# ******************************************************************************
# Copyright 2017-2019 Intel Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ******************************************************************************
# CLI definition
import argparse
from argparse import _SubParsersAction
from nlp_architect.cli.cmd_registry import CMD_REGISTRY
from nlp_architect.version import NLP_ARCHITECT_VERSION
[docs]def nlp_train_cli():
prog_name = "nlp-train"
desc = "NLP Architect Train CLI [{}]".format(NLP_ARCHITECT_VERSION)
parser = argparse.ArgumentParser(description=desc, prog=prog_name)
parser.add_argument(
"-v", "--version", action="version", version="%(prog)s v{}".format(NLP_ARCHITECT_VERSION)
)
parser.set_defaults(func=lambda _: parser.print_help())
subparsers = parser.add_subparsers(title="Models", metavar="")
for model in CMD_REGISTRY["train"]:
sp = subparsers.add_parser(
model["name"], description=model["description"], help=model["description"]
)
model["arg_adder"](sp)
sp.set_defaults(func=model["fn"])
args = parser.parse_args()
if hasattr(args, "func"):
args.func(args)
else:
parser.print_help()
[docs]def nlp_inference_cli():
prog_name = "nlp-inference"
desc = "NLP Architect Inference CLI [{}]".format(NLP_ARCHITECT_VERSION)
parser = argparse.ArgumentParser(description=desc, prog=prog_name)
parser.add_argument(
"-v", "--version", action="version", version="%(prog)s v{}".format(NLP_ARCHITECT_VERSION)
)
parser.set_defaults(func=lambda _: parser.print_help())
subparsers = parser.add_subparsers(title="Models", metavar="")
for model in CMD_REGISTRY["inference"]:
sp = subparsers.add_parser(
model["name"], description=model["description"], help=model["description"]
)
model["arg_adder"](sp)
sp.set_defaults(func=model["fn"])
args = parser.parse_args()
if hasattr(args, "func"):
args.func(args)
else:
parser.print_help()
[docs]def generic_cmd(cmd_name: str, subtitle: str, description: str, subparsers: _SubParsersAction):
parser = subparsers.add_parser(cmd_name, description=description, help=description)
subsubparsers = parser.add_subparsers(title=subtitle, metavar="")
for model in CMD_REGISTRY[cmd_name]:
sp = subsubparsers.add_parser(
model["name"], description=model["description"], help=model["description"]
)
model["arg_adder"](sp)
sp.set_defaults(func=model["fn"])
parser.set_defaults(func=lambda _: parser.print_help())
[docs]def cli_train_cmd(subparsers: _SubParsersAction):
generic_cmd("train", "Available models", "Train a model from the library", subparsers)
[docs]def cli_run_cmd(subparsers: _SubParsersAction):
generic_cmd("run", "Available models", "Run a model from the library", subparsers)