def restore(self, sess, checkpoints):
vgg_network.vgg_assign_from_values_fn()(sess)
if checkpoints:
if not isinstance(checkpoints, (list, tuple)):
checkpoints = [checkpoints]
if len(checkpoints) != self.hparams.num_views:
raise ValueError(
'number of checkpoints should be equal to the number of views'
)
savers = []
for i, checkpoint in enumerate(checkpoints):
print("creating restore saver from checkpoint %s" % checkpoint)
restore_scope = 'view%d' % i
def restore_to_checkpoint_mapping(name):
name = name.split(':')[0]
assert name.split('/')[0] == restore_scope
name = '/'.join(name.split('/')[1:])
return name
saver, _ = tf_utils.get_checkpoint_restore_saver(
checkpoint,
restore_to_checkpoint_mapping=restore_to_checkpoint_mapping,
restore_scope=restore_scope)
savers.append(saver)
restore_op = [saver.saver_def.restore_op_name for saver in savers]
sess.run(restore_op)
def restore(self, sess, checkpoints):
vgg_network.vgg_assign_from_values_fn()(sess)
if checkpoints:
# possibly restore from multiple checkpoints. useful if subset of weights
# (e.g. generator or discriminator) are on different checkpoints.
if not isinstance(checkpoints, (list, tuple)):
checkpoints = [checkpoints]
# automatically skip global_step if more than one checkpoint is provided
skip_global_step = len(checkpoints) > 1
savers = []
for checkpoint in checkpoints:
print("creating restore saver from checkpoint %s" % checkpoint)
saver, _ = tf_utils.get_checkpoint_restore_saver(
checkpoint, skip_global_step=skip_global_step)
savers.append(saver)
restore_op = [saver.saver_def.restore_op_name for saver in savers]
sess.run(restore_op)
def restore(self, sess, checkpoints, restore_to_checkpoint_mapping=None):
if checkpoints:
var_list = self.saveable_variables
# possibly restore from multiple checkpoints. useful if subset of weights
# (e.g. generator or discriminator) are on different checkpoints.
if not isinstance(checkpoints, (list, tuple)):
checkpoints = [checkpoints]
# automatically skip global_step if more than one checkpoint is provided
skip_global_step = len(checkpoints) > 1
savers = []
for checkpoint in checkpoints:
print("creating restore saver from checkpoint %s" % checkpoint)
saver, _ = tf_utils.get_checkpoint_restore_saver(
checkpoint, var_list, skip_global_step=skip_global_step,
restore_to_checkpoint_mapping=restore_to_checkpoint_mapping)
savers.append(saver)
restore_op = [saver.saver_def.restore_op_name for saver in savers]
sess.run(restore_op)