Comments (1)
never mind
from pytorch.
Related Issues (20)
- [feature request] allow torch.compile calls with compiler options, but without modifying global dynamo options
- Option to hard fail for cudagraphs and/or more cudagraph logging HOT 1
- torch.export of ResNet with dynamic height fails due to constraint violation HOT 2
- DISABLED test_no_requires_grad_inplace (__main__.TestAutogradWithCompiledAutograd) HOT 2
- DISABLED test_aot_module_simplified_dynamic (__main__.TestAOTModuleSimplified) HOT 5
- `torch.histc` does not work with `torch.compile(dynamic=True)` HOT 2
- Request for Implementation of 'aten::isin.Tensor_Tensor_out' Operation on MPS Device HOT 4
- optim.apply_optimizer_in_backward does not account for gradient accumulation HOT 2
- decide how dynamo/export should handle parametrizations HOT 1
- `aot_module` + `torch.onnx.export` bug or user error?
- DISABLED test_alibi_bias_float32 (__main__.TestTemplatedSDPA) HOT 2
- DISABLED test_no_unnecessary_save (__main__.TestAutogradWithCompiledAutograd) HOT 1
- Add option to `torch.load(mmap=True)` to do `MAP_SHARED` rather than `MAP_PRIVATE` HOT 1
- DISABLED test_binary_op_list_error_cases__foreach_add_cuda_complex64 (__main__.TestForeachCUDA) HOT 1
- `torch.func.jvp` yields different output compared to original function with `torch.nn.functional.layer_norm`
- Not loading optimizer state separately from checkpoint causes errors with FQNs HOT 2
- Profiler does not record CUDA times
- `torch.func.linearize` fails when linearizing functions of gradients
- Triton Error [CUDA]: invalid device context when autograd.backward a triton kernel HOT 3
- Can't download pytorch/ timeouterror HOT 2
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from pytorch.