Comments (1)
@dlibenzi You have to put the "Fixes #" in the commit message to close the issue automatically when the commit lands.
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Related Issues (20)
- In spmd training of multiple machines, xp.trace is problematic HOT 4
- Import "torch_xla.core.xla_model" could not be resolved HOT 6
- torch_xla.distributed.parallel_loader doesn't shard data HOT 5
- Documentation: Discoverability of http://pytorch.org/xla HOT 5
- Error while trying to save a sharded model checkpoint on multi-host TPU HOT 6
- optimizer.step() takes too long in XLA/TPU HOT 4
- Prepare a documentation to explain the use cases for `torch.compile`, `torch_xla.compile`, torch_xla eager mode, torchxla2 HOT 1
- [hard] Op info test for `special.airy_ai` HOT 1
- SPMD Checkpointing Error HOT 6
- TPU V4-32 Failed to get global TPU topology. HOT 4
- Ran out of memory in memory space vmem / Extra memory due to padding HOT 2
- Copy data from TPU to CPU increases CompileTime HOT 4
- [hard] Op info test for `logdet` HOT 1
- Ran out of memory in memory space vmem / register allocator spill slots call depth 2 HOT 1
- Report real device for XLATensor2
- Core dump when calling `jax.device_put` on array mapped from torch.tensor to jax with xla2
- Registering CUDA custom calls with the C++ FFI HOT 1
- Processes hang when running multiprocess training with xmp.spawn, and one rank waits at rendezvous while another hits assertion HOT 2
- [benchmarks] `dlrm` training running twice on dynamo and non-dynamo configurations.
- 2.5 backport PR request list HOT 3
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