self.use_nested_tensor是一个实例变量,用于记录当前实例(可能是模型的一个组件)是否实际使用了嵌套张量。这个变量通常在模型或组件的初始化过程中根据配置和其他条件进行设置。 分析两者之间的关系,为何出现不一致: 不一致的原因可能在于enable_nested_tensor的配置没有在模型的初始化过程中被正确应用。例如,如果enable...
- func: _scaled_dot_product_cudnn_attention(Tensor query, Tensor key, Tensor value, float dropout_p=0.0, bool is_causal=False, bool return_debug_mask=False, *, float? scale=None) -> (Tensor output, Tensor logsumexp, Tensor cum_seq_q, Tensor cum_seq_k, SymInt max_q, SymInt max...
revert-56972-cinn_remove_nested_block revert-57019-move_tensor_writer_tell revert-56360-isl_stage revert-57005-refine_stride_flag revert-56925-check_inputs_grad_semantic revert-56545-revert-56366-fix_openssl_bug revert-56620-fix_new_ir_ocr_bug ...
skylion007/nested-tensor-matmul-reserve-2024-11-20 skylion007/remove-typeignore-2025-02-12 (pytorch/pytorch#146989) skylion007/ruff-FURB148-2024-08-19 skylion007/ruff-RUF025-2024-04-27 skylion007/ruff-apply-FURB188-2025-02-12 (pytorch/pytorch#146997) skylion007/ruff-apply-RUFF046-2025-02...
One interesting thing I found that is a nested loop function consume 96.7% CPU loading during the simulation. My experience told me that I should try to optimize the compiler option. Streamline Functions Usage NN Device Inference Performance Table Execution Time (instr) NN code s...
2)CPU:Intel(R) Xeon(R) CPU E5-2650 v3 @ 2.30GHz, EnableMKLDNN, SwitchIrOptim=true 4)系统环境:Linux version 2.6.32_1-17-0-0, x86_64 -预测信息 1)C++预测:v1.8.1-gcc82-mkl-avx-mkldnn_PD_BL version.txt: GIT COMMIT ID: ea1c05d0e61ddb1bd69b9f7fa82898a9c9859126 ...
Tensors and Dynamic neural networks in Python with strong GPU acceleration - Enable nested namespace check in clang-tidy (#118506) · apakbin/pytorch@4a01904
Tensors and Dynamic neural networks in Python with strong GPU acceleration - [cuDNN][SDPA] Remove `TORCH_CUDNN_SDPA_ENABLED=1`, enable cuDNN SDPA …· pytorch/pytorch@f845a7a
gtest-tmva-tmva-rtensor ‑ gtest-tmva-tmva-rtensor gtest-tmva-tmva-rtensor-iterator ‑ gtest-tmva-tmva-rtensor-iterator gtest-tmva-tmva-rtensor-utils ‑ gtest-tmva-tmva-rtensor-utils gtest-tree-dataframe-dataframe-cache ‑ gtest-tree-dataframe-dataframe-cache ...
const Tensor& self, int64_t level, int64_t batch_size, const c10::SymInt& batch_size, int64_t out_dim) { TORCH_CHECK( out_dim == 0 || !self.key_set().has(DispatchKey::BatchedNestedTensor), "Nested tensors can only be vmapped over dim=0, but got dim=", out_dim); if (!