Comments (2)
@k223kim wants to work on this. Thank you!
from lightning-thunder.
Hey Team! I will be working on this issue. Thanks!
from lightning-thunder.
Related Issues (20)
- Updating Module's buffer leads to crash in thunder.jit
- ThunderModule - `state_dict` followed by `load_original_state_dict` returns `state_dict` of the original module. HOT 1
- functionalization fails to replace in-place operands with new tensors
- When comparing Thunder Torch Executor to Torch Eager, the ResNet18 gradients are not close for FP32. HOT 2
- Desired inplace idioms (add yours here) HOT 2
- TransformerEngine's FP8 LayerNorm support HOT 5
- "nvFuser" illegal memory access with falcon-7b model HOT 3
- TypeError: unwrap_if_dead() incompatible args in NeVA model HOT 2
- torch._dynamo.exc.Unsupported: call_method UserDefinedObjectVariable(set) __contains__ [UserDefinedObjectVariable()] {} HOT 3
- dolly-v2-3b with thunder_inductor_cat_cudnn fails with KeyError: \'t5905\' HOT 6
- backwards of autograd functions
- jit+grad: had an unexpected type <class TensorProxy>. Supported types are <class TensorProxy> HOT 3
- CI failure in thunder/tests/test_jit_general.py::test_litgpt_variants_kvcache with PyTorch 2.5dev
- RuntimeError: detect_exception_in_thread_pool.load() HOT 1
- NotImplementedError: aten::nonzero: attempted to run this operator with Meta tensors HOT 2
- maximum recursion depth in NeVA HOT 5
- thunder.examine.memory_calculation.get_alloc_memory overestimates the peak allocated memory on Colab HOT 2
- Dtype mismatch in linear layer HOT 1
- Support missing interpolate() options
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