parameters: (x)
return_statement: return array_ops.transpose(x)
docstring: Transposes a tensor and returns it.
  
    Arguments:
        x: Tensor or variable.
  
    Returns:
        A tensor.
  
    Examples:
    ```python
        >>> var = K.variable([[1, 2, 3], [4, 5, 6]])
        >>> K.eval(var)
        array([[ 1.,  2.,  3.],
               [ 4.,  5.,  6.]], dtype=float32)
        >>> var_transposed = K.transpose(var)
        >>> K.eval(var_transposed)
        array([[ 1.,  4.],
               [ 2.,  5.],
               [ 3.,  6.]], dtype=float32)
    ```
  
    ```python
        >>> input = K.placeholder((2, 3))
        >>> input
        <tf.Tensor 'Placeholder_11:0' shape=(2, 3) dtype=float32>
        >>> input_transposed = K.transpose(input)
        >>> input_transposed
        <tf.Tensor 'transpose_4:0' shape=(3, 2) dtype=float32>
  
    ```
docstring_summary: Transposes a tensor and returns it.
docstring_tokens: Transposes a tensor and returns it .
function: def transpose(x):
    """Transposes a tensor and returns it.
  
    Arguments:
        x: Tensor or variable.
  
    Returns:
        A tensor.
  
    Examples:
    ```python
        >>> var = K.variable([[1, 2, 3], [4, 5, 6]])
        >>> K.eval(var)
        array([[ 1.,  2.,  3.],
               [ 4.,  5.,  6.]], dtype=float32)
        >>> var_transposed = K.transpose(var)
        >>> K.eval(var_transposed)
        array([[ 1.,  4.],
               [ 2.,  5.],
               [ 3.,  6.]], dtype=float32)
    ```
  
    ```python
        >>> input = K.placeholder((2, 3))
        >>> input
        <tf.Tensor 'Placeholder_11:0' shape=(2, 3) dtype=float32>
        >>> input_transposed = K.transpose(input)
        >>> input_transposed
        <tf.Tensor 'transpose_4:0' shape=(3, 2) dtype=float32>
  
    ```
    """
    return array_ops.transpose(x)
function_tokens: def transpose ( x ) : return array_ops . transpose ( x )