def _config(self):
layer_factory = LayerFactory(self)
layer_factory.new_feed(name='data', layer_shape=(None, 24, 24, 3))
layer_factory.new_conv(name='conv1',
kernel_size=(3, 3),
channels_output=28,
stride_size=(1, 1),
padding='VALID',
relu=False)
layer_factory.new_prelu(name='prelu1')
layer_factory.new_max_pool(name='pool1',
kernel_size=(3, 3),
stride_size=(2, 2))
layer_factory.new_conv(name='conv2',
kernel_size=(3, 3),
channels_output=48,
stride_size=(1, 1),
padding='VALID',
relu=False)
layer_factory.new_prelu(name='prelu2')
layer_factory.new_max_pool(name='pool2',
kernel_size=(3, 3),
stride_size=(2, 2),
padding='VALID')
layer_factory.new_conv(name='conv3',
kernel_size=(2, 2),
channels_output=64,
stride_size=(1, 1),
padding='VALID',
relu=False)
layer_factory.new_prelu(name='prelu3')
layer_factory.new_fully_connected(
name="fc1", output_count=128,
relu=False) # shouldn't the name be "fc1"?
layer_factory.new_prelu(name='prelu4')
layer_factory.new_fully_connected(
name='fc2-1', output_count=2,
relu=False) # shouldn't the name be "fc2-1"?
layer_factory.new_softmax(name='prob1', axis=1)
layer_factory.new_fully_connected(name='fc2-2',
output_count=4,
relu=False,
input_layer_name='prelu4')
def _config(self):
layer_factory = LayerFactory(self)
layer_factory.new_feed(name='data', layer_shape=(None, None, None, 3))
layer_factory.new_conv(name='conv1', kernel_size=(3, 3), channels_output=10, stride_size=(1, 1),
padding='VALID', relu=False)
layer_factory.new_prelu(name='prelu1')
layer_factory.new_max_pool(name='pool1', kernel_size=(2, 2), stride_size=(2, 2))
layer_factory.new_conv(name='conv2', kernel_size=(3, 3), channels_output=16, stride_size=(1, 1),
padding='VALID', relu=False)
layer_factory.new_prelu(name='prelu2')
layer_factory.new_conv(name='conv3', kernel_size=(3, 3), channels_output=32, stride_size=(1, 1),
padding='VALID', relu=False)
layer_factory.new_prelu(name='prelu3')
layer_factory.new_conv(name='conv4-1', kernel_size=(1, 1), channels_output=2, stride_size=(1, 1), relu=False)
layer_factory.new_softmax(name='prob1', axis=3)
layer_factory.new_conv(name='conv4-2', kernel_size=(1, 1), channels_output=4, stride_size=(1, 1),
input_layer_name='prelu3', relu=False)
