


import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer


def 			UpperCAmelCase_				(      UpperCAmelCase__						,							UpperCAmelCase__						,							UpperCAmelCase__						,							UpperCAmelCase__=1_0_2_4  ):
					lowercase_							,					lowercase_  							=			[], []

					lowercase_  							=			list(zip(UpperCAmelCase__						,							UpperCAmelCase__  )  )
					lowercase_							,					lowercase_  							=			sorted_examples[0]

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

					for src, tgt in tqdm(sorted_examples[1:]  ):
										lowercase_  							=			new_src + """ """ + src
										lowercase_  							=			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__  )
															lowercase_							,					lowercase_  							=			src, tgt
										else:  # can fit, keep adding
															lowercase_							,					lowercase_  							=			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__						,							UpperCAmelCase__						,							UpperCAmelCase__						,							UpperCAmelCase__  ):
					lowercase_  							=			Path(UpperCAmelCase__  )
					save_path.mkdir(exist_ok=UpperCAmelCase__  )
					for split in ["train"]:
										lowercase_							,					lowercase_  							=			data_dir / F'''{split}.source''', data_dir / F'''{split}.target'''
										lowercase_  							=			[x.rstrip() for x in Path(UpperCAmelCase__  ).open().readlines()]
										lowercase_  							=			[x.rstrip() for x in Path(UpperCAmelCase__  ).open().readlines()]
										lowercase_							,					lowercase_  							=			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"]:
										lowercase_							,					lowercase_  							=			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_				(      ):
					lowercase_  							=			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=1_2_8  )
					parser.add_argument("""--data_dir"""						,							type=UpperCAmelCase__  )
					parser.add_argument("""--save_path"""						,							type=UpperCAmelCase__  )
					lowercase_  							=			parser.parse_args()
					lowercase_  							=			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()






# Copyright 2022 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
import platform

import numpy as np
import psutil
import torch

from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file

from ..utils import is_npu_available, is_xpu_available


def 			UpperCAmelCase_				(      UpperCAmelCase__=None  ):
					if subparsers is not None:
										lowercase_  							=			subparsers.add_parser("""env"""  )
					else:
										lowercase_  							=			argparse.ArgumentParser("""Accelerate env command"""  )

					parser.add_argument(
					    """--config_file"""						,							default=UpperCAmelCase__						,							help="""The config file to use for the default values in the launching script."""  )

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


def 			UpperCAmelCase_				(      UpperCAmelCase__  ):
					lowercase_  							=			torch.__version__
					lowercase_  							=			torch.cuda.is_available()
					lowercase_  							=			is_xpu_available()
					lowercase_  							=			is_npu_available()

					lowercase_  							=			"""Not found"""
					# Get the default from the config file.
					if args.config_file is not None or os.path.isfile(UpperCAmelCase__  ):
										lowercase_  							=			load_config_from_file(args.config_file  ).to_dict()

					lowercase_  							=			{
					    """`Accelerate` version""": version,
					    """Platform""": platform.platform(),
					    """Python version""": platform.python_version(),
					    """Numpy version""": np.__version__,
					    """PyTorch version (GPU?)""": F'''{pt_version} ({pt_cuda_available})''',
					    """PyTorch XPU available""": str(UpperCAmelCase__  ),
					    """PyTorch NPU available""": str(UpperCAmelCase__  ),
					    """System RAM""": F'''{psutil.virtual_memory().total / 1_0_2_4 ** 3:.2f} GB''',
					}
					if pt_cuda_available:
										lowercase_  							=			torch.cuda.get_device_name()

					print("""\nCopy-and-paste the text below in your GitHub issue\n"""  )
					print("""\n""".join([F'''- {prop}: {val}''' for prop, val in info.items()]  )  )

					print("""- `Accelerate` default config:""" if args.config_file is None else """- `Accelerate` config passed:"""  )
					lowercase_  							=			(
					    """\n""".join([F'''\t- {prop}: {val}''' for prop, val in accelerate_config.items()]  )
					    if isinstance(UpperCAmelCase__						,							UpperCAmelCase__  )
					    else F'''\t{accelerate_config}'''
					)
					print(UpperCAmelCase__  )

					lowercase_  							=			accelerate_config

					return info


def 			UpperCAmelCase_				(      ):
					lowercase_  							=			env_command_parser()
					lowercase_  							=			parser.parse_args()
					env_command(UpperCAmelCase__  )
					return 0


if __name__ == "__main__":
							raise SystemExit(main())


