def initialize_trainer_provider(task, trainer_opts, provider_opts, _run):
storage_dir = Path(trainer_opts['storage_dir'])
if (storage_dir / 'init.json').exists():
assert task in ['restart', 'validate'], task
elif task in ['train', 'create_checkpoint']:
dump_json(
dict(trainer_opts=recursive_class_to_str(trainer_opts),
provider_opts=recursive_class_to_str(provider_opts)),
storage_dir / 'init.json')
else:
raise ValueError(task, storage_dir)
sacred.commands.print_config(_run)
trainer = Trainer.from_config(trainer_opts)
assert isinstance(trainer, Trainer)
provider = config_to_instance(provider_opts)
return trainer, provider
def write_makefile_and_config(
storage_dir,
_config,
_run,
backend='yaml',
write_config=True,
write_makefile=True,
):
"""
Writes a Makefile and a config file in the storage_dir to resume the
Experiment.
Args:
storage_dir:
_config:
_run:
backend:
Returns:
"""
from padertorch.configurable import recursive_class_to_str
if backend == 'json':
config_path = Path(storage_dir) / "config.json"
if write_config:
pb.io.dump_json(recursive_class_to_str(_config), config_path)
elif backend == 'yaml':
config_path = Path(storage_dir) / "config.yaml"
if write_config:
pb.io.dump_yaml(_config, config_path)
else:
raise ValueError(backend)
if write_makefile:
makefile_path = Path(storage_dir) / "Makefile"
module_name = pt.configurable.resolve_main_python_path()
makefile_path.write_text(
"resume:\n"
f"\tpython -m {module_name} "
f"resume with {config_path.name}\n"
)