


# 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   _UpperCAmelCase       (     UpperCAmelCase      :			Dict=None      ):
      """simple docstring"""




      if subparsers is not None:
            __lowerCamelCase     :      List[str]       						=						subparsers.add_parser("""test"""      )
      else:
            __lowerCamelCase     :      str       						=						argparse.ArgumentParser("""Accelerate test command"""      )

      parser.add_argument(
          """--config_file"""						,	default=UpperCAmelCase						,	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=UpperCAmelCase      )
      return parser





def   _UpperCAmelCase       (     UpperCAmelCase      :			int      ):
      """simple docstring"""




      __lowerCamelCase     :      str       						=						os.path.sep.join(__file__.split(os.path.sep      )[:-2] + ["""test_utils""", """scripts""", """test_script.py"""]      )

      if args.config_file is None:
            __lowerCamelCase     :      List[str]       						=						script_name
      else:
            __lowerCamelCase     :      Optional[Any]       						=						f"""--config_file={args.config_file} {script_name}"""

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





def   _UpperCAmelCase       (     ):
      """simple docstring"""




      __lowerCamelCase     :      int       						=						test_command_parser()
      __lowerCamelCase     :      List[str]       						=						parser.parse_args()
      test_command(UpperCAmelCase      )


if __name__ == "__main__":
    main()







import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer





def   _UpperCAmelCase       (     UpperCAmelCase      :			Any						,	UpperCAmelCase      :			int						,	UpperCAmelCase      :			int						,	UpperCAmelCase      :			Any=1_024      ):
      """simple docstring"""




      __lowerCamelCase						, __lowerCamelCase     :      str       						=						[], []

      __lowerCamelCase     :      Any       						=						list(zip(UpperCAmelCase						,	UpperCAmelCase      )      )
      __lowerCamelCase						, __lowerCamelCase     :      List[str]       						=						sorted_examples[0]

      def is_too_big(UpperCAmelCase      :			Optional[Any]      ):
            return tok(UpperCAmelCase						,	return_tensors="""pt"""      ).input_ids.shape[1] > max_tokens

      for src, tgt in tqdm(sorted_examples[1:]      ):
            __lowerCamelCase     :      Union[str, Any]       						=						new_src + """ """ + src
            __lowerCamelCase     :      str       						=						new_tgt + """ """ + tgt
            if is_too_big(UpperCAmelCase      ) or is_too_big(UpperCAmelCase      ):  # cant fit, finalize example
                  finished_src.append(UpperCAmelCase      )
                  finished_tgt.append(UpperCAmelCase      )
                  __lowerCamelCase						, __lowerCamelCase     :      str       						=						src, tgt
            else:  # can fit, keep adding
                  __lowerCamelCase						, __lowerCamelCase     :      int       						=						cand_src, cand_tgt

    # cleanup
      if new_src:
            assert new_tgt
            finished_src.append(UpperCAmelCase      )
            finished_tgt.append(UpperCAmelCase      )
      return finished_src, finished_tgt





def   _UpperCAmelCase       (     UpperCAmelCase      :			Tuple						,	UpperCAmelCase      :			Path						,	UpperCAmelCase      :			Dict						,	UpperCAmelCase      :			Optional[Any]      ):
      """simple docstring"""




      __lowerCamelCase     :      List[Any]       						=						Path(UpperCAmelCase      )
      save_path.mkdir(exist_ok=UpperCAmelCase      )
      for split in ["train"]:
            __lowerCamelCase						, __lowerCamelCase     :      List[Any]       						=						data_dir / f"""{split}.source""", data_dir / f"""{split}.target"""
            __lowerCamelCase     :      Tuple       						=						[x.rstrip() for x in Path(UpperCAmelCase      ).open().readlines()]
            __lowerCamelCase     :      Tuple       						=						[x.rstrip() for x in Path(UpperCAmelCase      ).open().readlines()]
            __lowerCamelCase						, __lowerCamelCase     :      int       						=						pack_examples(UpperCAmelCase						,	UpperCAmelCase						,	UpperCAmelCase						,	UpperCAmelCase      )
            print(f"""packed {split} split from {len(UpperCAmelCase      )} examples -> {len(UpperCAmelCase      )}."""      )
            Path(save_path / f"""{split}.source"""      ).open("""w"""      ).write("""\n""".join(UpperCAmelCase      )      )
            Path(save_path / f"""{split}.target"""      ).open("""w"""      ).write("""\n""".join(UpperCAmelCase      )      )
      for split in ["val", "test"]:
            __lowerCamelCase						, __lowerCamelCase     :      Optional[Any]       						=						data_dir / f"""{split}.source""", data_dir / f"""{split}.target"""
            shutil.copyfile(UpperCAmelCase						,	save_path / f"""{split}.source"""      )
            shutil.copyfile(UpperCAmelCase						,	save_path / f"""{split}.target"""      )





def   _UpperCAmelCase       (     ):
      """simple docstring"""




      __lowerCamelCase     :      List[Any]       						=						argparse.ArgumentParser()
      parser.add_argument("""--tok_name"""						,	type=UpperCAmelCase						,	help="""like facebook/bart-large-cnn,t5-base, etc."""      )
      parser.add_argument("""--max_seq_len"""						,	type=UpperCAmelCase						,	default=128      )
      parser.add_argument("""--data_dir"""						,	type=UpperCAmelCase      )
      parser.add_argument("""--save_path"""						,	type=UpperCAmelCase      )
      __lowerCamelCase     :      Union[str, Any]       						=						parser.parse_args()
      __lowerCamelCase     :      Tuple       						=						AutoTokenizer.from_pretrained(args.tok_name      )
      return pack_data_dir(UpperCAmelCase						,	Path(args.data_dir      )						,	args.max_seq_len						,	args.save_path      )


if __name__ == "__main__":
    packer_cli()



