def testUpdateCheckpointStateSaveRelativePaths(self):
save_dir = self._get_test_dir("update_checkpoint_state")
os.chdir(save_dir)
abs_path2 = os.path.join(save_dir, "model-2")
rel_path2 = "model-2"
abs_path0 = os.path.join(save_dir, "model-0")
rel_path0 = "model-0"
checkpoint_management.update_checkpoint_state_internal(
save_dir=save_dir,
model_checkpoint_path=abs_path2,
all_model_checkpoint_paths=[rel_path0, abs_path2],
save_relative_paths=True)
# File should contain relative paths.
file_content = file_io.read_file_to_string(
os.path.join(save_dir, "checkpoint"))
ckpt = CheckpointState()
text_format.Merge(file_content, ckpt)
self.assertEqual(ckpt.model_checkpoint_path, rel_path2)
self.assertEqual(len(ckpt.all_model_checkpoint_paths), 2)
self.assertEqual(ckpt.all_model_checkpoint_paths[-1], rel_path2)
self.assertEqual(ckpt.all_model_checkpoint_paths[0], rel_path0)
# get_checkpoint_state should return absolute paths.
ckpt = checkpoint_management.get_checkpoint_state(save_dir)
self.assertEqual(ckpt.model_checkpoint_path, abs_path2)
self.assertEqual(len(ckpt.all_model_checkpoint_paths), 2)
self.assertEqual(ckpt.all_model_checkpoint_paths[-1], abs_path2)
self.assertEqual(ckpt.all_model_checkpoint_paths[0], abs_path0)
def testUpdateCheckpointStateSaveRelativePaths(self):
save_dir = self._get_test_dir("update_checkpoint_state")
os.chdir(save_dir)
abs_path2 = os.path.join(save_dir, "model-2")
rel_path2 = "model-2"
abs_path0 = os.path.join(save_dir, "model-0")
rel_path0 = "model-0"
checkpoint_management.update_checkpoint_state_internal(
save_dir=save_dir,
model_checkpoint_path=abs_path2,
all_model_checkpoint_paths=[rel_path0, abs_path2],
save_relative_paths=True)
# File should contain relative paths.
file_content = file_io.read_file_to_string(
os.path.join(save_dir, "checkpoint"))
ckpt = CheckpointState()
text_format.Merge(file_content, ckpt)
self.assertEqual(ckpt.model_checkpoint_path, rel_path2)
self.assertEqual(len(ckpt.all_model_checkpoint_paths), 2)
self.assertEqual(ckpt.all_model_checkpoint_paths[-1], rel_path2)
self.assertEqual(ckpt.all_model_checkpoint_paths[0], rel_path0)
# get_checkpoint_state should return absolute paths.
ckpt = checkpoint_management.get_checkpoint_state(save_dir)
self.assertEqual(ckpt.model_checkpoint_path, abs_path2)
self.assertEqual(len(ckpt.all_model_checkpoint_paths), 2)
self.assertEqual(ckpt.all_model_checkpoint_paths[-1], abs_path2)
self.assertEqual(ckpt.all_model_checkpoint_paths[0], abs_path0)
def save(self, file_prefix):
"""Saves a training checkpoint and provides basic checkpoint management.
The saved checkpoint includes variables created by this object and any
trackable objects it depends on at the time `Checkpoint.save()` is
called.
`save` is a basic convenience wrapper around the `write` method,
sequentially numbering checkpoints using `save_counter` and updating the
metadata used by `tf.train.latest_checkpoint`. More advanced checkpoint
management, for example garbage collection and custom numbering, may be
provided by other utilities which also wrap `write`
(`tf.train.CheckpointManager` for example).
Args:
file_prefix: A prefix to use for the checkpoint filenames
(/path/to/directory/and_a_prefix). Names are generated based on this
prefix and `Checkpoint.save_counter`.
Returns:
The full path to the checkpoint.
"""
graph_building = not context.executing_eagerly()
if graph_building:
if ops.inside_function():
raise NotImplementedError(
"Calling tf.train.Checkpoint.save() from a function is not "
"supported, as save() modifies saving metadata in ways not "
"supported by TensorFlow Operations. Consider using "
"tf.train.Checkpoint.write(), a lower-level API which does not "
"update metadata. tf.train.latest_checkpoint and related APIs will "
"not see this checkpoint.")
session = get_session()
if self._save_counter is None:
# When graph building, if this is a new save counter variable then it
# needs to be initialized before assign_add. This is only an issue if
# restore() has not been called first.
session.run(self.save_counter.initializer)
if not graph_building or self._save_assign_op is None:
with ops.colocate_with(self.save_counter):
assign_op = self.save_counter.assign_add(1, read_value=True)
if graph_building:
self._save_assign_op = data_structures.NoDependency(assign_op)
file_path = self.write(file_prefix)
checkpoint_management.update_checkpoint_state_internal(
save_dir=os.path.dirname(file_prefix),
model_checkpoint_path=file_path,
all_model_checkpoint_paths=[file_path],
save_relative_paths=True)
return file_path
def commit(self, prefix, session):
"""
Commit the latest checkpoint.
"""
if self._cached_checkpoint == None:
if len(self._checkpoints) > 0:
return self._checkpoints[-1]
else:
return ""
if len(self._checkpoints) == self._max_to_keep:
for filename in self._get_checkpoint_filenames(
self._checkpoints.pop(0)):
os.remove(filename)
# Replication from checkpoint.save
if self._checkpoint._save_counter is None:
session.run(self._checkpoint.save_counter.initializer)
if self._checkpoint._save_assign_op is None:
self._checkpoint._save_assign_op = data_structures.NoDependency(
self._checkpoint.save_counter.assign_add(1, read_value=True))
checkpoint_count = session.run(self._checkpoint._save_assign_op)
filename_prefix = "%s-%d" % (prefix, checkpoint_count)
for filename in self._get_checkpoint_filenames(
self._cached_checkpoint):
# Change prefix
os.rename(
filename,
filename.replace(self._cached_checkpoint, filename_prefix))
self._checkpoints.append(filename_prefix)
self._cached_checkpoint = None
# Update checkpoint state file (@tf.train.latest_checkpoint)
checkpoint_management.update_checkpoint_state_internal(
self._directory, self._checkpoints[-1], self._checkpoints)
return filename_prefix