def main(args):
with tf.Session(config=tf.ConfigProto(allow_soft_placement=True)) as sess:
model = Model(phase='predict',
visualize=args.visualize,
output_dir=args.output_dir,
batch_size=args.batch_size,
initial_learning_rate=args.initial_learning_rate,
steps_per_checkpoint=None,
model_dir=args.model_dir,
target_embedding_size=args.target_embedding_size,
attn_num_hidden=args.attn_num_hidden,
attn_num_layers=args.attn_num_layers,
clip_gradients=args.clip_gradients,
max_gradient_norm=args.max_gradient_norm,
session=sess,
load_model=True,
gpu_id=args.gpu_id,
use_gru=args.use_gru,
use_distance=args.use_distance,
max_image_width=args.max_width,
max_image_height=args.max_height,
max_prediction_length=args.max_prediction,
channels=args.channels)
model.batch_predict(data_path=args.dataset)
