



"""simple docstring"""






# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# 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.

import argparse
import os

from accelerate.test_utils import execute_subprocess_async


def     _lowercase       (						__snake_case=None			)		->     Tuple:
			if subparsers is not None:
						__lowerCAmelCase   :						Optional[Any]				= subparsers.add_parser("test"			)
			else:
						__lowerCAmelCase   :						Tuple				= argparse.ArgumentParser("Accelerate test command"			)

			parser.add_argument(
			    "--config_file"      ,default=__snake_case      ,help=(
			        "The path to use to store the config file. Will default to a file named default_config.yaml in the cache "
			        "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have "
			        "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed "
			        "with 'huggingface'."
			    )      ,)

			if subparsers is not None:
						parser.set_defaults(func=__snake_case			)
			return parser


def     _lowercase       (						__snake_case			)		->     Dict:
			__lowerCAmelCase   :						Optional[int]				= os.path.sep.join(__file__.split(os.path.sep			)[:-2] + ["test_utils", "scripts", "test_script.py"]			)

			if args.config_file is None:
						__lowerCAmelCase   :						Any				= script_name
			else:
						__lowerCAmelCase   :						List[str]				= F"""--config_file={args.config_file} {script_name}"""

			__lowerCAmelCase   :						str				= ["accelerate-launch"] + test_args.split()
			__lowerCAmelCase   :						Optional[Any]				= execute_subprocess_async(__snake_case      ,env=os.environ.copy()			)
			if result.returncode == 0:
						print("Test is a success! You are ready for your distributed training!"			)


def     _lowercase       (						)		->     Optional[Any]:
			__lowerCAmelCase   :						Union[str, Any]				= test_command_parser()
			__lowerCAmelCase   :						Union[str, Any]				= parser.parse_args()
			test_command(__snake_case			)


if __name__ == "__main__":
	main()




"""simple docstring"""






import string
from math import logaa


def     _lowercase       (						__snake_case      ,__snake_case			)		->     int:
			__lowerCAmelCase   :						int				= document.translate(
			    str.maketrans(""      ,""      ,string.punctuation			)			).replace("\n"      ,""			)
			__lowerCAmelCase   :						Dict				= document_without_punctuation.split(" "			)  # word tokenization
			return len([word for word in tokenize_document if word.lower() == term.lower()]			)


def     _lowercase       (						__snake_case      ,__snake_case			)		->     tuple[int, int]:
			__lowerCAmelCase   :						Optional[Any]				= corpus.lower().translate(
			    str.maketrans(""      ,""      ,string.punctuation			)			)  # strip all punctuation and replace it with ''
			__lowerCAmelCase   :						List[str]				= corpus_without_punctuation.split("\n"			)
			__lowerCAmelCase   :						str				= term.lower()
			return (len([doc for doc in docs if term in doc]			), len(__snake_case			))


def     _lowercase       (						__snake_case      ,__snake_case      ,__snake_case=False			)		->     float:
			if smoothing:
						if n == 0:
									raise ValueError("log10(0) is undefined."			)
						return round(1 + logaa(n / (1 + df)			)      ,3			)

			if df == 0:
						raise ZeroDivisionError("df must be > 0"			)
			elif n == 0:
						raise ValueError("log10(0) is undefined."			)
			return round(logaa(n / df			)      ,3			)





def     _lowercase       (						__snake_case      ,__snake_case			)		->     float:
			return round(tf * idf      ,3			)