





import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__=True					,					SCREAMING_SNAKE_CASE__="pt")   ->    Tuple:
  __snake_case:						Tuple   =						{"""add_prefix_space""": True} if isinstance(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__) and not line.startswith(""" """) else {}
  __snake_case:						Any   =						padding_side
  return tokenizer(
      [line]					,					max_length=SCREAMING_SNAKE_CASE__					,					padding="""max_length""" if pad_to_max_length else None					,					truncation=SCREAMING_SNAKE_CASE__					,					return_tensors=SCREAMING_SNAKE_CASE__					,					add_special_tokens=SCREAMING_SNAKE_CASE__					,					**SCREAMING_SNAKE_CASE__					,					)







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__=None					,					)   ->    int:
  __snake_case:						List[Any]   =						input_ids.ne(SCREAMING_SNAKE_CASE__).any(dim=0)
  if attention_mask is None:
    return input_ids[:, keep_column_mask]
  else:
    return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])







class     __snake_case       (							__lowerCamelCase			):





       '''simple docstring'''







       def __init__(  self :    int							,				A :    Union[str, Any]							,				A :    Optional[Any]							,				A :    Tuple							,				A :    Optional[int]							,				A :    Dict="train"							,				A :    Optional[int]=None							,				A :    str=None							,				A :    List[str]=None							,				A :    Dict=""							,				):
         super().__init__()
         __snake_case:						Any   =						Path(A		).joinpath(type_path + """.source"""		)
         __snake_case:						List[str]   =						Path(A		).joinpath(type_path + """.target"""		)
         __snake_case:						Tuple   =						self.get_char_lens(self.src_file		)
         __snake_case:						List[str]   =						max_source_length
         __snake_case:						Any   =						max_target_length
         assert min(self.src_lens		) > 0, f'''found empty line in {self.src_file}'''
         __snake_case:						Dict   =						tokenizer
         __snake_case:						int   =						prefix
         if n_obs is not None:
           __snake_case:						int   =						self.src_lens[:n_obs]
         __snake_case:						str   =						src_lang
         __snake_case:						List[Any]   =						tgt_lang




       def __len__(  self :    Dict		):
         return len(self.src_lens		)




       def __getitem__(  self :    Optional[int]							,				A :    Any		):
         __snake_case:						List[str]   =						index + 1  # linecache starts at 1
         __snake_case:						int   =						self.prefix + linecache.getline(str(self.src_file		)							,				A		).rstrip("""\n"""		)
         __snake_case:						Dict   =						linecache.getline(str(self.tgt_file		)							,				A		).rstrip("""\n"""		)
         assert source_line, f'''empty source line for index {index}'''
         assert tgt_line, f'''empty tgt line for index {index}'''

         # Need to add eos token manually for T5
         if isinstance(self.tokenizer							,				A		):
           source_line += self.tokenizer.eos_token
           tgt_line += self.tokenizer.eos_token

         # Pad source and target to the right
         __snake_case:						int   =						(
             self.tokenizer.question_encoder if isinstance(self.tokenizer							,				A		) else self.tokenizer
         )
         __snake_case:						Optional[Any]   =						self.tokenizer.generator if isinstance(self.tokenizer							,				A		) else self.tokenizer

         __snake_case:						Tuple   =						encode_line(A							,				A							,				self.max_source_length							,				"""right"""		)
         __snake_case:						List[str]   =						encode_line(A							,				A							,				self.max_target_length							,				"""right"""		)

         __snake_case:						List[Any]   =						source_inputs["""input_ids"""].squeeze()
         __snake_case:						Optional[int]   =						target_inputs["""input_ids"""].squeeze()
         __snake_case:						Optional[int]   =						source_inputs["""attention_mask"""].squeeze()
         return {
             "input_ids": source_ids,
             "attention_mask": src_mask,
             "decoder_input_ids": target_ids,
         }




       @staticmethod
       def 							UpperCAmelCase__ (  A :    Dict		):
         return [len(A		) for x in Path(A		).open().readlines()]






       def 							UpperCAmelCase__ (  self :    Dict							,				A :    str		):
         __snake_case:						Dict   =						torch.stack([x["""input_ids"""] for x in batch]		)
         __snake_case:						int   =						torch.stack([x["""attention_mask"""] for x in batch]		)
         __snake_case:						Tuple   =						torch.stack([x["""decoder_input_ids"""] for x in batch]		)
         __snake_case:						int   =						(
             self.tokenizer.generator.pad_token_id
             if isinstance(self.tokenizer							,				A		)
             else self.tokenizer.pad_token_id
         )
         __snake_case:						Optional[Any]   =						(
             self.tokenizer.question_encoder.pad_token_id
             if isinstance(self.tokenizer							,				A		)
             else self.tokenizer.pad_token_id
         )
         __snake_case:						str   =						trim_batch(A							,				A		)
         __snake_case  ,   __snake_case:						Tuple   =						trim_batch(A							,				A							,				attention_mask=A		)
         __snake_case:						str   =						{
             """input_ids""": source_ids,
             """attention_mask""": source_mask,
             """decoder_input_ids""": y,
         }
         return batch






__UpperCAmelCase       :   int				       =							getLogger(__name__)







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    List[str]:
  return list(itertools.chain.from_iterable(SCREAMING_SNAKE_CASE__))







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    None:
  __snake_case:						List[Any]   =						get_git_info()
  save_json(SCREAMING_SNAKE_CASE__					,					os.path.join(SCREAMING_SNAKE_CASE__					,					"""git_log.json"""))







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__=4					,					**SCREAMING_SNAKE_CASE__)   ->    str:
  with open(SCREAMING_SNAKE_CASE__					,					"""w""") as f:
    json.dump(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					indent=SCREAMING_SNAKE_CASE__					,					**SCREAMING_SNAKE_CASE__)







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    Optional[int]:
  with open(SCREAMING_SNAKE_CASE__) as f:
    return json.load(SCREAMING_SNAKE_CASE__)







def 			A__							(    )   ->    Union[str, Any]:
  __snake_case:						str   =						git.Repo(search_parent_directories=SCREAMING_SNAKE_CASE__)
  __snake_case:						Tuple   =						{
      """repo_id""": str(SCREAMING_SNAKE_CASE__),
      """repo_sha""": str(repo.head.object.hexsha),
      """repo_branch""": str(repo.active_branch),
      """hostname""": str(socket.gethostname()),
  }
  return repo_infos







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    List:
  return list(map(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__))







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    Optional[Any]:
  with open(SCREAMING_SNAKE_CASE__					,					"""wb""") as f:
    return pickle.dump(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    Any:

  def remove_articles(SCREAMING_SNAKE_CASE__):
    return re.sub(r"""\b(a|an|the)\b"""					,					""" """					,					SCREAMING_SNAKE_CASE__)

  def white_space_fix(SCREAMING_SNAKE_CASE__):
    return " ".join(text.split())

  def remove_punc(SCREAMING_SNAKE_CASE__):
    __snake_case:						Any   =						set(string.punctuation)
    return "".join(ch for ch in text if ch not in exclude)

  def lower(SCREAMING_SNAKE_CASE__):
    return text.lower()

  return white_space_fix(remove_articles(remove_punc(lower(SCREAMING_SNAKE_CASE__))))







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    Optional[int]:
  __snake_case:						int   =						normalize_answer(SCREAMING_SNAKE_CASE__).split()
  __snake_case:						Any   =						normalize_answer(SCREAMING_SNAKE_CASE__).split()
  __snake_case:						Dict   =						Counter(SCREAMING_SNAKE_CASE__) & Counter(SCREAMING_SNAKE_CASE__)
  __snake_case:						Dict   =						sum(common.values())
  if num_same == 0:
    return 0
  __snake_case:						Union[str, Any]   =						1.0 * num_same / len(SCREAMING_SNAKE_CASE__)
  __snake_case:						int   =						1.0 * num_same / len(SCREAMING_SNAKE_CASE__)
  __snake_case:						str   =						(2 * precision * recall) / (precision + recall)
  return fa







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    Union[str, Any]:
  return normalize_answer(SCREAMING_SNAKE_CASE__) == normalize_answer(SCREAMING_SNAKE_CASE__)







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    Dict:
  assert len(SCREAMING_SNAKE_CASE__) == len(SCREAMING_SNAKE_CASE__)
  __snake_case:						List[Any]   =						0
  for hypo, pred in zip(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__):
    em += exact_match_score(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)
  if len(SCREAMING_SNAKE_CASE__) > 0:
    em /= len(SCREAMING_SNAKE_CASE__)
  return {"em": em}







def 			A__							(    SCREAMING_SNAKE_CASE__)   ->    Optional[int]:
  return model_prefix.startswith("""rag""")







def 			A__							(    SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)   ->    List[str]:
  __snake_case:						Dict   =						{p: p for p in extra_params}
  # T5 models don't have `dropout` param, they have `dropout_rate` instead
  __snake_case:						Dict   =						"""dropout_rate"""
  for p in extra_params:
    if getattr(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__):
      if not hasattr(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__) and not hasattr(SCREAMING_SNAKE_CASE__					,					equivalent_param[p]):
        logger.info("""config doesn't have a `{}` attribute""".format(SCREAMING_SNAKE_CASE__))
        delattr(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)
        continue
      __snake_case:						Dict   =						p if hasattr(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__) else equivalent_param[p]
      setattr(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__					,					getattr(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__))
      delattr(SCREAMING_SNAKE_CASE__					,					SCREAMING_SNAKE_CASE__)
  return hparams, config













def 			A__							(    SCREAMING_SNAKE_CASE__ = 200)   ->    int:
  __snake_case:						Optional[int]   =						[1, 2, 5, 10, 20, 50, 100, 200]
  __snake_case:						List[Any]   =						[0] * (pence + 1)
  __snake_case:						int   =						1  # base case: 1 way to make 0 pence

  for coin in coins:
    for i in range(SCREAMING_SNAKE_CASE__					,					pence + 1					,					1):
      number_of_ways[i] += number_of_ways[i - coin]
  return number_of_ways[pence]


if __name__ == "__main__":
      assert solution(200) == 73_682






