def testSerialization(self):
original = Resources(1, 0, 0, 1, custom_resources={"a": 1, "b": 2})
jsoned = resources_to_json(original)
new_resource = json_to_resources(jsoned)
self.assertEquals(original, new_resource)
def create_trial_from_spec(spec: dict, output_path: str,
parser: argparse.ArgumentParser, **trial_kwargs):
"""Creates a Trial object from parsing the spec.
Args:
spec: A resolved experiment specification. Arguments should
The args here should correspond to the command line flags
in ray.tune.experiment.config_parser.
output_path: A specific output path within the local_dir.
Typically the name of the experiment.
parser: An argument parser object from
make_parser.
trial_kwargs: Extra keyword arguments used in instantiating the Trial.
Returns:
A trial object with corresponding parameters to the specification.
"""
global _cached_pgf
spec = spec.copy()
resources = spec.pop("resources_per_trial", None)
try:
args, _ = parser.parse_known_args(to_argv(spec))
except SystemExit:
raise TuneError("Error parsing args, see above message", spec)
if resources:
if isinstance(resources, PlacementGroupFactory):
trial_kwargs["placement_group_factory"] = resources
else:
# This will be converted to a placement group factory in the
# Trial object constructor
try:
trial_kwargs["resources"] = json_to_resources(resources)
except (TuneError, ValueError) as exc:
raise TuneError("Error parsing resources_per_trial",
resources) from exc
remote_checkpoint_dir = spec.get("remote_checkpoint_dir")
sync_config = spec.get("sync_config", SyncConfig())
if (sync_config.syncer is None or sync_config.syncer == "auto"
or isinstance(sync_config.syncer, Syncer)):
custom_syncer = sync_config.syncer
else:
raise ValueError(
f"Unknown syncer type passed in SyncConfig: {type(sync_config.syncer)}. "
f"Note that custom sync functions and templates have been deprecated. "
f"Instead you can implement you own `Syncer` class. "
f"Please leave a comment on GitHub if you run into any issues with this: "
f"https://github.com/ray-project/ray/issues")
return Trial(
# Submitting trial via server in py2.7 creates Unicode, which does not
# convert to string in a straightforward manner.
trainable_name=spec["run"],
# json.load leads to str -> unicode in py2.7
config=spec.get("config", {}),
local_dir=os.path.join(spec["local_dir"], output_path),
# json.load leads to str -> unicode in py2.7
stopping_criterion=spec.get("stop", {}),
remote_checkpoint_dir=remote_checkpoint_dir,
custom_syncer=custom_syncer,
checkpoint_freq=args.checkpoint_freq,
checkpoint_at_end=args.checkpoint_at_end,
sync_on_checkpoint=sync_config.sync_on_checkpoint,
keep_checkpoints_num=args.keep_checkpoints_num,
checkpoint_score_attr=args.checkpoint_score_attr,
export_formats=spec.get("export_formats", []),
# str(None) doesn't create None
restore_path=spec.get("restore"),
trial_name_creator=spec.get("trial_name_creator"),
trial_dirname_creator=spec.get("trial_dirname_creator"),
log_to_file=spec.get("log_to_file"),
# str(None) doesn't create None
max_failures=args.max_failures,
**trial_kwargs,
)
def create_trial_from_spec(spec: dict, output_path: str,
parser: argparse.ArgumentParser, **trial_kwargs):
"""Creates a Trial object from parsing the spec.
Args:
spec: A resolved experiment specification. Arguments should
The args here should correspond to the command line flags
in ray.tune.config_parser.
output_path: A specific output path within the local_dir.
Typically the name of the experiment.
parser: An argument parser object from
make_parser.
trial_kwargs: Extra keyword arguments used in instantiating the Trial.
Returns:
A trial object with corresponding parameters to the specification.
"""
global _cached_pgf
spec = spec.copy()
resources = spec.pop("resources_per_trial", None)
try:
args, _ = parser.parse_known_args(to_argv(spec))
except SystemExit:
raise TuneError("Error parsing args, see above message", spec)
if resources:
if isinstance(resources, PlacementGroupFactory):
trial_kwargs["placement_group_factory"] = resources
else:
# This will be converted to a placement group factory in the
# Trial object constructor
try:
trial_kwargs["resources"] = json_to_resources(resources)
except (TuneError, ValueError) as exc:
raise TuneError("Error parsing resources_per_trial",
resources) from exc
remote_checkpoint_dir = spec.get("remote_checkpoint_dir")
sync_config = spec.get("sync_config", SyncConfig())
if sync_config.syncer is None or isinstance(sync_config.syncer, str):
sync_function_tpl = sync_config.syncer
elif not isinstance(sync_config.syncer, str):
# If a syncer was specified, but not a template, it is a function.
# Functions cannot be used for trial checkpointing on remote nodes,
# so we set the remote checkpoint dir to None to disable this.
sync_function_tpl = None
remote_checkpoint_dir = None
else:
sync_function_tpl = None # Auto-detect
return Trial(
# Submitting trial via server in py2.7 creates Unicode, which does not
# convert to string in a straightforward manner.
trainable_name=spec["run"],
# json.load leads to str -> unicode in py2.7
config=spec.get("config", {}),
local_dir=os.path.join(spec["local_dir"], output_path),
# json.load leads to str -> unicode in py2.7
stopping_criterion=spec.get("stop", {}),
remote_checkpoint_dir=remote_checkpoint_dir,
sync_function_tpl=sync_function_tpl,
checkpoint_freq=args.checkpoint_freq,
checkpoint_at_end=args.checkpoint_at_end,
sync_on_checkpoint=sync_config.sync_on_checkpoint,
keep_checkpoints_num=args.keep_checkpoints_num,
checkpoint_score_attr=args.checkpoint_score_attr,
export_formats=spec.get("export_formats", []),
# str(None) doesn't create None
restore_path=spec.get("restore"),
trial_name_creator=spec.get("trial_name_creator"),
trial_dirname_creator=spec.get("trial_dirname_creator"),
log_to_file=spec.get("log_to_file"),
# str(None) doesn't create None
max_failures=args.max_failures,
**trial_kwargs)
def create_trial_from_spec(spec, output_path, parser, **trial_kwargs):
"""Creates a Trial object from parsing the spec.
Arguments:
spec (dict): A resolved experiment specification. Arguments should
The args here should correspond to the command line flags
in ray.tune.config_parser.
output_path (str); A specific output path within the local_dir.
Typically the name of the experiment.
parser (ArgumentParser): An argument parser object from
make_parser.
trial_kwargs: Extra keyword arguments used in instantiating the Trial.
Returns:
A trial object with corresponding parameters to the specification.
"""
global _cached_pgf
spec = spec.copy()
resources = spec.pop("resources_per_trial", None)
try:
args, _ = parser.parse_known_args(to_argv(spec))
except SystemExit:
raise TuneError("Error parsing args, see above message", spec)
if resources:
if isinstance(resources, PlacementGroupFactory):
trial_kwargs["placement_group_factory"] = resources
elif callable(resources):
if resources in _cached_pgf:
trial_kwargs["placement_group_factory"] = _cached_pgf[
resources]
else:
pgf = PlacementGroupFactory(resources)
_cached_pgf[resources] = pgf
trial_kwargs["placement_group_factory"] = pgf
else:
try:
trial_kwargs["resources"] = json_to_resources(resources)
except (TuneError, ValueError) as exc:
raise TuneError("Error parsing resources_per_trial",
resources) from exc
return Trial(
# Submitting trial via server in py2.7 creates Unicode, which does not
# convert to string in a straightforward manner.
trainable_name=spec["run"],
# json.load leads to str -> unicode in py2.7
config=spec.get("config", {}),
local_dir=os.path.join(spec["local_dir"], output_path),
# json.load leads to str -> unicode in py2.7
stopping_criterion=spec.get("stop", {}),
remote_checkpoint_dir=spec.get("remote_checkpoint_dir"),
checkpoint_freq=args.checkpoint_freq,
checkpoint_at_end=args.checkpoint_at_end,
sync_on_checkpoint=args.sync_on_checkpoint,
keep_checkpoints_num=args.keep_checkpoints_num,
checkpoint_score_attr=args.checkpoint_score_attr,
export_formats=spec.get("export_formats", []),
# str(None) doesn't create None
restore_path=spec.get("restore"),
trial_name_creator=spec.get("trial_name_creator"),
trial_dirname_creator=spec.get("trial_dirname_creator"),
log_to_file=spec.get("log_to_file"),
# str(None) doesn't create None
max_failures=args.max_failures,
**trial_kwargs)
