Add maximum and minimum torch wrappers (for fixed two-arg type promotion)

Author: asmeurer

array_api_compat/torch/_aliases.py

@@ -177,6 +177,8 @@ def can_cast(from_: Union[Dtype, array], to: Dtype, /) -> bool:
 logaddexp = _two_arg(torch.logaddexp)
 # logical functions are not included here because they only accept bool in the
 # spec, so type promotion is irrelevant.
+maximum = _two_arg(torch.maximum)
+minimum = _two_arg(torch.minimum)
 multiply = _two_arg(torch.multiply)
 not_equal = _two_arg(torch.not_equal)
 pow = _two_arg(torch.pow)
@@ -735,15 +737,16 @@ def sign(x: array, /) -> array:
  'atan2', 'bitwise_and', 'bitwise_left_shift', 'bitwise_or',
  'bitwise_right_shift', 'bitwise_xor', 'copysign', 'divide',
  'equal', 'floor_divide', 'greater', 'greater_equal', 'hypot',
- 'less', 'less_equal', 'logaddexp', 'multiply', 'not_equal', 'pow',
- 'remainder', 'subtract', 'max', 'min', 'clip', 'unstack',
- 'cumulative_sum', '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', 'sign']
+ 'less', 'less_equal', 'logaddexp', 'maximum', 'minimum',
+ 'multiply', 'not_equal', 'pow', 'remainder', 'subtract', 'max',
+ 'min', 'clip', 'unstack', 'cumulative_sum', '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', 'sign']
 
 _all_ignore = ['torch', 'get_xp']