ParameterList¶

class paddle.nn. ParameterList ( parameters=None ) [source]

ParameterList Container.

This container acts like a Python list, but parameters it contains will be properly added.

Parameters

parameters (iterable, optional) – Iterable Parameters to be added.

Examples

>>> import paddle

>>> class MyLayer(paddle.nn.Layer):
...     def __init__(self, num_stacked_param):
...         super().__init__()
...         # create ParameterList with iterable Parameters
...         self.params = paddle.nn.ParameterList(
...             [paddle.create_parameter(
...                 shape=[2, 2], dtype='float32')] * num_stacked_param)
...
...     def forward(self, x):
...         for i, p in enumerate(self.params):
...             tmp = self._helper.create_variable_for_type_inference('float32')
...             self._helper.append_op(
...                 type="mul",
...                 inputs={"X": x,
...                         "Y": p},
...                 outputs={"Out": tmp},
...                 attrs={"x_num_col_dims": 1,
...                         "y_num_col_dims": 1})
...             x = tmp
...         return x
...
>>> x = paddle.uniform(shape=[5, 2], dtype='float32')
>>> num_stacked_param = 4
>>> model = MyLayer(num_stacked_param)
>>> print(len(model.params))
4
>>> res = model(x)
>>> print(res.shape)
[5, 2]

>>> replaced_param = paddle.create_parameter(shape=[2, 3], dtype='float32')
>>> model.params[num_stacked_param - 1] = replaced_param  # replace last param
>>> res = model(x)
>>> print(res.shape)
[5, 3]
>>> model.params.append(paddle.create_parameter(shape=[3, 4], dtype='float32'))  # append param
>>> print(len(model.params))
5
>>> res = model(x)
>>> print(res.shape)
[5, 4]

append ( parameter )

append¶

Appends a given parameter at the end of the list.

Parameters

parameter (Parameter) – parameter to append