parameters: (shape, dtype=None, name=None)
docstring: Instantiates an all-ones variable and returns it.
  
    Arguments:
        shape: Tuple of integers, shape of returned Keras variable.
        dtype: String, data type of returned Keras variable.
        name: String, name of returned Keras variable.
  
    Returns:
        A Keras variable, filled with `1.0`.
        Note that if `shape` was symbolic, we cannot return a variable,
        and will return a dynamically-shaped tensor instead.
  
    Example:
    ```python
    >>> from keras import backend as K
    >>> kvar = K.ones((3,4))
    >>> K.eval(kvar)
    array([[ 1.,  1.,  1.,  1.],
           [ 1.,  1.,  1.,  1.],
           [ 1.,  1.,  1.,  1.]], dtype=float32)
    ```
docstring_summary: Instantiates an all-ones variable and returns it.
docstring_tokens: Instantiates an all - ones variable and returns it .
function: def ones(shape, dtype=None, name=None):
    """Instantiates an all-ones variable and returns it.
  
    Arguments:
        shape: Tuple of integers, shape of returned Keras variable.
        dtype: String, data type of returned Keras variable.
        name: String, name of returned Keras variable.
  
    Returns:
        A Keras variable, filled with `1.0`.
        Note that if `shape` was symbolic, we cannot return a variable,
        and will return a dynamically-shaped tensor instead.
  
    Example:
    ```python
    >>> from keras import backend as K
    >>> kvar = K.ones((3,4))
    >>> K.eval(kvar)
    array([[ 1.,  1.,  1.,  1.],
           [ 1.,  1.,  1.,  1.],
           [ 1.,  1.,  1.,  1.]], dtype=float32)
    ```
    """
    with ops.init_scope():
      if dtype is None:
        dtype = floatx()
      tf_dtype = dtypes_module.as_dtype(dtype)
      v = array_ops.ones(shape=shape, dtype=tf_dtype, name=name)
      if py_all(v.shape.as_list()):
        return variable(v, dtype=dtype, name=name)
      track_variable(v)
      return v
function_tokens: def ones ( shape , dtype = None , name = None ) : with ops . init_scope ( ) : if dtype is None : dtype = floatx ( ) tf_dtype = dtypes_module . as_dtype ( dtype ) v = array_ops . ones ( shape = shape , dtype = tf_dtype , name = name ) if py_all ( v . shape . as_list ( ) ) : return variable ( v , dtype = dtype , name = name ) track_variable ( v ) return v