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43 lines
1.5 KiB
43 lines
1.5 KiB
import paddle.fluid as fluid
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class ConvPool(fluid.dygraph.Layer):
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def __init__(self,
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num_channels,
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num_filters,
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filter_size,
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pool_size,
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pool_stride,
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groups,
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pool_padding=0,
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pool_type='max',
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conv_stride=1,
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conv_padding=1,
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act=None):
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super(ConvPool,self).__init__()
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self._conv2d_list=[]
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for i in range (groups):
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conv2d = self.add_sublayer('bb_%d'%i,
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fluid.dygraph.Conv2D(
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num_channels=num_channels,
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num_filters=num_filters,
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filter_size=filter_size,
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stride=conv_stride,
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padding=conv_padding,
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act=act
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))
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num_channels = num_filters
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self._conv2d_list.append(conv2d)
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self._pool2d=fluid.dygraph.Pool2D(
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pool_size=pool_size,
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pool_type=pool_type,
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pool_stride=pool_stride,
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pool_padding=pool_padding
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)
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def forward(self, inputs):
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x= inputs
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for conv in self._conv2d_list:
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x= conv(x)
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x = self._pool2d(x)
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return x |