pytorch
https://github.com/pytorch/pytorch
Python
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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- Issues
- Multi-processing leaking file descriptors
- Setting a random seed or passing a generator to Modules for deterministic sampling.
- Unification of model initialization methods / naming across domain libraries + support of skip_init
- [pytorch v1.9.0] for torch sync.pipeline in a single GPU, passing tensor layer by layer is better or using the skip-connection API is better?
- [AWS EC2 P3DN, EFA is enabled] Torch RPC tensorpipe/common/ibv.h:172 "": Operation not supported
- [feature request] "Batched" index_select (i.e. simplified torch.gather with not specifying full index)
- RandomSampler / DistributedSampler does not seem really random
- Quantile is limited to 16 million elements and have poor performance.
- Either support torch.mean on BoolTensors or fix the error message
- [proposal] Let's unify the various gather/scatter ops.
- Docs
- Python not yet supported