Merge pull request #174 from asmeurer/torch-conj

Use conj_physical for torch.conj

Author: asmeurer

array_api_compat/torch/_aliases.py

@@ -145,6 +145,9 @@ def can_cast(from_: Union[Dtype, array], to: Dtype, /) -> bool:
 # Basic renames
 bitwise_invert = torch.bitwise_not
 newaxis = None
+# torch.conj sets the conjugation bit, which breaks conversion to other
+# libraries. See https://github.com/data-apis/array-api-compat/issues/173
+conj = torch.conj_physical
 
 # Two-arg elementwise functions
 # These require a wrapper to do the correct type promotion on 0-D tensors
@@ -704,18 +707,18 @@ def take(x: array, indices: array, /, *, axis: Optional[int] = None, **kwargs) -
     return torch.index_select(x, axis, indices, **kwargs)
 
 __all__ = ['result_type', 'can_cast', 'permute_dims', 'bitwise_invert',
-           'newaxis', 'add', 'atan2', 'bitwise_and', 'bitwise_left_shift',
-           'bitwise_or', 'bitwise_right_shift', 'bitwise_xor', 'copysign',
-           'divide', 'equal', 'floor_divide', 'greater', 'greater_equal',
-           'less', 'less_equal', 'logaddexp', 'multiply', 'not_equal', 'pow',
-           'remainder', 'subtract', 'max', 'min', 'clip', 'sort', 'prod',
-           'sum', 'any', 'all', 'mean', 'std', 'var', 'concat', 'squeeze',
-           'broadcast_to', 'flip', 'roll', 'nonzero', 'where', 'reshape',
-           'arange', 'eye', 'linspace', 'full', 'ones', 'zeros', 'empty',
-           'tril', 'triu', 'expand_dims', 'astype', 'broadcast_arrays',
-           'UniqueAllResult', 'UniqueCountsResult', 'UniqueInverseResult',
-           'unique_all', 'unique_counts', 'unique_inverse', 'unique_values',
-           'matmul', 'matrix_transpose', 'vecdot', 'tensordot', 'isdtype',
-           'take']
+           'newaxis', 'conj', 'add', 'atan2', 'bitwise_and',
+           'bitwise_left_shift', 'bitwise_or', 'bitwise_right_shift',
+           'bitwise_xor', 'copysign', 'divide', 'equal', 'floor_divide',
+           'greater', 'greater_equal', 'less', 'less_equal', 'logaddexp',
+           'multiply', 'not_equal', 'pow', 'remainder', 'subtract', 'max',
+           'min', 'clip', 'sort', 'prod', 'sum', 'any', 'all', 'mean', 'std',
+           'var', 'concat', 'squeeze', 'broadcast_to', 'flip', 'roll',
+           'nonzero', 'where', 'reshape', 'arange', 'eye', 'linspace', 'full',
+           'ones', 'zeros', 'empty', 'tril', 'triu', 'expand_dims', 'astype',
+           'broadcast_arrays', 'UniqueAllResult', 'UniqueCountsResult',
+           'UniqueInverseResult', 'unique_all', 'unique_counts',
+           'unique_inverse', 'unique_values', 'matmul', 'matrix_transpose',
+           'vecdot', 'tensordot', 'isdtype', 'take']
 
 _all_ignore = ['torch', 'get_xp']