2021-12-07 17:19:19 +08:00
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mindspore.nn.SequentialCell
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============================
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.. py:class:: mindspore.nn.SequentialCell(*args)
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构造Cell顺序容器。
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Cell列表将按照它们在构造函数中传递的顺序添加到其中。
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或者,也可以传入Cell的有序字典。
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2021-12-08 10:01:50 +08:00
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**参数:**
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2021-12-07 17:19:19 +08:00
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2021-12-08 10:01:50 +08:00
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**args** (list, OrderedDict) - 仅包含Cell子类的列表或有序字典。
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2021-12-07 17:19:19 +08:00
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2021-12-08 10:01:50 +08:00
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**输入:**
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**x** (Tensor) - Tensor,其shape取决于序列中的第一个Cell。
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**输出:**
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Tensor,输出Tensor,其shape取决于输入 `x` 和定义的Cell序列。
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2021-12-07 17:19:19 +08:00
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**异常:**
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2021-12-08 10:01:50 +08:00
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**TypeError** - `args` 的类型不是列表或有序字典。
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2021-12-07 17:19:19 +08:00
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2021-12-08 10:01:50 +08:00
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**支持平台:**
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2021-12-07 17:19:19 +08:00
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2021-12-08 10:01:50 +08:00
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``Ascend`` ``GPU`` ``CPU``
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**样例:**
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>>> conv = nn.Conv2d(3, 2, 3, pad_mode='valid', weight_init="ones")
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>>> relu = nn.ReLU()
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>>> seq = nn.SequentialCell([conv, relu])
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>>> x = Tensor(np.ones([1, 3, 4, 4]), dtype=mindspore.float32)
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>>> output = seq(x)
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>>> print(output)
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[[[[27. 27.]
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[27. 27.]]
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[[27. 27.]
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[27. 27.]]]]
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2021-12-07 17:19:19 +08:00
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2021-12-08 10:01:50 +08:00
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.. py:method:: append(cell)
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2021-12-07 17:19:19 +08:00
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在容器末尾添加一个cell。
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2021-12-08 10:01:50 +08:00
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**参数:**
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**cell** (Cell) - 要添加的cell。
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**样例:**
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>>> conv = nn.Conv2d(3, 2, 3, pad_mode='valid', weight_init="ones")
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>>> bn = nn.BatchNorm2d(2)
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>>> relu = nn.ReLU()
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>>> seq = nn.SequentialCell([conv, bn])
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>>> seq.append(relu)
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>>> x = Tensor(np.ones([1, 3, 4, 4]), dtype=mindspore.float32)
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>>> output = seq(x)
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>>> print(output)
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[[[[26.999863 26.999863]
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[26.999863 26.999863]]
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[[26.999863 26.999863]
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[26.999863 26.999863]]]]
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