``logical_and`` operator computes element-wise logical AND on ``x`` and ``y``, and returns ``out``. ``x``, ``y`` and ``out`` are N-dim boolean ``Variable``.
``logical_and`` operator computes element-wise logical AND on ``x`` and ``y``, and returns ``out``. ``x``, ``y`` and ``out`` are N-dim boolean ``Tensor``.
Each element of ``out`` is calculated by
Each element of ``out`` is calculated by
.. math::
.. math::
out = x \&\& y
out = x \&\& y
.. note::
``paddle.logical_and`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting`.
Args:
Args:
x(${x_type}): ${x_comment}.
x (Tensor): the input tensor, it's data type should be bool.
y(${y_type}): ${y_comment}.
y (Tensor): the input tensor, it's data type should be bool.
out(Variable): The ``Variable`` that specifies the output of the operator, which can be any ``Variable`` that has been created in the program. The default value is None, and a new ``Variable`` will be created to save the output.
out(Tensor): The ``Tensor`` that specifies the output of the operator, which can be any ``Tensor`` that has been created in the program. The default value is None, and a new ``Tensor`` will be created to save the output.
name(str|None): The default value is None. Normally there is no need for users to set this property. For more information, please refer to :ref:`api_guide_Name`.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Returns:
${out_type}: ${out_comment}
N-D Tensor. A location into which the result is stored. It's dimension equals with ``x``.
Examples:
Examples:
.. code-block:: python
.. code-block:: python
...
@@ -12140,43 +12146,38 @@ def logical_and(x, y, out=None, name=None):
...
@@ -12140,43 +12146,38 @@ def logical_and(x, y, out=None, name=None):
``logical_or`` operator computes element-wise logical OR on ``x`` and ``y``, and returns ``out``. ``x``, ``y`` and ``out`` are N-dim boolean ``Variable``.
``logical_or`` operator computes element-wise logical OR on ``x`` and ``y``, and returns ``out``. ``x``, ``y`` and ``out`` are N-dim boolean ``Tensor``.
Each element of ``out`` is calculated by
Each element of ``out`` is calculated by
.. math::
.. math::
out = x || y
out = x || y
.. note::
``paddle.logical_or`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting`.
Args:
Args:
x(${x_type}): ${x_comment}.
x (Tensor): the input tensor, it's data type should be bool.
y(${y_type}): ${y_comment}.
y (Tensor): the input tensor, it's data type should be bool.
out(Variable): The ``Variable`` that specifies the output of the operator, which can be any ``Variable`` that has been created in the program. The default value is None, and a new ``Variable`` will be created to save the output.
out(Tensor): The ``Variable`` that specifies the output of the operator, which can be any ``Tensor`` that has been created in the program. The default value is None, and a new ``Tensor`` will be created to save the output.
name(str|None): The default value is None. Normally there is no need for users to set this property. For more information, please refer to :ref:`api_guide_Name`.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Returns:
${out_type}: ${out_comment}
N-D Tensor. A location into which the result is stored. It's dimension equals with ``x``.
Examples:
Examples:
.. code-block:: python
.. code-block:: python
...
@@ -12185,43 +12186,38 @@ def logical_or(x, y, out=None, name=None):
...
@@ -12185,43 +12186,38 @@ def logical_or(x, y, out=None, name=None):
``logical_xor`` operator computes element-wise logical XOR on ``x`` and ``y``, and returns ``out``. ``x``, ``y`` and ``out`` are N-dim boolean ``Variable``.
``logical_xor`` operator computes element-wise logical XOR on ``x`` and ``y``, and returns ``out``. ``x``, ``y`` and ``out`` are N-dim boolean ``Tensor``.
Each element of ``out`` is calculated by
Each element of ``out`` is calculated by
.. math::
.. math::
out = (x || y) \&\& !(x \&\& y)
out = (x || y) \&\& !(x \&\& y)
.. note::
``paddle.logical_xor`` supports broadcasting. If you want know more about broadcasting, please refer to :ref:`user_guide_broadcasting`.
Args:
Args:
x(${x_type}): ${x_comment}.
x (Tensor): the input tensor, it's data type should be bool.
y(${y_type}): ${y_comment}.
y (Tensor): the input tensor, it's data type should be bool.
out(Variable): The ``Variable`` that specifies the output of the operator, which can be any ``Variable`` that has been created in the program. The default value is None, and a new ``Variable`` will be created to save the output.
out(Tensor): The ``Tensor`` that specifies the output of the operator, which can be any ``Tensor`` that has been created in the program. The default value is None, and a new ``Tensor`` will be created to save the output.
name(str|None): The default value is None. Normally there is no need for users to set this property. For more information, please refer to :ref:`api_guide_Name`.
name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
Returns:
Returns:
${out_type}: ${out_comment}
N-D Tensor. A location into which the result is stored. It's dimension equals with ``x``.
Examples:
Examples:
.. code-block:: python
.. code-block:: python
...
@@ -12230,17 +12226,13 @@ def logical_xor(x, y, out=None, name=None):
...
@@ -12230,17 +12226,13 @@ def logical_xor(x, y, out=None, name=None):
