mindspore.nn.SequentialCell

class mindspore.nn.SequentialCell(*args)

Sequential Cell container. For more details about Cell, please refer to Cell.

A list of Cells will be added to it in the order they are passed in the constructor. Alternatively, an ordered dict of cells can also be passed in.

Parameters:

args (list, OrderedDict) – List or OrderedDict of subclass of Cell.

Inputs:

• x (Tensor) - Tensor with shape according to the first Cell in the sequence.

Outputs:

Tensor, the output Tensor with shape depending on the input x and defined sequence of Cells.

Raises:

TypeError – If the type of the args is not list or OrderedDict.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, nn
>>> import numpy as np
>>>
>>> conv = nn.Conv2d(3, 2, 3, pad_mode='valid', weight_init="ones")
>>> relu = nn.ReLU()
>>> seq = nn.SequentialCell([conv, relu])
>>> x = Tensor(np.ones([1, 3, 4, 4]), dtype = mindspore.float32)
>>> output = seq(x)
>>> print(output)
[[[[27. 27.]
   [27. 27.]]
  [[27. 27.]
   [27. 27.]]]]
>>> from collections import OrderedDict
>>> d = OrderedDict()
>>> d["conv"] = conv
>>> d["relu"] = relu
>>> seq = nn.SequentialCell(d)
>>> x = Tensor(np.ones([1, 3, 4, 4]), dtype=mindspore.float32)
>>> output = seq(x)
>>> print(output)
[[[[27. 27.]
   [27. 27.]]
  [[27. 27.]
   [27. 27.]]]]

append(cell)

Appends a given Cell to the end of the list.

Parameters:

cell (Cell) – The Cell to be appended.

Examples

>>> import mindspore
>>> from mindspore import Tensor, nn
>>> import numpy as np
>>>
>>> conv = nn.Conv2d(3, 2, 3, pad_mode='valid', weight_init="ones")
>>> bn = nn.BatchNorm2d(2)
>>> relu = nn.ReLU()
>>> seq = nn.SequentialCell([conv, bn])
>>> seq.append(relu)
>>> x = Tensor(np.ones([1, 3, 4, 4]), dtype=mindspore.float32)
>>> output = seq(x)
>>> print(output)
[[[[26.999863 26.999863]
   [26.999863 26.999863]]
  [[26.999863 26.999863]
   [26.999863 26.999863]]]]