array-api-compat/torch-xfails.txt at main · data-apis/array-api-compat · GitHub

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# Note: see array_api_compat/torch/_aliases.py for links to corresponding
# pytorch issues

# We cannot wrap the array object

# Indexing does not support negative step
array_api_tests/test_array_object.py::test_getitem
array_api_tests/test_array_object.py::test_setitem
# Masking doesn't support 0 dimensions in the mask
array_api_tests/test_array_object.py::test_getitem_masking

# Overflow error from large inputs
array_api_tests/test_creation_functions.py::test_arange
# pytorch linspace bug (should be fixed in torch 2.0)

# We cannot wrap the tensor object
array_api_tests/test_has_names.py::test_has_names[array_method-__array_namespace__]
array_api_tests/test_has_names.py::test_has_names[array_method-to_device]

# We cannot wrap the tensor object
array_api_tests/test_operators_and_elementwise_functions.py::test_add[__add__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_bitwise_and[__and__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_bitwise_left_shift[__lshift__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_bitwise_or[__or__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_bitwise_right_shift[__rshift__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_bitwise_right_shift[__irshift__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_bitwise_xor[__xor__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_divide[__truediv__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_equal[__eq__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_not_equal[__ne__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_floor_divide[__floordiv__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_floor_divide[__floordiv__(x, s)]
array_api_tests/test_operators_and_elementwise_functions.py::test_floor_divide[__ifloordiv__(x, s)]
array_api_tests/test_operators_and_elementwise_functions.py::test_floor_divide[__ifloordiv__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_floor_divide[floor_divide(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_greater[__gt__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_greater_equal[__ge__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_less[__lt__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_less_equal[__le__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_multiply[__mul__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_pow[__pow__(x1, x2)]
# This test is skipped instead of xfailed because it causes core dumps on CI
# array_api_tests/test_operators_and_elementwise_functions.py::test_remainder[__mod__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_remainder[__imod__(x1, x2)]
array_api_tests/test_operators_and_elementwise_functions.py::test_subtract[__sub__(x1, x2)]

# inverse trig functions are too inaccurate on CPU
array_api_tests/test_operators_and_elementwise_functions.py::test_acos
array_api_tests/test_operators_and_elementwise_functions.py::test_atan
array_api_tests/test_operators_and_elementwise_functions.py::test_asin

# Torch bug for remainder in some cases with large values
array_api_tests/test_operators_and_elementwise_functions.py::test_remainder[remainder(x1, x2)]

# unique_all cannot be implemented because torch's unique does not support
# returning indices
array_api_tests/test_set_functions.py::test_unique_all
# unique_inverse incorrectly counts nan values
# (https://github.com/pytorch/pytorch/issues/94106)
array_api_tests/test_set_functions.py::test_unique_inverse


# We cannot add attributes to the tensor object
array_api_tests/test_signatures.py::test_array_method_signature[__array_namespace__]
array_api_tests/test_signatures.py::test_array_method_signature[to_device]


# We do not attempt to work around special-case differences (most are on
# tensor methods which we couldn't fix anyway).
array_api_tests/test_special_cases.py::test_binary[__floordiv__(isfinite(x1_i) and x1_i < 0 and x2_i is +infinity) -> -0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(isfinite(x1_i) and x1_i < 0 and x2_i is -infinity) -> +0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(isfinite(x1_i) and x1_i > 0 and x2_i is +infinity) -> +0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(isfinite(x1_i) and x1_i > 0 and x2_i is -infinity) -> -0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i < 0 and x2_i is +0) -> -infinity]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i < 0 and x2_i is -0) -> +infinity]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i > 0 and x2_i is +0) -> +infinity]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i > 0 and x2_i is -0) -> -infinity]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is +0 and x2_i < 0) -> -0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is +0 and x2_i > 0) -> +0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is +infinity and isfinite(x2_i) and x2_i < 0) -> -infinity]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is +infinity and isfinite(x2_i) and x2_i > 0) -> +infinity]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is -0 and x2_i < 0) -> +0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is -0 and x2_i > 0) -> -0]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is -infinity and isfinite(x2_i) and x2_i < 0) -> +infinity]
array_api_tests/test_special_cases.py::test_binary[__floordiv__(x1_i is -infinity and isfinite(x2_i) and x2_i > 0) -> -infinity]
array_api_tests/test_special_cases.py::test_binary[__mod__(isfinite(x1_i) and x1_i < 0 and x2_i is +infinity) -> x2_i]
array_api_tests/test_special_cases.py::test_binary[__mod__(isfinite(x1_i) and x1_i < 0 and x2_i is -infinity) -> x1_i]
array_api_tests/test_special_cases.py::test_binary[__mod__(isfinite(x1_i) and x1_i > 0 and x2_i is +infinity) -> x1_i]
array_api_tests/test_special_cases.py::test_binary[__mod__(isfinite(x1_i) and x1_i > 0 and x2_i is -infinity) -> x2_i]
array_api_tests/test_special_cases.py::test_binary[__mod__(x1_i is +0 and x2_i < 0) -> -0]
array_api_tests/test_special_cases.py::test_binary[__mod__(x1_i is +0 and x2_i > 0) -> +0]
array_api_tests/test_special_cases.py::test_binary[__mod__(x1_i is -0 and x2_i < 0) -> -0]
array_api_tests/test_special_cases.py::test_binary[__mod__(x1_i is -0 and x2_i > 0) -> +0]
array_api_tests/test_special_cases.py::test_binary[floor_divide(isfinite(x1_i) and x1_i < 0 and x2_i is +infinity) -> -0]
array_api_tests/test_special_cases.py::test_binary[floor_divide(isfinite(x1_i) and x1_i > 0 and x2_i is -infinity) -> -0]
array_api_tests/test_special_cases.py::test_binary[floor_divide(x1_i is +infinity and isfinite(x2_i) and x2_i < 0) -> -infinity]
array_api_tests/test_special_cases.py::test_binary[floor_divide(x1_i is +infinity and isfinite(x2_i) and x2_i > 0) -> +infinity]
array_api_tests/test_special_cases.py::test_binary[floor_divide(x1_i is -infinity and isfinite(x2_i) and x2_i < 0) -> +infinity]
array_api_tests/test_special_cases.py::test_binary[floor_divide(x1_i is -infinity and isfinite(x2_i) and x2_i > 0) -> -infinity]
array_api_tests/test_special_cases.py::test_binary[remainder(x1_i is +0 and x2_i < 0) -> -0]
array_api_tests/test_special_cases.py::test_binary[remainder(x1_i is -0 and x2_i > 0) -> +0]
array_api_tests/test_special_cases.py::test_iop[__ifloordiv__(isfinite(x1_i) and x1_i < 0 and x2_i is +infinity) -> -0]
array_api_tests/test_special_cases.py::test_iop[__ifloordiv__(isfinite(x1_i) and x1_i > 0 and x2_i is -infinity) -> -0]
array_api_tests/test_special_cases.py::test_iop[__ifloordiv__(x1_i is +infinity and isfinite(x2_i) and x2_i < 0) -> -infinity]
array_api_tests/test_special_cases.py::test_iop[__ifloordiv__(x1_i is +infinity and isfinite(x2_i) and x2_i > 0) -> +infinity]
array_api_tests/test_special_cases.py::test_iop[__ifloordiv__(x1_i is -infinity and isfinite(x2_i) and x2_i < 0) -> +infinity]
array_api_tests/test_special_cases.py::test_iop[__ifloordiv__(x1_i is -infinity and isfinite(x2_i) and x2_i > 0) -> -infinity]
array_api_tests/test_special_cases.py::test_iop[__imod__(x1_i is +0 and x2_i < 0) -> -0]
array_api_tests/test_special_cases.py::test_iop[__imod__(x1_i is -0 and x2_i > 0) -> +0]

# complex cases
array_api_tests/test_special_cases.py::test_unary[acos((real(x_i) is +0 or real(x_i) == -0) and imag(x_i) is +0) -> \u03c0/2 - 0j]
array_api_tests/test_special_cases.py::test_unary[expm1((real(x_i) is +0 or real(x_i) == -0) and imag(x_i) is +0) -> 0 + 0j]
array_api_tests/test_special_cases.py::test_unary[expm1(real(x_i) is +infinity and imag(x_i) is +0) -> +infinity + 0j]
array_api_tests/test_special_cases.py::test_unary[expm1(real(x_i) is -infinity and imag(x_i) is +infinity) -> -1 + 0j]
array_api_tests/test_special_cases.py::test_unary[expm1(real(x_i) is +infinity and imag(x_i) is +infinity) -> infinity + NaN j]
array_api_tests/test_special_cases.py::test_unary[expm1(real(x_i) is -infinity and imag(x_i) is NaN) -> -1 + 0j]
array_api_tests/test_special_cases.py::test_unary[expm1(real(x_i) is +infinity and imag(x_i) is NaN) -> infinity + NaN j]
array_api_tests/test_special_cases.py::test_unary[expm1(real(x_i) is NaN and imag(x_i) is +0) -> NaN + 0j]
array_api_tests/test_special_cases.py::test_unary[log1p(isfinite(real(x_i)) and imag(x_i) is +infinity) -> +infinity + \u03c0j/2]
array_api_tests/test_special_cases.py::test_unary[log1p((real(x_i) is +infinity or real(x_i) == -infinity) and imag(x_i) is NaN) -> +infinity + NaN j]
array_api_tests/test_special_cases.py::test_unary[log1p(real(x_i) is NaN and imag(x_i) is +infinity) -> +infinity + NaN j]
array_api_tests/test_special_cases.py::test_unary[sqrt(real(x_i) is +infinity and isfinite(imag(x_i)) and imag(x_i) > 0) -> +0 + infinity j]
array_api_tests/test_special_cases.py::test_unary[tanh(real(x_i) is +infinity and isfinite(imag(x_i)) and imag(x_i) > 0) -> 1 + 0j]

# Float correction is not supported by pytorch
# (https://github.com/data-apis/array-api-tests/issues/168)
array_api_tests/test_statistical_functions.py::test_std
array_api_tests/test_statistical_functions.py::test_var


# These functions do not yet support complex numbers
array_api_tests/test_set_functions.py::test_unique_counts
array_api_tests/test_set_functions.py::test_unique_values

# finfo/iinfo.dtype is a string instead of a dtype
array_api_tests/test_data_type_functions.py::test_finfo_dtype
array_api_tests/test_data_type_functions.py::test_iinfo_dtype

# 2023.12 support
# Argument 'device' missing from signature
array_api_tests/test_signatures.py::test_func_signature[from_dlpack]
# Argument 'max_version' missing from signature
array_api_tests/test_signatures.py::test_array_method_signature[__dlpack__]

# 2025.12 support

# broadcast_shapes emits a RuntimeError where the spec says ValueError
array_api_tests/test_data_type_functions.py::TestBroadcastShapes::test_error