def add_interactive_args(parser):
parser.add_argument("-u",
"--nlu",
type=str,
default=None,
help="trained nlu model")
parser.add_argument(
"--endpoints",
default=None,
help="Configuration file for the connectors as a yml file",
)
parser.add_argument(
"--skip_visualization",
default=False,
action="store_true",
help="disables plotting the visualization during interactive learning",
)
parser.add_argument(
"--finetune",
default=False,
action="store_true",
help="retrain the model immediately based on feedback.",
)
arguments.add_output_arg(
parser,
help_text="directory to persist the trained model in",
required=False)
arguments.add_config_arg(parser, nargs=1)
arguments.add_model_and_story_group(parser, allow_pretrained_model=True)
arguments.add_domain_arg(parser, required=False)
def add_train_args(parser):
arguments.add_config_arg(parser, nargs=1)
arguments.add_output_arg(
parser,
help_text="directory to persist the trained model in",
required=True)
arguments.add_model_and_story_group(parser, allow_pretrained_model=False)
arguments.add_domain_arg(parser, required=True)
def add_compare_args(parser):
parser.add_argument('--percentages',
nargs="*",
type=int,
default=[0, 5, 25, 50, 70, 90, 95],
help="Range of exclusion percentages")
parser.add_argument('--runs',
type=int,
default=3,
help="Number of runs for experiments")
arguments.add_output_arg(
parser,
help_text="directory to persist the trained model in",
required=True)
arguments.add_config_arg(parser, nargs="*")
arguments.add_model_and_story_group(parser, allow_pretrained_model=False)
arguments.add_domain_arg(parser, required=True)
