parameters: (x)
return_statement: return array_ops.shape(x)
docstring: Returns the symbolic shape of a tensor or variable.
  
    Arguments:
        x: A tensor or variable.
  
    Returns:
        A symbolic shape (which is itself a tensor).
  
    Examples:
  
    ```python
    # TensorFlow example
    >>> from keras import backend as K
    >>> tf_session = K.get_session()
    >>> val = np.array([[1, 2], [3, 4]])
    >>> kvar = K.variable(value=val)
    >>> input = keras.backend.placeholder(shape=(2, 4, 5))
    >>> K.shape(kvar)
    <tf.Tensor 'Shape_8:0' shape=(2,) dtype=int32>
    >>> K.shape(input)
    <tf.Tensor 'Shape_9:0' shape=(3,) dtype=int32>
    # To get integer shape (Instead, you can use K.int_shape(x))
    >>> K.shape(kvar).eval(session=tf_session)
    array([2, 2], dtype=int32)
    >>> K.shape(input).eval(session=tf_session)
    array([2, 4, 5], dtype=int32)
    ```
docstring_summary: Returns the symbolic shape of a tensor or variable.
docstring_tokens: Returns the symbolic shape of a tensor or variable .
function: def shape(x):
    """Returns the symbolic shape of a tensor or variable.
  
    Arguments:
        x: A tensor or variable.
  
    Returns:
        A symbolic shape (which is itself a tensor).
  
    Examples:
  
    ```python
    # TensorFlow example
    >>> from keras import backend as K
    >>> tf_session = K.get_session()
    >>> val = np.array([[1, 2], [3, 4]])
    >>> kvar = K.variable(value=val)
    >>> input = keras.backend.placeholder(shape=(2, 4, 5))
    >>> K.shape(kvar)
    <tf.Tensor 'Shape_8:0' shape=(2,) dtype=int32>
    >>> K.shape(input)
    <tf.Tensor 'Shape_9:0' shape=(3,) dtype=int32>
    # To get integer shape (Instead, you can use K.int_shape(x))
    >>> K.shape(kvar).eval(session=tf_session)
    array([2, 2], dtype=int32)
    >>> K.shape(input).eval(session=tf_session)
    array([2, 4, 5], dtype=int32)
    ```
    """
    return array_ops.shape(x)
function_tokens: def shape ( x ) : return array_ops . shape ( x )