





"""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 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE=True	,  _SCREAMING_SNAKE_CASE="pt"     )   ->List[str]:





  """simple docstring"""


  lowerCAmelCase__     :List[Any]											=				{'add_prefix_space': True} if isinstance(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     ) and not line.startswith(' '     ) else {}
  lowerCAmelCase__     :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	,  )   ->List[Any]:





  """simple docstring"""


  lowerCAmelCase__     :Dict											=				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    _lowerCAmelCase  (	a			):
       """simple docstring"""




       def __init__(       self       ,					__UpperCAmelCase       ,					__UpperCAmelCase       ,					__UpperCAmelCase       ,					__UpperCAmelCase       ,					__UpperCAmelCase="train"       ,					__UpperCAmelCase=None       ,					__UpperCAmelCase=None       ,					__UpperCAmelCase=None       ,					__UpperCAmelCase=""       ,					):



         '''simple docstring'''

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






       def __len__(       self ):



         '''simple docstring'''

         return len(self.src_lens )






       def __getitem__(       self       ,					__UpperCAmelCase ):



         '''simple docstring'''

         lowerCAmelCase__     :Any											=				index + 1  # linecache starts at 1
         lowerCAmelCase__     :Any											=				self.prefix + linecache.getline(str(self.src_file )       ,					__UpperCAmelCase ).rstrip('\n' )
         lowerCAmelCase__     :Dict											=				linecache.getline(str(self.tgt_file )       ,					__UpperCAmelCase ).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       ,					__UpperCAmelCase ):
           source_line += self.tokenizer.eos_token
           tgt_line += self.tokenizer.eos_token

         # Pad source and target to the right
         lowerCAmelCase__     :str											=				(
             self.tokenizer.question_encoder if isinstance(self.tokenizer       ,					__UpperCAmelCase ) else self.tokenizer
         )
         lowerCAmelCase__     :int											=				self.tokenizer.generator if isinstance(self.tokenizer       ,					__UpperCAmelCase ) else self.tokenizer

         lowerCAmelCase__     :str											=				encode_line(__UpperCAmelCase       ,					__UpperCAmelCase       ,					self.max_source_length       ,					'right' )
         lowerCAmelCase__     :Optional[Any]											=				encode_line(__UpperCAmelCase       ,					__UpperCAmelCase       ,					self.max_target_length       ,					'right' )

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






       @staticmethod
       def 	snake_case		(       __UpperCAmelCase ):



         '''simple docstring'''

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






       def 	snake_case		(       self       ,					__UpperCAmelCase ):



         '''simple docstring'''

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






__A											=						getLogger(__name__)
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->Optional[int]:





  """simple docstring"""


  return list(itertools.chain.from_iterable(_SCREAMING_SNAKE_CASE     )     )
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->None:





  """simple docstring"""


  lowerCAmelCase__     :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     )   ->Optional[Any]:





  """simple docstring"""


  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[Any]:





  """simple docstring"""


  with open(_SCREAMING_SNAKE_CASE     ) as f:
    return json.load(_SCREAMING_SNAKE_CASE     )
def 					__A  ()   ->List[Any]:





  """simple docstring"""


  lowerCAmelCase__     :Any											=				git.Repo(search_parent_directories=_SCREAMING_SNAKE_CASE     )
  lowerCAmelCase__     :int											=				{
      '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:





  """simple docstring"""


  return list(map(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Dict:





  """simple docstring"""


  with open(_SCREAMING_SNAKE_CASE	,  'wb'     ) as f:
    return pickle.dump(_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )
def 					__A  (_SCREAMING_SNAKE_CASE     )   ->Tuple:





  """simple docstring"""


  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     ):
    lowerCAmelCase__     :Optional[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[Any]:





  """simple docstring"""


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





  """simple docstring"""


  return normalize_answer(_SCREAMING_SNAKE_CASE     ) == normalize_answer(_SCREAMING_SNAKE_CASE     )
def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Dict:





  """simple docstring"""


  assert len(_SCREAMING_SNAKE_CASE     ) == len(_SCREAMING_SNAKE_CASE     )
  lowerCAmelCase__     :Optional[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     )   ->Tuple:





  """simple docstring"""


  return model_prefix.startswith('rag'     )




def 					__A  (_SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE	,  _SCREAMING_SNAKE_CASE     )   ->Any:





  """simple docstring"""


  lowerCAmelCase__     :Union[str, Any]											=				{p: p for p in extra_params}
  # T5 models don't have `dropout` param, they have `dropout_rate` instead
  lowerCAmelCase__     :Union[str, Any]											=				'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
      lowerCAmelCase__     :int											=				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







"""simple docstring"""





import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


__A											=						"""sshleifer/bart-tiny-random"""
__A											=						"""patrickvonplaten/t5-tiny-random"""






@require_torch
class    _lowerCAmelCase  (	unittest.TestCase			):
       """simple docstring"""




       @cached_property
       def 	snake_case		(       self ):



         '''simple docstring'''

         return AutoConfig.from_pretrained(__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :List[str]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=1 )
         self.assertEqual(student.config.num_hidden_layers       ,					1 )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :Optional[int]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=__UpperCAmelCase )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :List[Any]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=__UpperCAmelCase )
         self.assertEqual(student.config.encoder_layers       ,					1 )
         self.assertEqual(student.config.decoder_layers       ,					self.teacher_config.encoder_layers )






       def 	snake_case		(       self ):



         '''simple docstring'''

         lowerCAmelCase__				,							*lowerCAmelCase__     :Optional[int]											=				create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=1       ,					d=1 )
         self.assertEqual(student.config.encoder_layers       ,					1 )
         self.assertEqual(student.config.decoder_layers       ,					1 )






       def 	snake_case		(       self ):



         '''simple docstring'''

         with self.assertRaises(__UpperCAmelCase ):
           create_student_by_copying_alternating_layers(__UpperCAmelCase       ,					tempfile.mkdtemp()       ,					e=__UpperCAmelCase       ,					d=__UpperCAmelCase )
