code: def _docs_logic():
      _docs.set_doc(
          chainerx.all,
          """all(x)
  Test whether all array elements along a given axis evaluate to True.
  
  Args:
      x (~chainerx.ndarray): Input array.
      axis (None or int or tuple of ints):
          Axis or axes along which AND reduction is performed.
          The flattened array is used by default.
      keepdims (bool):
          If this is set to ``True``, the reduced axes are left in the result
          as dimensions with size one.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.all`
  """,
      )
  
      _docs.set_doc(
          chainerx.any,
          """any(x)
  Test whether any array element along a given axis evaluate to True.
  
  Args:
      x (~chainerx.ndarray): Input array.
      axis (None or int or tuple of ints):
          Axis or axes along which OR reduction is performed.
          The flattened array is used by default.
      keepdims (bool):
          If this is set to ``True``, the reduced axes are left in the result
          as dimensions with size one.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.any`
  """,
      )
  
      _docs.set_doc(
          chainerx.logical_not,
          """logical_not(x)
  Returns an array of NOT x element-wise.
  
  Args:
      x (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.logical_not`
  """,
      )
  
      _docs.set_doc(
          chainerx.logical_and,
          """logical_and(x1, x2)
  Returns an array of x1 AND x2 element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.logical_and`
      """,
      )
  
      _docs.set_doc(
          chainerx.logical_or,
          """logical_or(x1, x2)
  Returns an array of x1 OR x2 element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.logical_or`
      """,
      )
  
      _docs.set_doc(
          chainerx.logical_xor,
          """logical_xor(x1, x2)
  Returns an array of x1 XOR x2 element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.logical_xor`
      """,
      )
  
      _docs.set_doc(
          chainerx.greater,
          """greater(x1, x2)
  Returns an array of (x1 > x2) element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.greater`
  """,
      )
  
      _docs.set_doc(
          chainerx.greater_equal,
          """greater_equal(x1, x2)
  Returns an array of (x1 >= x2) element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.greater_equal`
  """,
      )
  
      _docs.set_doc(
          chainerx.less,
          """less(x1, x2)
  Returns an array of (x1 < x2) element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.less`
  """,
      )
  
      _docs.set_doc(
          chainerx.less_equal,
          """less_equal(x1, x2)
  Returns an array of (x1 <= x2) element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.less_equal`
  """,
      )
  
      _docs.set_doc(
          chainerx.equal,
          """equal(x1, x2)
  Returns an array of (x1 == x2) element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.equal`
  """,
      )
  
      _docs.set_doc(
          chainerx.not_equal,
          """not_equal(x1, x2)
  Returns an array of (x1 != x2) element-wise.
  
  Args:
      x1 (~chainerx.ndarray): Input array.
      x2 (~chainerx.ndarray): Input array.
  
  Returns:
      :class:`~chainerx.ndarray`: Output array of type bool.
  
  Note:
      During backpropagation, this function does not propagate gradients.
  
  .. seealso:: :data:`numpy.not_equal`
  """,
      )
  
file_path: chainer/chainerx/_docs/routines.py
imports: import chainerx
  from chainerx import _docs
label_desc: Use image node_id 6 for calling a global function with example usage: _docs_logic() without return types