Related Issues (20)
- Support NeMo NeVa Model
- Support NeMo MegatronGPTModel
- import thunder tries to initialize all native executors HOT 3
- Support `torch.nn.functional.adaptive_avg_pool2d` HOT 1
- `use_cudagraphs=True` is silently ignored. HOT 1
- Distributed and Bucketing Performance Improvements HOT 1
- using size() twice in a row on same tensor causes interpreter out of sync error with thunder jit HOT 1
- Consider if functions like full_like and expand_as should be symbols (or not)
- max_pool2d:Shape propagation error for input dimensions used by resnet HOT 1
- transformer_engine: clear_collection doesn't clear the tensors saved by transformer_engine_ex ops for backward. HOT 1
- transformer_engine: Fails with Pythia-14m in distributed
- Benchmark: Running benchmark_litgpt with `transformerengine` leads to `nullcontext` not defined.
- uniform_like: The function outputs different values when the input tensor is the same but `requires_grad` is True/False.
- Add activation checkpointing to litGPT benchmarking script HOT 1
- utils.find_producer_symbols is too aggressive at collecting producer symbols not taking into account stop information HOT 1
- Add more nvFuser debug information HOT 2
- reenable apex backward / phantom grad tests without wrecking CI HOT 2
- Investigate GPU memory intense CI tests HOT 1
- Regression on thunder/benchmarks/targets.py
- CSE pass should work on symbols with keyword arguments
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