def make_init_fn(self, chpt_path):
if chpt_path is None:
chpt_path = get_checkpoint_path(self.get_save_dir())
if chpt_path is None:
print('No checkpoint found for initialization')
return None
else:
print('Initializing from previous checkpoint: {}'.format(
chpt_path))
else:
print(
'Initializing from provided checkpoint: {}'.format(chpt_path))
var2restore = slim.get_variables_to_restore(
exclude=self.exclude_scopes)
print('Variables to restore: {}'.format(
[v.op.name for v in var2restore]))
var2restore = remove_missing(var2restore, chpt_path)
init_assign_op, init_feed_dict = slim.assign_from_checkpoint(
chpt_path, var2restore)
sys.stdout.flush()
# Create an initial assignment function.
def init_fn(sess):
sess.run(init_assign_op, init_feed_dict)
return init_fn
def cont_init_fn(self, chpt_path):
if chpt_path:
if self.reinit_fc:
var2restore = slim.get_variables_to_restore(
include=[
'encoder', 'decoder', 'generator', 'discriminator'
],
exclude=[
'discriminator/fully_connected', 'discriminator/fc1',
'discriminator/fc2'
])
else:
var2restore = slim.get_variables_to_restore(include=[
'encoder', 'decoder', 'generator', 'discriminator'
])
print('Variables to restore: {}'.format(
[v.op.name for v in var2restore]))
var2restore = remove_missing(var2restore, chpt_path)
init_assign_op, init_feed_dict = slim.assign_from_checkpoint(
chpt_path, var2restore)
sys.stdout.flush()
# Create an initial assignment function.
def InitAssignFn(sess):
sess.run(init_assign_op, init_feed_dict)
return InitAssignFn
else:
return None
def make_init_fn(self, chpt_path):
if chpt_path is None:
return None
var2restore = slim.get_variables_to_restore(include=['discriminator', 'generator'])
print('Variables to restore: {}'.format([v.op.name for v in var2restore]))
var2restore = remove_missing(var2restore, chpt_path)
init_assign_op, init_feed_dict = slim.assign_from_checkpoint(chpt_path, var2restore)
sys.stdout.flush()
# Create an initial assignment function.
def init_fn(sess):
print('Restoring from: {}'.format(chpt_path))
sess.run(init_assign_op, init_feed_dict)
return init_fn
def make_init_fn(self, chpt_path):
# Handle model initialization from prior checkpoint
if chpt_path is None:
return None
var2restore = slim.get_variables_to_restore(exclude=self.exclude_scopes)
print('Variables to restore: {}'.format([v.op.name for v in var2restore]))
var2restore = remove_missing(var2restore, chpt_path)
init_assign_op, init_feed_dict = slim.assign_from_checkpoint(chpt_path, var2restore)
sys.stdout.flush()
# Create an initial assignment function.
def init_fn(sess):
print('Restoring from: {}'.format(chpt_path))
sess.run(init_assign_op, init_feed_dict)
return init_fn
def make_init_fn(self, chpt_path):
if chpt_path is None:
ae_chpt_dir = os.path.join(
LOG_DIR, '{}_{}/'.format(self.model.ae.name,
self.dataset.name))
chpt_path = get_checkpoint_path(ae_chpt_dir)
var2restore = slim.get_variables_to_restore(
include=self.restore_scopes)
print('Variables to restore: {}'.format(
[v.op.name for v in var2restore]))
var2restore = remove_missing(var2restore, chpt_path)
init_assign_op, init_feed_dict = slim.assign_from_checkpoint(
chpt_path, var2restore)
sys.stdout.flush()
# Create an initial assignment function.
def init_fn(sess):
print('Restoring from: {}'.format(chpt_path))
sess.run(init_assign_op, init_feed_dict)
return init_fn