def setup_embedding_initializer(self): """Sets up the function to restore embedding variables from checkpoint.""" embed_config = self.model_config['embed_config'] if embed_config['embedding_checkpoint_file']: # Restore Siamese FC models from .mat model files initialize = load_mat_model(embed_config['embedding_checkpoint_file'], 'convolutional_alexnet/', 'detection/') def restore_fn(sess): tf.logging.info("Restoring embedding variables from checkpoint file %s", embed_config['embedding_checkpoint_file']) sess.run([initialize]) self.init_fn = restore_fn
def setup_embedding_initializer(self): """Sets up the function to restore embedding variables from checkpoint.""" embed_config = self.model_config['embed_config'] if embed_config['embedding_checkpoint_file']: # Restore Siamese FC models from .mat model files initialize = load_mat_model(embed_config['embedding_checkpoint_file'], 'sa_siam/appearance_net/', 'detection/') def restore_fn(sess): tf.logging.info("Restoring embedding variables from checkpoint file %s", embed_config['embedding_checkpoint_file']) sess.run([initialize]) self.init_fn = restore_fn