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