parameters: (x, axis=None, unbiased=True, keepdim=False, name=None)
return_statement: return paddle.sqrt(out)
docstring: Computes the standard-deviation of ``x`` along ``axis`` .
  
      Args:
          x (Tensor): The input Tensor with data type float32, float64.
          axis (int|list|tuple, optional): The axis along which to perform
              standard-deviation calculations. ``axis`` should be int, list(int)
              or tuple(int). If ``axis`` is a list/tuple of dimension(s),
              standard-deviation is calculated along all element(s) of ``axis`` .
              ``axis`` or element(s) of ``axis`` should be in range [-D, D),
              where D is the dimensions of ``x`` . If ``axis`` or element(s) of
              ``axis`` is less than 0, it works the same way as :math:`axis + D` .
              If ``axis`` is None, standard-deviation is calculated over all
              elements of ``x``. Default is None.
          unbiased (bool, optional): Whether to use the unbiased estimation. If
              ``unbiased`` is True, the standard-deviation is calculated via the
              unbiased estimator. If ``unbiased`` is True,  the divisor used in
              the computation is :math:`N - 1`, where :math:`N` represents the
              number of elements along ``axis`` , otherwise the divisor is
              :math:`N`. Default is True.
          keepdim (bool, optional): Whether to reserve the reduced dimension(s)
              in the output Tensor. If ``keepdim`` is True, the dimensions of
              the output Tensor is the same as ``x`` except in the reduced
              dimensions(it is of size 1 in this case). Otherwise, the shape of
              the output Tensor is squeezed in ``axis`` . Default is False.
          name (str, optional): Name for the operation (optional, default is None).
              For more information, please refer to :ref:`api_guide_Name`.
  
      Returns:
          Tensor, results of standard-deviation along ``axis`` of ``x``, with the
          same data type as ``x``.
  
      Examples:
          .. code-block:: python
  
              import paddle
  
              x = paddle.to_tensor([[1.0, 2.0, 3.0], [1.0, 4.0, 5.0]])
              out1 = paddle.std(x)
              # [1.63299316]
              out2 = paddle.std(x, axis=1)
              # [1.       2.081666]
docstring_summary: Computes the standard-deviation of ``x`` along ``axis`` .
docstring_tokens: Computes the standard - deviation of x along axis .
function: def std(x, axis=None, unbiased=True, keepdim=False, name=None):
      """
      Computes the standard-deviation of ``x`` along ``axis`` .
  
      Args:
          x (Tensor): The input Tensor with data type float32, float64.
          axis (int|list|tuple, optional): The axis along which to perform
              standard-deviation calculations. ``axis`` should be int, list(int)
              or tuple(int). If ``axis`` is a list/tuple of dimension(s),
              standard-deviation is calculated along all element(s) of ``axis`` .
              ``axis`` or element(s) of ``axis`` should be in range [-D, D),
              where D is the dimensions of ``x`` . If ``axis`` or element(s) of
              ``axis`` is less than 0, it works the same way as :math:`axis + D` .
              If ``axis`` is None, standard-deviation is calculated over all
              elements of ``x``. Default is None.
          unbiased (bool, optional): Whether to use the unbiased estimation. If
              ``unbiased`` is True, the standard-deviation is calculated via the
              unbiased estimator. If ``unbiased`` is True,  the divisor used in
              the computation is :math:`N - 1`, where :math:`N` represents the
              number of elements along ``axis`` , otherwise the divisor is
              :math:`N`. Default is True.
          keepdim (bool, optional): Whether to reserve the reduced dimension(s)
              in the output Tensor. If ``keepdim`` is True, the dimensions of
              the output Tensor is the same as ``x`` except in the reduced
              dimensions(it is of size 1 in this case). Otherwise, the shape of
              the output Tensor is squeezed in ``axis`` . Default is False.
          name (str, optional): Name for the operation (optional, default is None).
              For more information, please refer to :ref:`api_guide_Name`.
  
      Returns:
          Tensor, results of standard-deviation along ``axis`` of ``x``, with the
          same data type as ``x``.
  
      Examples:
          .. code-block:: python
  
              import paddle
  
              x = paddle.to_tensor([[1.0, 2.0, 3.0], [1.0, 4.0, 5.0]])
              out1 = paddle.std(x)
              # [1.63299316]
              out2 = paddle.std(x, axis=1)
              # [1.       2.081666]
      """
      if not in_dygraph_mode():
          check_variable_and_dtype(x, 'x', ['float32', 'float64'], 'std')
  
      out = var(**locals())
      return paddle.sqrt(out)
function_tokens: def std ( x , axis = None , unbiased = True , keepdim = False , name = None ) : if not in_dygraph_mode ( ) : check_variable_and_dtype ( x , 'x' , [ 'float32' , 'float64' ] , 'std' ) out = var ( * * locals ( ) ) return paddle . sqrt ( out )