def test_can_write_and_read_default_opts(config_file_args, minimal_args):
config_file_path = config_file_args[1]
parser = build_parser()
default_options = vars(parser.parse(args=minimal_args).all_options)
save_args_to_file(file_name=config_file_path, **default_options)
try:
loaded_options = parser.parse(config_file_args).all_options
except Exception as e:
raised_exception = e
loaded_options = None
else:
raised_exception = None
assert raised_exception is None
assert loaded_options.source_max_length == float('inf')
assert loaded_options.target_max_length == float('inf')
loaded_options = vars(loaded_options)
del loaded_options['config']
del default_options['config']
for key, value in loaded_options.items():
assert key in default_options
assert value == default_options[key]
del default_options[key]
assert not default_options
def build_parser():
return HyperPipelineParser(
name='jackknife',
pipeline_parser=train.build_parser(),
pipeline_config_key='train-config',
options_fn=jackknife_opts,
)
def train_from_file(filename):
"""
Loads options from a config file and calls the training procedure.
Args:
filename (str): filename of the configuration file
"""
parser = build_parser()
options = parser.parse_config_file(filename)
return train_from_options(options)