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82 lines
2.0 KiB
82 lines
2.0 KiB
import numpy as np
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import mindspore
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from mindspore import nn
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from mindspore import Tensor
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from mindspore import context
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from mindspore.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE)
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class Layer1(nn.Cell):
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def __init__(self):
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super(Layer1, self).__init__()
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self.net = nn.Conv2d(3, 1, 3, pad_mode='same')
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self.pad = nn.Pad(
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paddings=((0, 0), (0, 2), (0, 0), (0, 0)), mode="CONSTANT")
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def construct(self, x):
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y = self.net(x)
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return self.pad(y)
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class Layer2(nn.Cell):
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def __init__(self):
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super(Layer2, self).__init__()
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self.net = nn.Conv2d(3, 1, 7, pad_mode='same')
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self.pad = nn.Pad(
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paddings=((0, 0), (0, 2), (0, 0), (0, 0)), mode="CONSTANT")
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def construct(self, x):
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y = self.net(x)
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return self.pad(y)
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class Layer3(nn.Cell):
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def __init__(self):
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super(Layer3, self).__init__()
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self.net = nn.Conv2d(3, 3, 3, pad_mode='same')
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def construct(self, x):
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return self.net(x)
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class SwitchNet(nn.Cell):
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def __init__(self):
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super(SwitchNet, self).__init__()
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self.layer1 = Layer1()
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self.layer2 = Layer2()
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self.layer3 = Layer3()
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self.layers = (self.layer1, self.layer2, self.layer3)
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self.fill = P.Fill()
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def construct(self, x, index):
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y = self.layers[index](x)
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return y
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class MySwitchNet(nn.Cell):
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def __init__(self):
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super(MySwitchNet, self).__init__()
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self.layer1 = Layer1()
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self.layer2 = Layer2()
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self.layer3 = Layer3()
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self.layers = (self.layer1, self.layer2, self.layer3)
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self.fill = P.Fill()
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def construct(self, x, index):
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y = self.layers[0](x)
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for i in range(len(self.layers)):
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if i == index:
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y = self.layers[i](x)
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return y
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def test_layer_switch():
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net = MySwitchNet()
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x = Tensor(np.ones((3, 3, 24, 24)), mindspore.float32)
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index = Tensor(0, dtype=mindspore.int32)
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y = net(x, index)
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