



"""simple docstring"""
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 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase=True ,  __lowerCAmelCase="pt"							) ->						List[str]:







  '''simple docstring'''


  lowercase_								= {"""add_prefix_space""": True} if isinstance(__lowerCAmelCase ,  __lowerCAmelCase							) and not line.startswith(""" """							) else {}
  lowercase_								= padding_side
  return tokenizer(
      [line] ,  max_length=__lowerCAmelCase ,  padding="""max_length""" if pad_to_max_length else None ,  truncation=__lowerCAmelCase ,  return_tensors=__lowerCAmelCase ,  add_special_tokens=__lowerCAmelCase ,  **__lowerCAmelCase ,  )


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase=None ,  ) ->						Optional[Any]:







  '''simple docstring'''


  lowercase_								= input_ids.ne(__lowerCAmelCase							).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    SCREAMING_SNAKE_CASE__ (							__UpperCAmelCase   ):

    def __init__(				self			:				Dict ,  lowerCAmelCase_			:				Optional[Any] ,  lowerCAmelCase_			:				str ,  lowerCAmelCase_			:				Optional[int] ,  lowerCAmelCase_			:				int ,  lowerCAmelCase_			:				Dict="train" ,  lowerCAmelCase_			:				Union[str, Any]=None ,  lowerCAmelCase_			:				Any=None ,  lowerCAmelCase_			:				Dict=None ,  lowerCAmelCase_			:				List[str]="" ,  ):







      """simple docstring"""







      super().__init__()
      lowercase_								= Path(lowerCAmelCase_).joinpath(type_path + """.source""")
      lowercase_								= Path(lowerCAmelCase_).joinpath(type_path + """.target""")
      lowercase_								= self.get_char_lens(self.src_file)
      lowercase_								= max_source_length
      lowercase_								= max_target_length
      assert min(self.src_lens) > 0, F'''found empty line in {self.src_file}'''
      lowercase_								= tokenizer
      lowercase_								= prefix
      if n_obs is not None:
        lowercase_								= self.src_lens[:n_obs]
      lowercase_								= src_lang
      lowercase_								= tgt_lang

    def __len__(				self			:				str):







      """simple docstring"""







      return len(self.src_lens)

    def __getitem__(				self			:				Optional[int] ,  lowerCAmelCase_			:				Optional[int]):







      """simple docstring"""







      lowercase_								= index + 1  # linecache starts at 1
      lowercase_								= self.prefix + linecache.getline(str(self.src_file) ,  lowerCAmelCase_).rstrip("""\n""")
      lowercase_								= linecache.getline(str(self.tgt_file) ,  lowerCAmelCase_).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 ,  lowerCAmelCase_):
        source_line += self.tokenizer.eos_token
        tgt_line += self.tokenizer.eos_token

      # Pad source and target to the right
      lowercase_								= (
          self.tokenizer.question_encoder if isinstance(self.tokenizer ,  lowerCAmelCase_) else self.tokenizer
      )
      lowercase_								= self.tokenizer.generator if isinstance(self.tokenizer ,  lowerCAmelCase_) else self.tokenizer

      lowercase_								= encode_line(lowerCAmelCase_ ,  lowerCAmelCase_ ,  self.max_source_length ,  """right""")
      lowercase_								= encode_line(lowerCAmelCase_ ,  lowerCAmelCase_ ,  self.max_target_length ,  """right""")

      lowercase_								= source_inputs["""input_ids"""].squeeze()
      lowercase_								= target_inputs["""input_ids"""].squeeze()
      lowercase_								= source_inputs["""attention_mask"""].squeeze()
      return {
          "input_ids": source_ids,
          "attention_mask": src_mask,
          "decoder_input_ids": target_ids,
      }

    @staticmethod
    def 					_UpperCAmelCase	(				lowerCAmelCase_			:				List[Any]):







      """simple docstring"""







      return [len(lowerCAmelCase_) for x in Path(lowerCAmelCase_).open().readlines()]




    def 					_UpperCAmelCase	(				self			:				Any ,  lowerCAmelCase_			:				Tuple):







      """simple docstring"""







      lowercase_								= torch.stack([x["""input_ids"""] for x in batch])
      lowercase_								= torch.stack([x["""attention_mask"""] for x in batch])
      lowercase_								= torch.stack([x["""decoder_input_ids"""] for x in batch])
      lowercase_								= (
          self.tokenizer.generator.pad_token_id
          if isinstance(self.tokenizer ,  lowerCAmelCase_)
          else self.tokenizer.pad_token_id
      )
      lowercase_								= (
          self.tokenizer.question_encoder.pad_token_id
          if isinstance(self.tokenizer ,  lowerCAmelCase_)
          else self.tokenizer.pad_token_id
      )
      lowercase_								= trim_batch(lowerCAmelCase_ ,  lowerCAmelCase_)
      lowercase_					,    lowercase_								= trim_batch(lowerCAmelCase_ ,  lowerCAmelCase_ ,  attention_mask=lowerCAmelCase_)
      lowercase_								= {
          """input_ids""": source_ids,
          """attention_mask""": source_mask,
          """decoder_input_ids""": y,
      }
      return batch







UpperCAmelCase						:		Any			= getLogger(__name__)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						str:







  '''simple docstring'''


  return list(itertools.chain.from_iterable(__lowerCAmelCase							)							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						None:







  '''simple docstring'''


  lowercase_								= get_git_info()
  save_json(__lowerCAmelCase ,  os.path.join(__lowerCAmelCase ,  """git_log.json"""							)							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase=4 ,  **__lowerCAmelCase							) ->						Any:







  '''simple docstring'''


  with open(__lowerCAmelCase ,  """w"""							) as f:
    json.dump(__lowerCAmelCase ,  __lowerCAmelCase ,  indent=__lowerCAmelCase ,  **__lowerCAmelCase							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						List[str]:







  '''simple docstring'''


  with open(__lowerCAmelCase							) as f:
    return json.load(__lowerCAmelCase							)


def 			_SCREAMING_SNAKE_CASE						() ->						Optional[int]:







  '''simple docstring'''


  lowercase_								= git.Repo(search_parent_directories=__lowerCAmelCase							)
  lowercase_								= {
      """repo_id""": str(__lowerCAmelCase							),
      """repo_sha""": str(repo.head.object.hexsha							),
      """repo_branch""": str(repo.active_branch							),
      """hostname""": str(socket.gethostname()							),
  }
  return repo_infos


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase							) ->						List:







  '''simple docstring'''


  return list(map(__lowerCAmelCase ,  __lowerCAmelCase							)							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase							) ->						int:







  '''simple docstring'''


  with open(__lowerCAmelCase ,  """wb"""							) as f:
    return pickle.dump(__lowerCAmelCase ,  __lowerCAmelCase							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						int:







  '''simple docstring'''


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

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

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

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

  return white_space_fix(remove_articles(remove_punc(lower(__lowerCAmelCase							)							)							)							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase							) ->						List[str]:







  '''simple docstring'''


  lowercase_								= normalize_answer(__lowerCAmelCase							).split()
  lowercase_								= normalize_answer(__lowerCAmelCase							).split()
  lowercase_								= Counter(__lowerCAmelCase							) & Counter(__lowerCAmelCase							)
  lowercase_								= sum(common.values()							)
  if num_same == 0:
    return 0
  lowercase_								= 1.0 * num_same / len(__lowerCAmelCase							)
  lowercase_								= 1.0 * num_same / len(__lowerCAmelCase							)
  lowercase_								= (2 * precision * recall) / (precision + recall)
  return fa


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase							) ->						List[Any]:







  '''simple docstring'''


  return normalize_answer(__lowerCAmelCase							) == normalize_answer(__lowerCAmelCase							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase							) ->						Dict:







  '''simple docstring'''


  assert len(__lowerCAmelCase							) == len(__lowerCAmelCase							)
  lowercase_								= 0
  for hypo, pred in zip(__lowerCAmelCase ,  __lowerCAmelCase							):
    em += exact_match_score(__lowerCAmelCase ,  __lowerCAmelCase							)
  if len(__lowerCAmelCase							) > 0:
    em /= len(__lowerCAmelCase							)
  return {"em": em}


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase							) ->						int:







  '''simple docstring'''


  return model_prefix.startswith("""rag"""							)


def 			_SCREAMING_SNAKE_CASE						(__lowerCAmelCase ,  __lowerCAmelCase ,  __lowerCAmelCase							) ->						Tuple:







  '''simple docstring'''


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






"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCAmelCase						:		Any			= {"configuration_xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XGLMConfig"]}

try:
       if not is_sentencepiece_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		List[str]			= ["XGLMTokenizer"]

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		Dict			= ["XGLMTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		Tuple			= [
           "XGLM_PRETRAINED_MODEL_ARCHIVE_LIST",
           "XGLMForCausalLM",
           "XGLMModel",
           "XGLMPreTrainedModel",
       ]


try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		int			= [
           "FlaxXGLMForCausalLM",
           "FlaxXGLMModel",
           "FlaxXGLMPreTrainedModel",
       ]


try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase						:		List[str]			= [
           "TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST",
           "TFXGLMForCausalLM",
           "TFXGLMModel",
           "TFXGLMPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_xglm import XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP, XGLMConfig

       try:
              if not is_sentencepiece_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_xglm import XGLMTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_xglm_fast import XGLMTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_xglm import XGLM_PRETRAINED_MODEL_ARCHIVE_LIST, XGLMForCausalLM, XGLMModel, XGLMPreTrainedModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_xglm import FlaxXGLMForCausalLM, FlaxXGLMModel, FlaxXGLMPreTrainedModel

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_xglm import (
                  TF_XGLM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFXGLMForCausalLM,
                  TFXGLMModel,
                  TFXGLMPreTrainedModel,
              )


else:
       import sys

       UpperCAmelCase						:		Any			= _LazyModule(__name__, globals()["__file__"], _import_structure)

