def deconv_block(input_key, output_key, n_feat, name):
try:
layer_dict[output_key] = \
L.transpose_conv(layer_dict[input_key],
out_dim=n_feat,
name=name,
)
except KeyError:
pass
def _create_deconv(self, layer_dict, data_dict={}):
def deconv_block(input_key, output_key, n_feat, name):
try:
layer_dict[output_key] = \
L.transpose_conv(layer_dict[input_key],
out_dim=n_feat,
name=name,
)
except KeyError:
pass
def unpool_block(input_key, output_key, switch_key, name):
try:
layer_dict[output_key] = \
L.unpool_2d(layer_dict[input_key],
layer_dict[switch_key],
stride=[1, 2, 2, 1],
scope=name)
except KeyError:
pass
with arg_scope([L.transpose_conv],
filter_size=3,
nl=tf.nn.relu,
trainable=False,
data_dict=data_dict,
use_bias=False,
stride=1,
reuse=True):
deconv_block('deconv5_4', 'deconv5_3', 512, 'conv5_4')
deconv_block('deconv5_3', 'deconv5_2', 512, 'conv5_3')
deconv_block('deconv5_2', 'deconv5_1', 512, 'conv5_2')
deconv_block('deconv5_1', 'depool4', 512, 'conv5_1')
unpool_block('depool4', 'deconv4_4', 'switch_pool4', 'unpool4')
deconv_block('deconv4_4', 'deconv4_3', 512, 'conv4_4')
deconv_block('deconv4_3', 'deconv4_2', 512, 'conv4_3')
deconv_block('deconv4_2', 'deconv4_1', 512, 'conv4_2')
deconv_block('deconv4_1', 'depool3', 256, 'conv4_1')
unpool_block('depool3', 'deconv3_4', 'switch_pool3', 'unpool3')
deconv_block('deconv3_4', 'deconv3_3', 256, 'conv3_4')
deconv_block('deconv3_3', 'deconv3_2', 256, 'conv3_3')
deconv_block('deconv3_2', 'deconv3_1', 256, 'conv3_2')
deconv_block('deconv3_1', 'depool2', 128, 'conv3_1')
unpool_block('depool2', 'deconv2_2', 'switch_pool2', 'unpool2')
deconv_block('deconv2_2', 'deconv2_1', 128, 'conv2_2')
deconv_block('deconv2_1', 'depool1', 64, 'conv2_1')
unpool_block('depool1', 'deconv1_2', 'switch_pool1', 'unpool1')
deconv_block('deconv1_2', 'deconv1_1', 64, 'conv1_2')
layer_dict['deconvim'] = \
L.transpose_conv(layer_dict['deconv1_1'],
3,
3,
trainable=False,
data_dict=data_dict,
reuse=True,
use_bias=False,
stride=1,
name='conv1_1')