Comments (1)
- Job name:
periodic / win-vs2019-cuda11.8-py3 / test (default)
- Credential:
atalman
Within ~15 minutes, periodic / win-vs2019-cuda11.8-py3 / test (default)
and all of its dependants will be unstable in PyTorch CI. Please verify that the job name looks correct. With great power comes great responsibility.
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Related Issues (20)
- [ONNX][low pri] Move old (non-public) implementation into legacy/ and schedule for deprecation
- `argsort()` can use the 0D tensor of a complex type value against error message HOT 1
- Upgrade dependencies MKL and Intel OpenMP to 2024.2.0 HOT 6
- The unexpected behavior of `argsort()`
- `msort()` can use the 0D tensor of a complex type value against error message HOT 1
- [TP+FSDP2] model weights become fully shard again after calling model.unshard() followed by dcp get_model_state_dict HOT 1
- `int` type for `dims` of `tile()` without `dims=` works with a tensor against the doc HOT 2
- `repeat_interleave()` without `repeats` argument and `input` keyword works HOT 1
- [export/dynamo] torch._check fails at compile time when the condition evaluates to False HOT 7
- Torch dynamo deep dive and overview discrepancy HOT 1
- _foreach_addc_
- Fuyou Training Framework Integration for PyTorch HOT 3
- Exporting the operator 'aten::fft_fft' to ONNX opset version 12 is not supported.
- torch.Tensor.register_hook() source link does not work HOT 3
- `start` and `step` of `arange()` should be optional on the doc HOT 1
- `end`, `start` and `step` argument of `arange()` work with a 0D tensor against error messages HOT 2
- pytorch-nightly export KINETO_USE_DAEMON=1 Cannot initialize CUDA without ATen_cuda library
- `linspace()` can also use `complex` and `bool` type for `start` and `end` argument against the doc HOT 1
- NCCL Blocking Send/Recv are Non-blocking in practice HOT 2
- Error when loading a module file by calling torch::jit::load(..)
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