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))
