Comments (2)
Seems related to #65214
from pytorch.
Seems related to #65214
I feel like I've encountered the same problem, but its problem hasn't been resolved either.I want to know what are the criteria for judging this warning? Has an error occurred?
from pytorch.
Related Issues (20)
- DISABLED test_register_fsdp_forward_method (__main__.TestFullyShardCustomForwardMethod) HOT 1
- DISABLED test_register_fsdp_forward_method (__main__.TestFullyShardCustomForwardMethod) HOT 1
- DISABLED test_dtensor_op_db_inner_cpu_float32 (__main__.TestDTensorOpsCPU) HOT 1
- DISABLED test_vertical_pointwise_reduction_fusion_cuda (__main__.TestUnbackedSymintsCUDA) HOT 1
- LambdaLR has incorrect multiplicative behavior when using torch.tensor LR HOT 12
- TorchDynamo ONNX Export does not work as expected with masking (ScatterElements)
- [inductor][cpu]Background_Matting and pytorch_CycleGAN_and_pix2pix AMP multiple thread static/dynamic shape CPP/default wrapper performance regression HOT 1
- worse results by using the MPS backend, compared to the CPU HOT 2
- Compile with non-default mode + triton kernel fails HOT 1
- DISABLED test__int_mm_k_16_n_32_use_transpose_a_False_use_transpose_b_False_cuda (__main__.TestLinalgCUDA) HOT 1
- DISABLED test_non_contiguous_input_mm_plus_mm (__main__.TestMaxAutotune) HOT 2
- DISABLED test_dtensor_op_db_vstack_cpu_float32 (__main__.TestDTensorOpsCPU) HOT 2
- opcheck has dependency on expecttest, which is not a pytorch runtime dependency, leading to "module not found" error message
- running opcheck leads to `Fail to import hypothesis in common_utils, tests are not derandomized` print
- [docs] scaled_dot_product_attention is_causal description is misleading HOT 4
- Add warning messages to provide info about expected performance improvement using cuda for a specific model
- UserWarning:Plan failed with a cudnnException HOT 1
- [DCP] DCP does not support objects which are lazy initialized. HOT 3
- Bug: `torch.func.jacrev` fails with backend=`aot_eager` HOT 1
- UNSTABLE inductor / cuda12.1-py3.10-gcc9-sm86 / test (inductor_timm) HOT 1
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from pytorch.