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Add skip lists for LNL, BGM and MTL devices (#1187)
Add skip lists for LNL, BGM and MTL devices --------- Signed-off-by: Cheng, Penghui <[email protected]> Signed-off-by: Cheng <[email protected]>
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import os | ||
import pytest | ||
import sys | ||
from skip_list_common import skip_dict | ||
from skip_list_win import skip_dict as skip_dict_win | ||
from skip_list_win_bmg import skip_dict as skip_dict_win_bmg | ||
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IS_WINDOWS = sys.platform == "win32" | ||
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skip_list = skip_dict["test_ops_xpu.py"] | ||
if IS_WINDOWS: | ||
skip_list += skip_dict_win["test_ops_xpu.py"] + skip_dict_win_bmg["test_ops_xpu.py"] | ||
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skip_options = "not " + skip_list[0] | ||
for skip_case in skip_list[1:]: | ||
skip_option = " and not " + skip_case | ||
skip_options += skip_option | ||
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os.environ["PYTORCH_TEST_WITH_SLOW"]="1" | ||
test_command = ["-k", skip_options, "test_ops_xpu.py", "-v"] | ||
res = pytest.main(test_command) | ||
sys.exit(res) |
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import os | ||
import pytest | ||
import sys | ||
from skip_list_common import skip_dict | ||
from skip_list_win import skip_dict as skip_dict_win | ||
from skip_list_win_lnl import skip_dict as skip_dict_win_lnl | ||
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IS_WINDOWS = sys.platform == "win32" | ||
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skip_list = skip_dict["test_ops_xpu.py"] | ||
if IS_WINDOWS: | ||
skip_list += skip_dict_win["test_ops_xpu.py"] + skip_dict_win_lnl["test_ops_xpu.py"] | ||
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skip_options = "not " + skip_list[0] | ||
for skip_case in skip_list[1:]: | ||
skip_option = " and not " + skip_case | ||
skip_options += skip_option | ||
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os.environ["PYTORCH_TEST_WITH_SLOW"]="1" | ||
test_command = ["-k", skip_options, "test_ops_xpu.py", "-v"] | ||
res = pytest.main(test_command) | ||
sys.exit(res) |
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import os | ||
import pytest | ||
import sys | ||
from skip_list_common import skip_dict | ||
from skip_list_win import skip_dict as skip_dict_win | ||
from skip_list_win_mtl import skip_dict as skip_dict_win_mtl | ||
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IS_WINDOWS = sys.platform == "win32" | ||
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skip_list = skip_dict["test_ops_xpu.py"] | ||
if IS_WINDOWS: | ||
skip_list += skip_dict_win["test_ops_xpu.py"] + skip_dict_win_mtl["test_ops_xpu.py"] | ||
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skip_options = "not " + skip_list[0] | ||
for skip_case in skip_list[1:]: | ||
skip_option = " and not " + skip_case | ||
skip_options += skip_option | ||
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os.environ["PYTORCH_TEST_WITH_SLOW"]="1" | ||
test_command = ["-k", skip_options, "test_ops_xpu.py", "-v"] | ||
res = pytest.main(test_command) | ||
sys.exit(res) |
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skip_dict = { | ||
"test_ops_xpu.py": ( | ||
# https://github.com/intel/torch-xpu-ops/issues/1173 | ||
# Fatal Python error: Illegal instruction | ||
"test_compare_cpu_grid_sampler_2d_xpu_float64", | ||
"test_compare_cpu_cosh_xpu_complex64", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_bfloat16", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_float16", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_float32", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_float64", | ||
"test_compare_cpu_square_xpu_complex128", | ||
), | ||
} |
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skip_dict = { | ||
"test_ops_xpu.py": ( | ||
# https://github.com/intel/torch-xpu-ops/issues/1173 | ||
# Fatal Python error: Illegal instruction | ||
"test_compare_cpu_grid_sampler_2d_xpu_float64", | ||
"test_compare_cpu_cosh_xpu_complex64", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_bfloat16", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_float16", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_float32", | ||
"test_compare_cpu_nn_functional_softshrink_xpu_float64", | ||
"test_compare_cpu_square_xpu_complex128", | ||
), | ||
} |
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skip_dict = { | ||
# failed on MTL windows, skip first for Preci | ||
"test_ops_xpu.py": ( | ||
"test_compare_cpu_sqrt_xpu_complex64", | ||
"test_backward_nn_functional_adaptive_avg_pool2d_xpu_float32", | ||
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"test_compare_cpu_cosh_xpu_complex128", | ||
"test_compare_cpu_frexp_xpu_bfloat16", | ||
"test_compare_cpu_frexp_xpu_float16", | ||
"test_compare_cpu_frexp_xpu_float32", | ||
"test_compare_cpu_frexp_xpu_float64", | ||
"test_compare_cpu_max_pool2d_with_indices_backward_xpu_bfloat16", | ||
"test_compare_cpu_max_pool2d_with_indices_backward_xpu_float16", | ||
"test_compare_cpu_max_pool2d_with_indices_backward_xpu_float32", | ||
"test_compare_cpu_max_pool2d_with_indices_backward_xpu_float64", | ||
"test_compare_cpu_nn_functional_avg_pool2d_xpu_bfloat16", | ||
"test_compare_cpu_nn_functional_avg_pool2d_xpu_float32", | ||
"test_compare_cpu_nn_functional_avg_pool3d_xpu_float32", | ||
), | ||
} |
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import os | ||
import sys | ||
from skip_list_common import skip_dict | ||
from skip_list_win import skip_dict as skip_dict_win | ||
from skip_list_win_bmg import skip_dict as skip_dict_win_bmg | ||
from xpu_test_utils import launch_test | ||
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res = 0 | ||
IS_WINDOWS = sys.platform == "win32" | ||
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for key in skip_dict: | ||
skip_list = skip_dict[key] | ||
if IS_WINDOWS and key in skip_dict_win: | ||
skip_list += skip_dict_win[key] | ||
if IS_WINDOWS and key in skip_dict_win_bmg: | ||
skip_list += skip_dict_win_bmg[key] | ||
res += launch_test(key, skip_list) | ||
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if os.name == "nt": | ||
sys.exit(res) | ||
else: | ||
exit_code = os.WEXITSTATUS(res) | ||
sys.exit(exit_code) |
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import os | ||
import sys | ||
from skip_list_common import skip_dict | ||
from skip_list_win import skip_dict as skip_dict_win | ||
from skip_list_win_lnl import skip_dict as skip_dict_win_lnl | ||
from xpu_test_utils import launch_test | ||
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res = 0 | ||
IS_WINDOWS = sys.platform == "win32" | ||
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for key in skip_dict: | ||
skip_list = skip_dict[key] | ||
if IS_WINDOWS and key in skip_dict_win: | ||
skip_list += skip_dict_win[key] | ||
if IS_WINDOWS and key in skip_dict_win_lnl: | ||
skip_list += skip_dict_win_lnl[key] | ||
res += launch_test(key, skip_list) | ||
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if os.name == "nt": | ||
sys.exit(res) | ||
else: | ||
exit_code = os.WEXITSTATUS(res) | ||
sys.exit(exit_code) |
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skip_dict = { | ||
# tensor(0.-0.j, device='xpu:0', dtype=torch.complex32) tensor(nan+nanj, device='xpu:0', dtype=torch.complex32) (1.5707964+0j) | ||
"test_unary_ufuncs_xpu.pyy": ( | ||
"test_reference_numerics_small_acos_xpu_complex32", | ||
"test_reference_numerics_small_asin_xpu_complex32", | ||
"test_reference_numerics_small_asinh_xpu_complex32", | ||
"test_reference_numerics_small_atan_xpu_complex32", | ||
"test_reference_numerics_small_atanh_xpu_complex32", | ||
# Need to check compiler std::sin() on inf+infj | ||
"test_reference_numerics_extremal__refs_sin_xpu_complex128", | ||
"test_reference_numerics_extremal__refs_sin_xpu_complex64", | ||
"test_reference_numerics_extremal_nn_functional_tanhshrink_xpu_complex128", | ||
"test_reference_numerics_extremal_nn_functional_tanhshrink_xpu_complex64", | ||
"test_reference_numerics_extremal_sin_xpu_complex128", | ||
"test_reference_numerics_extremal_sin_xpu_complex64", | ||
"test_reference_numerics_extremal_sinh_xpu_complex128", | ||
"test_reference_numerics_extremal_sinh_xpu_complex64", | ||
"test_reference_numerics_large__refs_sin_xpu_complex32", | ||
"test_reference_numerics_large_sin_xpu_complex32", | ||
# Known issue of exp accuracy | ||
# tensor(13437.7000-501.j, device='xpu:0', dtype=torch.complex128) tensor(inf+infj, device='xpu:0', dtype=torch.complex128) (-inf+infj) | ||
"test_reference_numerics_large__refs_exp_xpu_complex128", | ||
"test_reference_numerics_large_exp_xpu_complex128", | ||
"test_reference_numerics_small_exp_xpu_complex32", | ||
":test_reference_numerics_normal_special_i1_xpu_float32", | ||
"test_reference_numerics_normal_sigmoid_xpu_complex32", | ||
"test_reference_numerics_small_sigmoid_xpu_complex32", | ||
), | ||
# https://github.com/intel/torch-xpu-ops/issues/1171 | ||
# AssertionError: 'Assertion maxind >= 0 && maxind < outputImageSize failed' not found in '\nAssertHandler::printMessage\n' : The expected error was not found | ||
"nn\test_pooling_xpu.py": ( | ||
"test_MaxUnpool_index_errors_case1_xpu", | ||
"test_MaxUnpool_index_errors_case2_xpu", | ||
"test_MaxUnpool_index_errors_case4_xpu", | ||
"test_MaxUnpool_index_errors_case6_xpu", | ||
"test_MaxUnpool_index_errors_case7_xpu", | ||
"test_MaxUnpool_index_errors_case9_xpu", | ||
), | ||
} |
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skip_dict = { | ||
# tensor(0.-0.j, device='xpu:0', dtype=torch.complex32) tensor(nan+nanj, device='xpu:0', dtype=torch.complex32) (1.5707964+0j) | ||
"test_unary_ufuncs_xpu.pyy": ( | ||
"test_reference_numerics_small_acos_xpu_complex32", | ||
"test_reference_numerics_small_asin_xpu_complex32", | ||
"test_reference_numerics_small_asinh_xpu_complex32", | ||
"test_reference_numerics_small_atan_xpu_complex32", | ||
"test_reference_numerics_small_atanh_xpu_complex32", | ||
# Need to check compiler std::sin() on inf+infj | ||
"test_reference_numerics_extremal__refs_sin_xpu_complex128", | ||
"test_reference_numerics_extremal__refs_sin_xpu_complex64", | ||
"test_reference_numerics_extremal_nn_functional_tanhshrink_xpu_complex128", | ||
"test_reference_numerics_extremal_nn_functional_tanhshrink_xpu_complex64", | ||
"test_reference_numerics_extremal_sin_xpu_complex128", | ||
"test_reference_numerics_extremal_sin_xpu_complex64", | ||
"test_reference_numerics_extremal_sinh_xpu_complex128", | ||
"test_reference_numerics_extremal_sinh_xpu_complex64", | ||
"test_reference_numerics_large__refs_sin_xpu_complex32", | ||
"test_reference_numerics_large_sin_xpu_complex32", | ||
# Known issue of exp accuracy | ||
# tensor(13437.7000-501.j, device='xpu:0', dtype=torch.complex128) tensor(inf+infj, device='xpu:0', dtype=torch.complex128) (-inf+infj) | ||
"test_reference_numerics_large__refs_exp_xpu_complex128", | ||
"test_reference_numerics_large_exp_xpu_complex128", | ||
"test_reference_numerics_small_exp_xpu_complex32", | ||
":test_reference_numerics_normal_special_i1_xpu_float32", | ||
"test_reference_numerics_normal_sigmoid_xpu_complex32", | ||
), | ||
# https://github.com/intel/torch-xpu-ops/issues/1171 | ||
# AssertionError: 'Assertion maxind >= 0 && maxind < outputImageSize failed' not found in '\nAssertHandler::printMessage\n' : The expected error was not found | ||
"nn\test_pooling_xpu.py": ( | ||
"test_MaxUnpool_index_errors_case1_xpu", | ||
"test_MaxUnpool_index_errors_case2_xpu", | ||
"test_MaxUnpool_index_errors_case4_xpu", | ||
"test_MaxUnpool_index_errors_case6_xpu", | ||
"test_MaxUnpool_index_errors_case7_xpu", | ||
"test_MaxUnpool_index_errors_case9_xpu", | ||
), | ||
} |