parameters: (x)
return_statement: return x
docstring: Turn a nD tensor into a 2D tensor with same 0th dimension.
  
    In other words, it flattens each data samples of a batch.
  
    Args:
        x: A tensor or variable.
  
    Returns:
        A tensor.
  
    Examples:
      Flattening a 3D tensor to 2D by collapsing the last dimension.
  
    >>> x_batch = tf.keras.backend.ones(shape=(2, 3, 4, 5))
    >>> x_batch_flatten = batch_flatten(x_batch)
    >>> tf.keras.backend.int_shape(x_batch_flatten)
    (2, 60)
docstring_summary: Turn a nD tensor into a 2D tensor with same 0th dimension.
docstring_tokens: Turn a nD tensor into a 2D tensor with same 0th dimension .
function: def batch_flatten(x):
    """Turn a nD tensor into a 2D tensor with same 0th dimension.
  
    In other words, it flattens each data samples of a batch.
  
    Args:
        x: A tensor or variable.
  
    Returns:
        A tensor.
  
    Examples:
      Flattening a 3D tensor to 2D by collapsing the last dimension.
  
    >>> x_batch = tf.keras.backend.ones(shape=(2, 3, 4, 5))
    >>> x_batch_flatten = batch_flatten(x_batch)
    >>> tf.keras.backend.int_shape(x_batch_flatten)
    (2, 60)
  
    """
    x = array_ops.reshape(x, array_ops.stack([-1, prod(shape(x)[1:])]))
    return x
function_tokens: def batch_flatten ( x ) : x = array_ops . reshape ( x , array_ops . stack ( [ - 1 , prod ( shape ( x ) [ 1 : ] ) ] ) ) return x