# Source code for mars.tensor.arithmetic.equal

#!/usr/bin/env python
# -*- coding: utf-8 -*-
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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
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import numpy as np
from ... import opcodes as OperandDef
from ..utils import inject_dtype
from .core import TensorBinOp
from .utils import arithmetic_operand
@arithmetic_operand(sparse_mode="binary_and")
class TensorEqual(TensorBinOp):
_op_type_ = OperandDef.EQ
_func_name = "equal"
[docs]@inject_dtype(np.bool_)
def equal(x1, x2, out=None, where=None, **kwargs):
"""
Return (x1 == x2) element-wise.
Parameters
----------
x1, x2 : array_like
Input tensors of the same shape.
out : Tensor, None, or tuple of Tensor and None, optional
A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or `None`,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.
where : array_like, optional
Values of True indicate to calculate the ufunc at that position, values
of False indicate to leave the value in the output alone.
**kwargs
For other keyword-only arguments, see the
:ref:`ufunc docs <ufuncs.kwargs>`.
Returns
-------
out : Tensor or bool
Output tensor of bools, or a single bool if x1 and x2 are scalars.
See Also
--------
not_equal, greater_equal, less_equal, greater, less
Examples
--------
>>> import mars.tensor as mt
>>> mt.equal([0, 1, 3], mt.arange(3)).execute()
array([ True, True, False])
What is compared are values, not types. So an int (1) and a tensor of
length one can evaluate as True:
>>> mt.equal(1, mt.ones(1))
array([ True])
"""
op = TensorEqual(**kwargs)
return op(x1, x2, out=out, where=where)