • Fix type hint for torch.Tensor.grad_fn, which can be a torch.autograd.graph.Node or None. #96804
  • Can’t convert float to int when the input is a scalar np.ndarray. #97696
  • Revisit torch._six.string_classes removal #97863
  • Fix module backward pre-hooks to actually update gradient #97983
  • Fix load_sharded_optimizer_state_dict error on multi node #98063
  • Warn once for TypedStorage deprecation #98777
  • cuDNN V8 API, Fix incorrect use of emplace in the benchmark cache #97838

Torch.compile:

  • Add support for Modules with custom getitem method to torch.compile #97932
  • Fix improper guards with on list variables. #97862
  • Fix Sequential nn module with duplicated submodule #98880

Distributed:

  • Fix distributed_c10d's handling of custom backends #95072
  • Fix MPI backend not properly initialized #98545

NN_frontend:

  • Update Multi-Head Attention's doc string #97046
  • Fix incorrect behavior of is_causal paremeter for torch.nn.TransformerEncoderLayer.forward #97214
  • Fix error for SDPA on sm86 and sm89 hardware #99105
  • Fix nn.MultiheadAttention mask handling #98375

DataLoader:

  • Fix regression for pin_memory recursion when operating on bytes #97737
  • Fix collation logic #97789
  • Fix Ppotentially backwards incompatible change with DataLoader and is_shardable Datapipes #97287

MPS:

  • Fix LayerNorm crash when input is in float16 #96208
  • Add support for cumsum on int64 input #96733
  • Fix issue with setting BatchNorm to non-trainable #98794

Functorch:

  • Fix Segmentation Fault for vmaped function accessing BatchedTensor.data #97237
  • Fix index_select support when dim is negative #97916
  • Improve docs for autograd.Function support #98020
  • Fix Exception thrown when running Migration guide example for jacrev #97746

Releng:

Torch.optim:

  • Fix fused AdamW causes NaN loss #95847
  • Fix Fused AdamW has worse loss than Apex and unfused AdamW for fp16/AMP #98620

The release tracker should contain all relevant pull requests related to this release as well as links to related issues

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dependabot[bot] commented 1 year ago

Looks like torch is up-to-date now, so this is no longer needed.