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refine skiplist to add issue id for some skipped cases. #2067

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refine skiplist to add issue id for some skipped cases. #2067

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7 changes: 2 additions & 5 deletions test/xpu/skip_list_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,7 @@
# This case is marked as skip but XPU failed. However, CUDA and XPU throw the same runtime error.
"test_out_histc_xpu_float32",
# Data type is not supported in oneDNN!
# https://github.com/intel/torch-xpu-ops/issues/1896
"test_dtypes_nn_functional_conv1d_xpu",
"test_dtypes_nn_functional_conv2d_xpu",
"test_dtypes_nn_functional_conv3d_xpu",
Expand Down Expand Up @@ -99,7 +100,6 @@
# unexpected success because of cpu fallback
# Linalg OPs not supported
"test_out_triangular_solve_xpu_float32",
# Newly added:
# Cuda skipped it
"test_non_standard_bool_values_sort_xpu_bool", # The implementation aligns with CUDA, RuntimeError: "sort" not implemented for 'Bool'.
# Cuda XFAIL (stock pytorch commit: e7cf7d0)
Expand Down Expand Up @@ -1414,8 +1414,7 @@
"test_gemm_bias_tunableop_xpu_bfloat16",
"test_scaled_gemm_tunableop_xpu_float8_e4m3fnuz",
"test_scaled_gemm_tunableop_xpu_float8_e5m2fnuz",
# CUDA bias cases added in latest PyTorch
# AttributeError: module 'torch._C' has no attribute '_cuda_tunableop_enable'
# https://github.com/intel/torch-xpu-ops/issues/2066
"test_matmul_check_entries_tunableop_xpu_float16",
"test_minimum_tuning_iteration_tunableop_xpu_float16",
"test_validator_tunableop_rocm_xpu_float32",
Expand Down Expand Up @@ -2968,8 +2967,6 @@
"test_meta_outplace_vdot_xpu_complex",
# Unexpected success:
"test_dispatch_symbolic_meta_outplace_all_strides_narrow_copy_xpu_float32",
# New added case in 2.7
"test_nonzero_xpu",
# https://github.com/intel/torch-xpu-ops/issues/1569
# RuntimeError: output 0: meta disagrees with real impl
"test_dispatch_meta_outplace_norm_fro_xpu_bfloat16",
Expand Down