


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   _UpperCAmelCase       (     UpperCAmelCase      :			str						,	UpperCAmelCase      :			List[str]						,	UpperCAmelCase      :			Dict						,	UpperCAmelCase      :			List[Any]						,	UpperCAmelCase      :			Optional[Any]=True						,	UpperCAmelCase      :			Any="pt"      ):
      """simple docstring"""




      __lowerCamelCase     :      List[str]       						=						{"""add_prefix_space""": True} if isinstance(UpperCAmelCase						,	UpperCAmelCase      ) and not line.startswith(""" """      ) else {}
      __lowerCamelCase     :      Optional[Any]       						=						padding_side
      return tokenizer(
          [line]						,	max_length=UpperCAmelCase						,	padding="""max_length""" if pad_to_max_length else None						,	truncation=UpperCAmelCase						,	return_tensors=UpperCAmelCase						,	add_special_tokens=UpperCAmelCase						,	**UpperCAmelCase						,	)





def   _UpperCAmelCase       (     UpperCAmelCase      :			Tuple						,	UpperCAmelCase      :			List[Any]						,	UpperCAmelCase      :			Dict=None						,	):
      """simple docstring"""




      __lowerCamelCase     :      Union[str, Any]       						=						input_ids.ne(UpperCAmelCase      ).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 							_UpperCamelCase (						A						):

   '''simple docstring'''







   def __init__(  self  : Optional[Any]       ,  _lowerCamelCase  : Tuple       ,  _lowerCamelCase  : Optional[Any]       ,  _lowerCamelCase  : Union[str, Any]       ,  _lowerCamelCase  : Any       ,  _lowerCamelCase  : List[Any]="train"       ,  _lowerCamelCase  : Union[str, Any]=None       ,  _lowerCamelCase  : Union[str, Any]=None       ,  _lowerCamelCase  : str=None       ,  _lowerCamelCase  : List[Any]=""       ,  ):






         '''simple docstring'''



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

   def __len__(  self  : List[str]							):






         '''simple docstring'''



         return len(self.src_lens							)

   def __getitem__(  self  : Any       ,  _lowerCamelCase  : Any							):






         '''simple docstring'''



         __lowerCamelCase     :      Optional[int]       						=						index + 1  # linecache starts at 1
         __lowerCamelCase     :      List[str]       						=						self.prefix + linecache.getline(str(self.src_file							)       ,  _lowerCamelCase							).rstrip("""\n"""							)
         __lowerCamelCase     :      Union[str, Any]       						=						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
         __lowerCamelCase     :      List[str]       						=						(
             self.tokenizer.question_encoder if isinstance(self.tokenizer       ,  _lowerCamelCase							) else self.tokenizer
         )
         __lowerCamelCase     :      Dict       						=						self.tokenizer.generator if isinstance(self.tokenizer       ,  _lowerCamelCase							) else self.tokenizer

         __lowerCamelCase     :      List[Any]       						=						encode_line(_lowerCamelCase       ,  _lowerCamelCase       ,  self.max_source_length       ,  """right"""							)
         __lowerCamelCase     :      List[Any]       						=						encode_line(_lowerCamelCase       ,  _lowerCamelCase       ,  self.max_target_length       ,  """right"""							)

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

   @staticmethod
   def   _snake_case    (  _lowerCamelCase  : Any							):






         '''simple docstring'''



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


   def   _snake_case    (  self  : Optional[Any]       ,  _lowerCamelCase  : Optional[Any]							):






         '''simple docstring'''



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

__UpperCamelCase    :						Any     =							getLogger(__name__)





def   _UpperCAmelCase       (     UpperCAmelCase      :			List[List]      ):
      """simple docstring"""




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





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




      __lowerCamelCase     :      str       						=						get_git_info()
      save_json(UpperCAmelCase						,	os.path.join(UpperCAmelCase						,	"""git_log.json"""      )      )





def   _UpperCAmelCase       (     UpperCAmelCase      :			Union[str, Any]						,	UpperCAmelCase      :			Dict						,	UpperCAmelCase      :			Any=4						,	**UpperCAmelCase      :			Tuple      ):
      """simple docstring"""




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





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




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





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




      __lowerCamelCase     :      List[Any]       						=						git.Repo(search_parent_directories=UpperCAmelCase      )
      __lowerCamelCase     :      Any       						=						{
          """repo_id""": str(UpperCAmelCase      ),
          """repo_sha""": str(repo.head.object.hexsha      ),
          """repo_branch""": str(repo.active_branch      ),
          """hostname""": str(socket.gethostname()      ),
      }
      return repo_infos





def   _UpperCAmelCase       (     UpperCAmelCase      :			Callable						,	UpperCAmelCase      :			Iterable      ):
      """simple docstring"""




      return list(map(UpperCAmelCase						,	UpperCAmelCase      )      )





def   _UpperCAmelCase       (     UpperCAmelCase      :			Optional[int]						,	UpperCAmelCase      :			Optional[Any]      ):
      """simple docstring"""




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





def   _UpperCAmelCase       (     UpperCAmelCase      :			Optional[int]      ):
      """simple docstring"""




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

      def white_space_fix(UpperCAmelCase      :			Any      ):
            return " ".join(text.split()      )

      def remove_punc(UpperCAmelCase      :			Dict      ):
            __lowerCamelCase     :      Union[str, Any]       						=						set(string.punctuation      )
            return "".join(ch for ch in text if ch not in exclude      )

      def lower(UpperCAmelCase      :			Union[str, Any]      ):
            return text.lower()

      return white_space_fix(remove_articles(remove_punc(lower(UpperCAmelCase      )      )      )      )





def   _UpperCAmelCase       (     UpperCAmelCase      :			str						,	UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      Optional[Any]       						=						normalize_answer(UpperCAmelCase      ).split()
      __lowerCamelCase     :      Dict       						=						normalize_answer(UpperCAmelCase      ).split()
      __lowerCamelCase     :      List[Any]       						=						Counter(UpperCAmelCase      ) & Counter(UpperCAmelCase      )
      __lowerCamelCase     :      Optional[Any]       						=						sum(common.values()      )
      if num_same == 0:
            return 0
      __lowerCamelCase     :      List[Any]       						=						1.0 * num_same / len(UpperCAmelCase      )
      __lowerCamelCase     :      Optional[Any]       						=						1.0 * num_same / len(UpperCAmelCase      )
      __lowerCamelCase     :      Union[str, Any]       						=						(2 * precision * recall) / (precision + recall)
      return fa





def   _UpperCAmelCase       (     UpperCAmelCase      :			Optional[int]						,	UpperCAmelCase      :			Dict      ):
      """simple docstring"""




      return normalize_answer(UpperCAmelCase      ) == normalize_answer(UpperCAmelCase      )





def   _UpperCAmelCase       (     UpperCAmelCase      :			List[str]						,	UpperCAmelCase      :			List[str]      ):
      """simple docstring"""




      assert len(UpperCAmelCase      ) == len(UpperCAmelCase      )
      __lowerCamelCase     :      Union[str, Any]       						=						0
      for hypo, pred in zip(UpperCAmelCase						,	UpperCAmelCase      ):
            em += exact_match_score(UpperCAmelCase						,	UpperCAmelCase      )
      if len(UpperCAmelCase      ) > 0:
            em /= len(UpperCAmelCase      )
      return {"em": em}





def   _UpperCAmelCase       (     UpperCAmelCase      :			List[Any]      ):
      """simple docstring"""




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





def   _UpperCAmelCase       (     UpperCAmelCase      :			List[str]						,	UpperCAmelCase      :			Dict						,	UpperCAmelCase      :			Optional[Any]      ):
      """simple docstring"""




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







# Copyright 2023 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.
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCamelCase    :						Any     =							{
    'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
    'processing_mgp_str': ['MgpstrProcessor'],
    'tokenization_mgp_str': ['MgpstrTokenizer'],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						Tuple     =							[
        'MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST',
        'MgpstrModel',
        'MgpstrPreTrainedModel',
        'MgpstrForSceneTextRecognition',
    ]

if TYPE_CHECKING:
    from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
    from .processing_mgp_str import MgpstrProcessor
    from .tokenization_mgp_str import MgpstrTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mgp_str import (
            MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
            MgpstrForSceneTextRecognition,
            MgpstrModel,
            MgpstrPreTrainedModel,
        )
else:
    import sys

    __UpperCamelCase    :						Optional[Any]     =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



