mindspore.nn.SequentialCell
- class mindspore.nn.SequentialCell(*args)[source]
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)[source]
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]]]]