def setup_args():
"""Setup saving arguments."""
parser = argparse.ArgumentParser()
models.add_cmdline_args(parser)
tasks.add_cmdline_args(parser)
parser.add_argument("--inference_model_path", type=str, required=True)
args = parse_args(parser)
args.load(args.config_path, "Model")
args.run_infer = True # only build infer program
args.display()
return args
def setup_args():
"""Setup arguments."""
parser = argparse.ArgumentParser()
parser.add_argument("--is_distributed", type=str2bool, default=False)
parser.add_argument("--port", type=int, default=18123)
models.add_cmdline_args(parser)
DialogGeneration.add_cmdline_args(parser)
args = parse_args(parser)
args.load(args.config_path, "Model")
args.run_infer = True # only build infer program
args.display()
return args
def setup_args():
"""Setup inference arguments."""
parser = argparse.ArgumentParser()
parser.add_argument("--is_distributed", type=str2bool, default=False)
parser.add_argument("--save_path", type=str, default="output")
parser.add_argument("--infer_file", type=str, required=True)
parser.add_argument("--output_name", type=str, required=True)
parser.add_argument("--log_steps", type=int, default=1)
models.add_cmdline_args(parser)
tasks.add_cmdline_args(parser)
args = parse_args(parser)
args.load(args.config_path, "Model")
args.run_infer = True # only build infer program
args.display()
return args
def setup_args():
"""Setup arguments."""
parser = argparse.ArgumentParser(
description="Main inference program for dialogue state tracking.")
parser.add_argument("--infer_file", type=str, required=True)
parser.add_argument("--save_path", type=str, required=True)
parser.add_argument("--dataset",
type=str,
default="multiwoz",
choices=["multiwoz", "woz"])
parser.add_argument("--dial_batch_size", type=int, default=32)
models.add_cmdline_args(parser)
tasks.add_cmdline_args(parser)
args = parse_args(parser)
args.load(args.config_path, "Model")
args.run_infer = True # only build infer program
args.display()
return args
def setup_args():
"""Setup evaluation arguments."""
parser = argparse.ArgumentParser()
parser.add_argument("--is_distributed", type=str2bool, default=False,
help="Whether to run distributed evaluation.")
parser.add_argument("--save_path", type=str, default="output",
help="The path where to save temporary files.")
parser.add_argument("--eval_file", type=str, required=True,
help="The evaluation dataset: file / filelist. "
"See more details in `docs/usage.md`: `file_format`.")
parser.add_argument("--log_steps", type=int, default=100,
help="Display evaluation log information every X steps.")
models.add_cmdline_args(parser)
tasks.add_cmdline_args(parser)
args = parse_args(parser)
args.load(args.config_path, "Model")
args.display()
return args
def setup_args():
"""Setup arguments."""
parser = argparse.ArgumentParser(
description="Main dynamic inference program.")
parser.add_argument("--infer_file", type=str, required=True)
parser.add_argument("--save_path", type=str, default="output")
parser.add_argument("--db_file", type=str, required=True)
parser.add_argument("--session_to_sample_mapping_file",
type=str,
required=True)
parser.add_argument("--dial_batch_size", type=int, default=8)
parser.add_argument("--normalization", type=str2bool, default=True)
parser.add_argument("--db_guidance", type=str2bool, default=True)
models.add_cmdline_args(parser)
DialogGeneration.add_cmdline_args(parser)
args = parse_args(parser)
args.load(args.config_path, "Model")
args.run_infer = True # only build infer program
args.display()
return args
def setup_args():
"""Setup training arguments."""
parser = argparse.ArgumentParser()
parser.add_argument("--is_distributed", type=str2bool, default=False,
help="Whether to run distributed training.")
parser.add_argument("--save_path", type=str, default="output",
help="The path where to save models.")
parser.add_argument("--train_file", type=str, required=True,
help="The training dataset: file / filelist. "
"See more details in `docs/usage.md`: `file_format`.")
parser.add_argument("--valid_file", type=str, required=True,
help="The validation datasets: files / filelists. "
"The files / filelists are separated by `,`. "
"See more details in `docs/usage.md`: `file_format`.")
parser.add_argument("--start_step", type=int, default=0,
help="The start step of training. It will be updated if you load from a checkpoint.")
parser.add_argument("--num_epochs", type=int, default=20,
help="The number of times that the learning algorithm will work through the entire training dataset.")
parser.add_argument("--log_steps", type=int, default=100,
help="Display training / evaluation log information every X steps.")
parser.add_argument("--validation_steps", type=int, default=1000,
help="Run validation every X training steps.")
parser.add_argument("--save_steps", type=int, default=0,
help="Save the lastest model every X training steps. "
"If `save_steps = 0`, then it only keep the lastest checkpoint.")
parser.add_argument("--eval_metric", type=str, default="-loss",
help="Keep the checkpoint with best evaluation metric.")
parser.add_argument("--save_checkpoint", type=str2bool, default=True,
help="Save completed checkpoint or parameters only. "
"The checkpoint contains all states for continuous training.")
models.add_cmdline_args(parser)
tasks.add_cmdline_args(parser)
args = parse_args(parser)
args.load(args.config_path, "Model")
args.display()
return args
