diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 097fbe982f21fc77efe9fe61dfa27fe71c5f08f7..b9f4ff900947dbfcf27d226fe80658ac16c04868 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -4263,14 +4263,18 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=True, name=None): say :attr:`actual_shape` has a higher priority than :attr:`shape`. act (str): The non-linear activation to be applied to output variable. - inplace(bool): If this flag is set true, a new output tensor is created - whose data is copied from input x, otherwise the output - shares data with input without copying. + inplace(bool): If this flag is set true, the output + shares data with input without copying, otherwise + a new output tensor is created + whose data is copied from input x. name (str): The name of this layer. It is optional. Returns: Variable: The output tensor. + Raises: + TypeError: if actual_shape is neither Variable nor None. + Examples: .. code-block:: python @@ -4282,6 +4286,11 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=True, name=None): if not (isinstance(shape, list) or isinstance(shape, tuple)): raise ValueError("Input shape must be a python lsit or tuple.") + inputs = {"X": x} + if isinstance(actual_shape, Variable): + inputs["Shape"] = actual_shape + elif actual_shape is not None: + raise TypeError("actual_shape should either be Variable or None") # Validate the shape unk_dim_idx = -1 @@ -4302,9 +4311,7 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=True, name=None): reshaped = helper.create_tmp_variable(dtype=x.dtype) helper.append_op( type="reshape", - inputs={"X": x, - "Shape": actual_shape} - if isinstance(actual_shape, Variable) else {"X": x}, + inputs=inputs, attrs={"shape": shape, "inplace": inplace}, outputs={"Out": reshaped})