parameters: (path='mnist.npz')
return_statement: return (x_train, y_train), (x_test, y_test)
docstring: Loads the MNIST dataset.
  
    Arguments:
        path: path where to cache the dataset locally
            (relative to ~/.keras/datasets).
  
    Returns:
        Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
docstring_summary: Loads the MNIST dataset.
docstring_tokens: Loads the MNIST dataset .
function: def load_data(path='mnist.npz'):
    """Loads the MNIST dataset.
  
    Arguments:
        path: path where to cache the dataset locally
            (relative to ~/.keras/datasets).
  
    Returns:
        Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.
    """
    path = get_file(
        path, origin='https://s3.amazonaws.com/img-datasets/mnist.npz')
    f = np.load(path)
    x_train = f['x_train']
    y_train = f['y_train']
    x_test = f['x_test']
    y_test = f['y_test']
    f.close()
    return (x_train, y_train), (x_test, y_test)
function_tokens: def load_data ( path = 'mnist.npz' ) : path = get_file ( path , origin = 'https://s3.amazonaws.com/img-datasets/mnist.npz' ) f = np . load ( path ) x_train = f [ 'x_train' ] y_train = f [ 'y_train' ] x_test = f [ 'x_test' ] y_test = f [ 'y_test' ] f . close ( ) return ( x_train , y_train ) , ( x_test , y_test )