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