def dense_block(self, blocks): for i in range(blocks): self.append_layer(Layers.BatchNormalizationLayer()) self.append_layer(Layers.ActivationLayer('relu')) self.append_layer(Layers.ConvLayer(4 * 32, 1, 1, use_bias_in=False)) self.append_layer(Layers.BatchNormalizationLayer()) self.append_layer(Layers.ActivationLayer('relu')) self.append_layer( Layers.ConvLayer(32, 3, 1, padding_in='same', use_bias_in=False)) self.append_layer(Layers.ConcatenateLayer(concatenate=True))
def test_layer(self): self.append_layer(Layers.ZeroPaddingLayer(3)) self.append_layer(Layers.ConvLayer(64, 7, 2, use_bias_in=False)) self.append_layer(Layers.BatchNormalizationLayer()) self.append_layer(Layers.ActivationLayer('relu')) self.append_layer(Layers.ZeroPaddingLayer(1)) self.append_layer( Layers.PoolLayer(3, 2, type_in='max', concatenate=True)) self.dense_block(6) self.transition_block(128) self.dense_block(12) self.transition_block(256) self.dense_block(32) self.transition_block(640) self.dense_block(32) self.append_layer(Layers.BatchNormalizationLayer()) self.append_layer(Layers.PoolLayer(2, 2, pool_type_in='globalaverage')) self.append_layer(Layers.ActivationLayer('sigmoid'))
def transition_block(self, conv_in): self.append_layer(Layers.BatchNormalizationLayer()) self.append_layer(Layers.ActivationLayer('relu')) self.append_layer(Layers.ConvLayer(conv_in, 1, 1, use_bias_in=False)) self.append_layer( Layers.PoolLayer(2, 2, type_in='average', concatenate=True))