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Arc: Add cases skip list for extended cases (#844)
Add cases skip list for ARC device in extended folder. --------- Signed-off-by: Cheng, Penghui <penghui.cheng@intel.com>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,19 @@ | ||
| import os | ||
| import sys | ||
| from skip_list_common import skip_dict | ||
| from skip_list_arc import skip_dict as skip_dict_specifical | ||
|
|
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| skip_list = skip_dict["test_ops_xpu.py"] + skip_dict_specifical["test_ops_xpu.py"] | ||
|
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| skip_options = " -k 'not " + skip_list[0] | ||
| for skip_case in skip_list[1:]: | ||
| skip_option = " and not " + skip_case | ||
| skip_options += skip_option | ||
| skip_options += "'" | ||
|
|
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| test_command = "PYTORCH_TEST_WITH_SLOW=1 pytest -v test_ops_xpu.py" | ||
| test_command += skip_options | ||
|
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||
| res = os.system(test_command) | ||
| exit_code = os.WEXITSTATUS(res) | ||
| sys.exit(exit_code) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,11 @@ | ||
| skip_dict = { | ||
| "test_ops_xpu.py": ( | ||
| # RuntimeError: Required aspect fp64 is not supported on the device | ||
| # https://github.com/intel/torch-xpu-ops/issues/628 | ||
| "test_compare_cpu_bincount_xpu_int16", | ||
| "test_compare_cpu_bincount_xpu_int32", | ||
| "test_compare_cpu_bincount_xpu_int64", | ||
| "test_compare_cpu_bincount_xpu_int8", | ||
| "test_compare_cpu_bincount_xpu_uint8", | ||
| ), | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,150 @@ | ||
| skip_dict = { | ||
| "test_ops_xpu.py": ( | ||
| # Calculation error between XPU implementation and CPU implementation, | ||
| # 1. Compiler optimization causes failing to promote data type to higher precision. | ||
| # 2. Accumulate error is amplified by some operations in some extreme cases. (std::exp(extreme_large_num)) | ||
| # 3. Accumulate error is amplified by a large number of accumalate operations. | ||
| # 4. Accumulate error is different on different implementations due to different accumulation order. | ||
| # a. Different kernel implementations. | ||
| # b. Different std functions. (std::log, std::tanh, std::exp) | ||
| # 5. The result of division between two same float values is not 1. | ||
| # 6. std functions get different results when input is nan or inf between GCC and SYCL. | ||
| "test_compare_cpu_cumsum_xpu_bfloat16", | ||
| "test_compare_cpu_cumsum_xpu_float16", | ||
| "test_compare_cpu_log_xpu_complex64", | ||
| "test_compare_cpu_log10_xpu_complex64", | ||
| "test_compare_cpu_log1p_xpu_complex64", | ||
| "test_compare_cpu_log2_xpu_complex64", | ||
| "test_compare_cpu_log2_xpu_complex128", | ||
| "test_compare_cpu_mul_xpu_complex64", | ||
| "test_compare_cpu_pow_xpu_complex128", | ||
| "test_compare_cpu_pow_xpu_complex64", | ||
| "test_compare_cpu_tan_xpu_complex128", | ||
| "test_compare_cpu_tan_xpu_complex64", | ||
| "test_compare_cpu_tanh_xpu_complex128", | ||
| "test_compare_cpu_tanh_xpu_complex64", | ||
| "test_compare_cpu_rsqrt_xpu_bfloat16", | ||
| "test_compare_cpu_pow_xpu_bfloat16", | ||
| # cuda has the same issue on this case | ||
| "test_compare_cpu__refs_rsub_xpu_bfloat16", | ||
| "test_compare_cpu_add_xpu_bfloat16", | ||
| "test_compare_cpu_sub_xpu_bfloat16", | ||
| "test_compare_cpu_acos_xpu_complex128", | ||
| "test_compare_cpu_acos_xpu_complex64", | ||
| "test_compare_cpu_acosh_xpu_complex64", | ||
| "test_compare_cpu_cross_xpu_float16", | ||
| "test_compare_cpu_floor_divide_xpu_bfloat16", | ||
| "test_compare_cpu_floor_divide_xpu_float16", | ||
| "test_compare_cpu_polygamma_polygamma_n_0_xpu_bfloat16", | ||
| "test_compare_cpu_exp_xpu_bfloat16", | ||
| "test_compare_cpu_exp_xpu_complex128", | ||
| "test_compare_cpu_exp_xpu_complex64", | ||
| "test_compare_cpu_acosh_xpu_complex64", | ||
| "test_compare_cpu_asin_xpu_complex128", | ||
| "test_compare_cpu_asin_xpu_complex64", | ||
| "test_compare_cpu_asinh_xpu_complex128", | ||
| "test_compare_cpu_asinh_xpu_complex64", | ||
| "test_compare_cpu_atan_xpu_complex128", | ||
| "test_compare_cpu_atan_xpu_complex64", | ||
| "test_compare_cpu_exp2_xpu_complex128", | ||
| "test_compare_cpu_exp2_xpu_complex64", | ||
| "test_compare_cpu_nextafter_xpu_bfloat16", | ||
| # CUDA does not support the data type either | ||
| "test_non_standard_bool_values_native_dropout_backward_xpu_bool", | ||
| # Need FP64 golden ref for more accurate comparison | ||
| "test_compare_cpu_log_softmax_xpu_bfloat16", | ||
| # TestCompositeCompliance | ||
| # CPU fallback fails | ||
| # Require implementing aten::embedding_renorm_ | ||
| "test_view_replay_nn_functional_embedding_xpu_float32", | ||
| # TestCompositeCompliance::test_cow_input | ||
| # XPU Tensor fails in copy-on-write cases | ||
| # AssertionError: False is not true : Keyword argument 'output grad 0' during backward call unexpectedly materializes. Either set `supports_cow_input_no_materialize_backward=False` in this operation's OpInfo, add the arg to the OpInfo's `allow_cow_input_materialize_backward` list, or change the implementation to avoid materialization. | ||
| # https://github.com/intel/torch-xpu-ops/issues/281 | ||
| "test_cow_input", | ||
| # XPU implementation is correct. | ||
| # std::exp{-inf, nan}, the result is (±0,±0) (signs are unspecified) | ||
| # std::exp{-inf, inf}, the result is (±0,±0) (signs are unspecified) | ||
| # CPU implementation gets NaN in the cases. | ||
| # https://en.cppreference.com/w/cpp/numeric/complex/exp | ||
| "test_compare_cpu_sigmoid_xpu_complex64", | ||
| "test_compare_cpu_sigmoid_xpu_complex128", | ||
| # Special handle (different calculation order) in CPU reference impl. | ||
| # https://github.com/pytorch/pytorch/blob/c97e3ebb96d7457075b019b94411e8c2d058e68b/aten/src/ATen/native/EmbeddingBag.cpp#L300 | ||
| "test_compare_cpu_nn_functional_embedding_bag_xpu_bfloat16", | ||
| "test_compare_cpu_nn_functional_embedding_bag_xpu_float16", | ||
| # Not implemented operators, aten::embedding_renorm_. | ||
| # To retrieve cases when the operators are supported. | ||
| # https://github.com/intel/torch-xpu-ops/issues/380 | ||
| "test_compare_cpu_nn_functional_embedding_bag_xpu_float32", | ||
| "test_compare_cpu_nn_functional_embedding_bag_xpu_float64", | ||
| "test_view_replay_nn_functional_embedding_bag_xpu_float32", | ||
| # Double and complex datatype matmul is not supported in oneDNN | ||
| "test_compare_cpu_cdist_xpu_float64", | ||
| # bilinear interpolate includes large calculation steps, accuracy reduces in half-precision | ||
| # Not in CUDA test scope too | ||
| "test_compare_cpu_nn_functional_upsample_bilinear_xpu_bfloat16", | ||
| "test_compare_cpu_nn_functional_upsample_bilinear_xpu_float16", | ||
| # CPU result is not golden reference | ||
| "test_compare_cpu_nn_functional_group_norm_xpu_bfloat16", | ||
| "test_compare_cpu_nn_functional_group_norm_xpu_float16", | ||
| "test_compare_cpu_nn_functional_nll_loss_xpu_bfloat16", | ||
| "test_compare_cpu_nn_functional_nll_loss_xpu_float16", | ||
| "test_compare_cpu_nn_functional_batch_norm_xpu_bfloat16", | ||
| "test_compare_cpu__batch_norm_with_update_xpu_bfloat16", | ||
| "test_compare_cpu__batch_norm_with_update_xpu_float16", | ||
| "test_compare_cpu_nn_functional_huber_loss_xpu_bfloat16", | ||
| "test_compare_cpu_nansum_xpu_bfloat16", | ||
| "test_compare_cpu_nanmean_xpu_bfloat16", | ||
| # Align with CUDA impl by using accumulate type. But CPU doesn't use. | ||
| # When XPU uses original data type, the case passes. | ||
| "test_compare_cpu_logit_xpu_bfloat16", | ||
| # precison error | ||
| # Mismatched elements: 1 / 24 (4.2%) | ||
| # Greatest absolute difference: 0.03125 at index (0, 1, 0, 1) (up to 0.001 allowed) | ||
| # Greatest relative difference: 0.0048828125 at index (0, 1, 0, 1) (up to 0.001 allowed) | ||
| "test_compare_cpu_nn_functional_interpolate_bilinear_xpu_bfloat16", | ||
| # RuntimeError: "compute_index_ranges_weights" not implemented for 'Half' | ||
| "test_compare_cpu_nn_functional_interpolate_bilinear_xpu_float16", | ||
| # AssertionError: False is not true : Argument 0 during forward call unexpectedly materializes. Either set `supports_cow_input_no_materialize_forward=False... | ||
| "test_cow_input_nn_functional_interpolate_bilinear_xpu_float32", | ||
| "test_cow_input_nn_functional_interpolate_linear_xpu_float32", | ||
| "test_cow_input_nn_functional_interpolate_trilinear_xpu_float32", | ||
| #The results of XPU and CUDA are consistent, but the results of CPU and CUDA are inconsistent | ||
| "test_compare_cpu_nn_functional_interpolate_linear_xpu_bfloat16", | ||
| "test_compare_cpu_nn_functional_interpolate_linear_xpu_float16", | ||
| # bicubic interpolate includes large calculation steps, accuracy reduces in half-precision | ||
| # Not in CUDA test scope too | ||
| "test_compare_cpu_nn_functional_interpolate_bicubic_xpu_bfloat16", | ||
| "test_compare_cpu_nn_functional_interpolate_bicubic_xpu_float16", | ||
| # Not all operators are implemented for XPU tested in the case. | ||
| # Retrieve it once the operator is implemented. | ||
| # Error: The operator 'aten::glu_jvp' is not currently implemented for the XPU device. | ||
| "test_forward_ad_nn_functional_glu_xpu_float32", | ||
| # Precision error. | ||
| # Mismatched elements: 1 / 812 (0.1%) | ||
| # Greatest absolute difference: 0.03125 at index (610,) (up to 0.001 allowed) | ||
| # Greatest relative difference: 0.00396728515625 at index (610,) (up to 0.001 allowed) | ||
| "test_compare_cpu_hypot_xpu_bfloat16", | ||
| # RuntimeError: Expected both inputs to be Half, Float or Double tensors but got BFloat16 and BFloat16. | ||
| # Polar's backward is calculated using complex(), which does not support bfloat16. CUDA fails with same error. | ||
| "test_compare_cpu_polar_xpu_bfloat16", | ||
| # Precision error. | ||
| # Mismatched elements: 1 / 25 (4.0%) | ||
| # Greatest absolute difference: 0.00146484375 at index (0, 0) (up to 0.001 allowed) | ||
| # Greatest relative difference: 0.0163116455078125 at index (0, 0) (up to 0.001 allowed) | ||
| "test_compare_cpu_sub_xpu_float16", | ||
| # different results for value index due to unstable sort. | ||
| # XPU and CUDA have the same result. | ||
| "test_compare_cpu_median_xpu_int16", | ||
| "test_compare_cpu_median_xpu_int32", | ||
| "test_compare_cpu_median_xpu_int64", | ||
| "test_compare_cpu_median_xpu_int8", | ||
| "test_compare_cpu_median_xpu_uint8", | ||
| "test_compare_cpu_nanmedian_xpu_int16", | ||
| "test_compare_cpu_nanmedian_xpu_int32", | ||
| "test_compare_cpu_nanmedian_xpu_int64", | ||
| "test_compare_cpu_nanmedian_xpu_int8", | ||
| "test_compare_cpu_nanmedian_xpu_uint8", | ||
| ), | ||
| } |