def build_model():
metadata_dir = utils.get_dir_path('models', pathfinder.METADATA_PATH)
metadata_path = utils.find_model_metadata(
metadata_dir,
patch_config.__name__.split('.')[-1])
metadata = utils.load_pkl(metadata_path)
print 'Build model'
model = patch_config.build_model(patch_size=(window_size, window_size,
window_size))
all_layers = nn.layers.get_all_layers(model.l_out)
num_params = nn.layers.count_params(model.l_out)
print ' number of parameters: %d' % num_params
print string.ljust(' layer output shapes:', 36),
print string.ljust('#params:', 10),
print 'output shape:'
for layer in all_layers:
name = string.ljust(layer.__class__.__name__, 32)
num_param = sum(
[np.prod(p.get_value().shape) for p in layer.get_params()])
num_param = string.ljust(num_param.__str__(), 10)
print ' %s %s %s' % (name, num_param, layer.output_shape)
nn.layers.set_all_param_values(model.l_out, metadata['param_values'])
return model
def build_segmentation_model(l_in):
metadata_dir = utils.get_dir_path('models', pathfinder.METADATA_PATH)
metadata_path = utils.find_model_metadata(metadata_dir, patch_segmentation_config.__name__.split('.')[-1])
metadata = utils.load_pkl(metadata_path)
model = patch_segmentation_config.build_model(l_in=l_in, patch_size=p_transform['patch_size'])
nn.layers.set_all_param_values(model.l_out, metadata['param_values'])
return model
def build_segmentation_model(l_in):
metadata_dir = utils.get_dir_path('models', pathfinder.METADATA_PATH)
metadata_path = utils.find_model_metadata(
metadata_dir,
patch_segmentation_config.__name__.split('.')[-1])
metadata = utils.load_pkl(metadata_path)
model = patch_segmentation_config.build_model(
l_in=l_in, patch_size=p_transform['patch_size'])
nn.layers.set_all_param_values(model.l_out, metadata['param_values'])
return model
def build_model():
print 'Build model'
model = patch_config.build_model(patch_size=(window_size, window_size, window_size))
all_layers = nn.layers.get_all_layers(model.l_out)
num_params = nn.layers.count_params(model.l_out)
print ' number of parameters: %d' % num_params
print string.ljust(' layer output shapes:', 36),
print string.ljust('#params:', 10),
print 'output shape:'
for layer in all_layers:
name = string.ljust(layer.__class__.__name__, 32)
num_param = sum([np.prod(p.get_value().shape) for p in layer.get_params()])
num_param = string.ljust(num_param.__str__(), 10)
print ' %s %s %s' % (name, num_param, layer.output_shape)
return model
def build_model():
print('Build model')
model = patch_config.build_model(patch_size=(window_size, window_size, window_size))
all_layers = nn.layers.get_all_layers(model.l_out)
num_params = nn.layers.count_params(model.l_out)
print(' number of parameters: %d' % num_params)
print(string.ljust(' layer output shapes:', 36),)
print(string.ljust('#params:', 10),)
print('output shape:')
for layer in all_layers:
name = string.ljust(layer.__class__.__name__, 32)
num_param = sum([np.prod(p.get_value().shape) for p in layer.get_params()])
num_param = string.ljust(num_param.__str__(), 10)
print(' %s %s %s' % (name, num_param, layer.output_shape))
return model
def build_model():
metadata_dir = utils.get_dir_path('models', pathfinder.METADATA_PATH)
metadata_path = utils.find_model_metadata(metadata_dir, patch_config.__name__.split('.')[-1])
metadata = utils.load_pkl(metadata_path)
print 'Build model'
model = patch_config.build_model(patch_size=(window_size, window_size, window_size))
all_layers = nn.layers.get_all_layers(model.l_out)
num_params = nn.layers.count_params(model.l_out)
print ' number of parameters: %d' % num_params
print string.ljust(' layer output shapes:', 36),
print string.ljust('#params:', 10),
print 'output shape:'
for layer in all_layers:
name = string.ljust(layer.__class__.__name__, 32)
num_param = sum([np.prod(p.get_value().shape) for p in layer.get_params()])
num_param = string.ljust(num_param.__str__(), 10)
print ' %s %s %s' % (name, num_param, layer.output_shape)
nn.layers.set_all_param_values(model.l_out, metadata['param_values'])
return model
