Related Issues (20)
- Vmap batching rule support for torch.isin
- Import Error: cannot import name 'XNNPACKQuantizer' from 'torch.ao.quantization.quantizer'
- A trivial but annoying bug in random_split
- DISABLED test_quantization_doc_qat (__main__.TestQuantizationDocs) HOT 1
- DISABLED test_flash_attention_vs_math_ref_grads_batch_size_8_seq_len_q_2048_seq_len_k_2048_head_dim_64_is_causal_True_dropout_p_0_22_bfloat16_scale_l1_cuda_bfloat16 (__main__.TestSDPACudaOnlyCUDA) HOT 1
- [Prelu_backward]: x, grad_out or weight is scalar, get wrong result
- 2nd compile of deepcopy(model) fails on multiple ubuntu-pc (fatal error: Python.h: file not found)
- [Dynamo][TVM] TVM backend not work on macOS nor Linux aarch64
- optional memory leak with torch.jit.script on models with fft
- Stateless random numbers HOT 1
- Fake tensor support of distributed ops in FX graph tracing HOT 3
- PyTorch fails to build on ppc64le HOT 1
- Unable to record Memory consumption with `torch.cuda.memory._record_memory_history()` HOT 1
- AMP guards recompilation `dtype mismatch. expected Half, actual Float`
- Class name displayed incorrectly
- torch.compile Jamba: Scheduler Error in codegen for ComputedBuffer
- torch.compile with Custom tensor subclass doesn't inline the tensor subclass methods
- More economical use of FX nodes when generating symbolic shapes related manipulations HOT 3
- torch.compile Jamba: long compilation time with backend="eager" HOT 1
- Inlining nn modules and FSDP HOT 1
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