'''simple docstring'''

import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
  UpperCamelCase__     :	int				=			'pt'
elif is_tf_available():
  UpperCamelCase__     :	Optional[Any]				=			'tf'
else:
  UpperCamelCase__     :	Dict				=			'jax'


class 				_lowercase	(      lowerCAmelCase		,unittest.TestCase   ):
      '''simple docstring'''


      UpperCAmelCase_      :      Optional[int]      							=   ByTaTokenizer
      UpperCAmelCase_      :      Union[str, Any]      							=   False




      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         super().setUp()
         UpperCAmelCase__							:				Optional[int]   				=  ByTaTokenizer()
         tokenizer.save_pretrained(self.tmpdirname							)




      @cached_property
      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         return ByTaTokenizer.from_pretrained('''google/byt5-small'''							)




      def 		lowerCAmelCase__					(				self					,**lowerCamelCase_							)			->			ByTaTokenizer:



         '''simple docstring'''



         return self.tokenizer_class.from_pretrained(self.tmpdirname					,**lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_					,lowerCamelCase_=False					,lowerCamelCase_=20					,lowerCamelCase_=5							)			->			Tuple[str, list]:



         '''simple docstring'''



         UpperCAmelCase__							:				Union[str, Any]   				=  []
         for i in range(len(lowerCamelCase_							)							):
            try:
               UpperCAmelCase__							:				Any   				=  tokenizer.decode([i]					,clean_up_tokenization_spaces=lowerCamelCase_							)
            except UnicodeDecodeError:
               pass
            toks.append((i, tok)							)

         UpperCAmelCase__							:				str   				=  list(filter(lambda lowerCamelCase_							: re.match(r'''^[ a-zA-Z]+$'''					,t[1]							)					,lowerCamelCase_							)							)
         UpperCAmelCase__							:				Tuple   				=  list(filter(lambda lowerCamelCase_							: [t[0]] == tokenizer.encode(t[1]					,add_special_tokens=lowerCamelCase_							)					,lowerCamelCase_							)							)
         if max_length is not None and len(lowerCamelCase_							) > max_length:
            UpperCAmelCase__							:				List[str]   				=  toks[:max_length]
         if min_length is not None and len(lowerCamelCase_							) < min_length and len(lowerCamelCase_							) > 0:
            while len(lowerCamelCase_							) < min_length:
               UpperCAmelCase__							:				Union[str, Any]   				=  toks + toks
        # toks_str = [t[1] for t in toks]
         UpperCAmelCase__							:				int   				=  [t[0] for t in toks]

         # Ensure consistency
         UpperCAmelCase__							:				Optional[Any]   				=  tokenizer.decode(lowerCamelCase_					,clean_up_tokenization_spaces=lowerCamelCase_							)
         if " " not in output_txt and len(lowerCamelCase_							) > 1:
            UpperCAmelCase__							:				Dict   				=  (
                tokenizer.decode([toks_ids[0]]					,clean_up_tokenization_spaces=lowerCamelCase_							)
                + ''' '''
                + tokenizer.decode(toks_ids[1:]					,clean_up_tokenization_spaces=lowerCamelCase_							)
            )
         if with_prefix_space:
            UpperCAmelCase__							:				Union[str, Any]   				=  ''' ''' + output_txt
         UpperCAmelCase__							:				Dict   				=  tokenizer.encode(lowerCamelCase_					,add_special_tokens=lowerCamelCase_							)
         return output_txt, output_ids




      def 		lowerCAmelCase__					(				self							)			->			Optional[int]:



         '''simple docstring'''



         UpperCAmelCase__							:				str   				=  self.ta_base_tokenizer
         UpperCAmelCase__							:				Any   				=  tokenizer(['''hi</s>''', '''I went to the gym</s>''', '''</s>''']							)
         UpperCAmelCase__							:				List[Any]   				=  tokenizer(['''hi''', '''I went to the gym''', '''''']							)
         self.assertListEqual(batch_with_eos_added['''input_ids''']					,batch_without_eos_added['''input_ids''']							)




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         UpperCAmelCase__							:				List[str]   				=  self.ta_base_tokenizer
         UpperCAmelCase__							:				Dict   				=  '''Unicode €.'''
         UpperCAmelCase__							:				Tuple   				=  tokenizer(lowerCamelCase_							)
         UpperCAmelCase__							:				int   				=  [88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
         self.assertEqual(encoded['''input_ids''']					,lowerCamelCase_							)

         # decoding
         UpperCAmelCase__							:				Optional[Any]   				=  tokenizer.decode(lowerCamelCase_							)
         self.assertEqual(lowerCamelCase_					,'''Unicode €.</s>'''							)

         UpperCAmelCase__							:				Optional[Any]   				=  tokenizer('''e è é ê ë'''							)
         UpperCAmelCase__							:				Optional[int]   				=  [104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
         self.assertEqual(encoded['''input_ids''']					,lowerCamelCase_							)
         # decoding
         UpperCAmelCase__							:				Tuple   				=  tokenizer.decode(lowerCamelCase_							)
         self.assertEqual(lowerCamelCase_					,'''e è é ê ë</s>'''							)

         # encode/decode, but with `encode` instead of `__call__`
         self.assertEqual(tokenizer.decode(tokenizer.encode('''e è é ê ë'''							)							)					,'''e è é ê ë</s>'''							)




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         UpperCAmelCase__							:				Any   				=  self.ta_base_tokenizer
         UpperCAmelCase__							:				str   				=  ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         # fmt: off
         UpperCAmelCase__							:				Dict   				=  [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
         # fmt: on
         UpperCAmelCase__							:				List[Any]   				=  tokenizer(lowerCamelCase_					,padding=lowerCamelCase_					,return_tensors=lowerCamelCase_							)
         self.assertIsInstance(lowerCamelCase_					,lowerCamelCase_							)

         if FRAMEWORK != "jax":
            UpperCAmelCase__							:				List[str]   				=  list(batch.input_ids.numpy()[0]							)
         else:
            UpperCAmelCase__							:				int   				=  list(batch.input_ids.tolist()[0]							)

         self.assertListEqual(lowerCamelCase_					,lowerCamelCase_							)

         self.assertEqual((2, 37)					,batch.input_ids.shape							)
         self.assertEqual((2, 37)					,batch.attention_mask.shape							)




      def 		lowerCAmelCase__					(				self							)			->			Tuple:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[int]   				=  self.ta_base_tokenizer
         UpperCAmelCase__							:				int   				=  ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
         UpperCAmelCase__							:				Any   				=  tokenizer(lowerCamelCase_					,padding=lowerCamelCase_					,return_tensors=lowerCamelCase_							)
         # check if input_ids are returned and no decoder_input_ids
         self.assertIn('''input_ids'''					,lowerCamelCase_							)
         self.assertIn('''attention_mask'''					,lowerCamelCase_							)
         self.assertNotIn('''decoder_input_ids'''					,lowerCamelCase_							)
         self.assertNotIn('''decoder_attention_mask'''					,lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self							)			->			str:



         '''simple docstring'''



         UpperCAmelCase__							:				Union[str, Any]   				=  self.ta_base_tokenizer
         UpperCAmelCase__							:				List[Any]   				=  [
             '''Summary of the text.''',
             '''Another summary.''',
         ]
         UpperCAmelCase__							:				Any   				=  tokenizer(
             text_target=lowerCamelCase_					,max_length=32					,padding='''max_length'''					,truncation=lowerCamelCase_					,return_tensors=lowerCamelCase_							)
         self.assertEqual(32					,targets['''input_ids'''].shape[1]							)




      def 		lowerCAmelCase__					(				self							)			->			Optional[int]:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[int]   				=  self.ta_base_tokenizer
         UpperCAmelCase__							:				Union[str, Any]   				=  ['''A long paragraph for summarization. </s>''']
         UpperCAmelCase__							:				Any   				=  ['''Summary of the text. </s>''']
         # fmt: off
         UpperCAmelCase__							:				Optional[Any]   				=  [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
         UpperCAmelCase__							:				List[str]   				=  [86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
         # fmt: on

         UpperCAmelCase__							:				Union[str, Any]   				=  tokenizer(lowerCamelCase_					,text_target=lowerCamelCase_							)

         self.assertEqual(lowerCamelCase_					,batch['''input_ids'''][0]							)
         self.assertEqual(lowerCamelCase_					,batch['''labels'''][0]							)




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         UpperCAmelCase__							:				Tuple   				=  self.get_tokenizers()
         for tokenizer in tokenizers:
            with self.subTest(f'''{tokenizer.__class__.__name__}'''							):
               self.assertNotEqual(tokenizer.model_max_length					,42							)

        # Now let's start the test
         UpperCAmelCase__							:				Any   				=  self.get_tokenizers()
         for tokenizer in tokenizers:
            with self.subTest(f'''{tokenizer.__class__.__name__}'''							):
               # Isolate this from the other tests because we save additional tokens/etc
               UpperCAmelCase__							:				Union[str, Any]   				=  tempfile.mkdtemp()

               UpperCAmelCase__							:				List[Any]   				=  ''' He is very happy, UNwant\u00E9d,running'''
               UpperCAmelCase__							:				Any   				=  tokenizer.encode(lowerCamelCase_					,add_special_tokens=lowerCamelCase_							)
               tokenizer.save_pretrained(lowerCamelCase_							)

               UpperCAmelCase__							:				Any   				=  tokenizer.__class__.from_pretrained(lowerCamelCase_							)
               UpperCAmelCase__							:				Union[str, Any]   				=  after_tokenizer.encode(lowerCamelCase_					,add_special_tokens=lowerCamelCase_							)
               self.assertListEqual(lowerCamelCase_					,lowerCamelCase_							)

               shutil.rmtree(lowerCamelCase_							)

         UpperCAmelCase__							:				Optional[int]   				=  self.get_tokenizers(model_max_length=42							)
         for tokenizer in tokenizers:
            with self.subTest(f'''{tokenizer.__class__.__name__}'''							):
               # Isolate this from the other tests because we save additional tokens/etc
               UpperCAmelCase__							:				List[str]   				=  tempfile.mkdtemp()

               UpperCAmelCase__							:				int   				=  ''' He is very happy, UNwant\u00E9d,running'''
               tokenizer.add_tokens(['''bim''', '''bambam''']							)
               UpperCAmelCase__							:				Dict   				=  tokenizer.additional_special_tokens
               additional_special_tokens.append('''new_additional_special_token'''							)
               tokenizer.add_special_tokens({'''additional_special_tokens''': additional_special_tokens}							)
               UpperCAmelCase__							:				List[str]   				=  tokenizer.encode(lowerCamelCase_					,add_special_tokens=lowerCamelCase_							)
               tokenizer.save_pretrained(lowerCamelCase_							)

               UpperCAmelCase__							:				int   				=  tokenizer.__class__.from_pretrained(lowerCamelCase_							)
               UpperCAmelCase__							:				Optional[int]   				=  after_tokenizer.encode(lowerCamelCase_					,add_special_tokens=lowerCamelCase_							)
               self.assertListEqual(lowerCamelCase_					,lowerCamelCase_							)
               self.assertIn('''new_additional_special_token'''					,after_tokenizer.additional_special_tokens							)
               self.assertEqual(after_tokenizer.model_max_length					,42							)

               UpperCAmelCase__							:				Optional[Any]   				=  tokenizer.__class__.from_pretrained(lowerCamelCase_					,model_max_length=43							)
               self.assertEqual(tokenizer.model_max_length					,43							)

               shutil.rmtree(lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self							)			->			int:



         '''simple docstring'''



         UpperCAmelCase__							:				Tuple   				=  []
         if self.test_slow_tokenizer:
            tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())							)

         if self.test_rust_tokenizer:
            tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())							)

         for tokenizer_class, tokenizer_utils in tokenizer_list:
            with tempfile.TemporaryDirectory() as tmp_dir:
               tokenizer_utils.save_pretrained(lowerCamelCase_							)

               with open(os.path.join(lowerCamelCase_					,'''special_tokens_map.json'''							)					,encoding='''utf-8'''							) as json_file:
                  UpperCAmelCase__							:				List[Any]   				=  json.load(lowerCamelCase_							)

               with open(os.path.join(lowerCamelCase_					,'''tokenizer_config.json'''							)					,encoding='''utf-8'''							) as json_file:
                  UpperCAmelCase__							:				Tuple   				=  json.load(lowerCamelCase_							)

               UpperCAmelCase__							:				Optional[int]   				=  [f'''<extra_id_{i}>''' for i in range(125							)]

               UpperCAmelCase__							:				Any   				=  added_tokens_extra_ids + [
                   '''an_additional_special_token'''
               ]
               UpperCAmelCase__							:				str   				=  added_tokens_extra_ids + [
                   '''an_additional_special_token'''
               ]

               with open(os.path.join(lowerCamelCase_					,'''special_tokens_map.json'''							)					,'''w'''					,encoding='''utf-8'''							) as outfile:
                  json.dump(lowerCamelCase_					,lowerCamelCase_							)
               with open(os.path.join(lowerCamelCase_					,'''tokenizer_config.json'''							)					,'''w'''					,encoding='''utf-8'''							) as outfile:
                  json.dump(lowerCamelCase_					,lowerCamelCase_							)

               # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
               # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
               # "special_tokens_map.json" files
               UpperCAmelCase__							:				str   				=  tokenizer_class.from_pretrained(
                   lowerCamelCase_					,)
               self.assertIn(
                   '''an_additional_special_token'''					,tokenizer_without_change_in_init.additional_special_tokens							)
               # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
               self.assertEqual(
                   ['''an_additional_special_token''']					,tokenizer_without_change_in_init.convert_ids_to_tokens(
                       tokenizer_without_change_in_init.convert_tokens_to_ids(['''an_additional_special_token''']							)							)					,)

               # Now we test that we can change the value of additional_special_tokens in the from_pretrained
               UpperCAmelCase__							:				Optional[int]   				=  added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''					,lstrip=lowerCamelCase_							)]
               UpperCAmelCase__							:				Any   				=  tokenizer_class.from_pretrained(
                   lowerCamelCase_					,additional_special_tokens=lowerCamelCase_					,)

               self.assertIn('''a_new_additional_special_token'''					,tokenizer.additional_special_tokens							)
               self.assertEqual(
                   ['''a_new_additional_special_token''']					,tokenizer.convert_ids_to_tokens(
                       tokenizer.convert_tokens_to_ids(['''a_new_additional_special_token''']							)							)					,)




      def 		lowerCAmelCase__					(				self							)			->			Any:



         '''simple docstring'''



         UpperCAmelCase__							:				Any   				=  []
         if self.test_slow_tokenizer:
            tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())							)

         if self.test_rust_tokenizer:
            tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())							)

         for tokenizer_class, tokenizer_utils in tokenizer_list:
            with tempfile.TemporaryDirectory() as tmp_dir:
               tokenizer_utils.save_pretrained(lowerCamelCase_							)

               UpperCAmelCase__							:				int   				=  tokenizer_class.from_pretrained(lowerCamelCase_							)

               self.assertTrue(tokenizer.decode([255]							) == ''''''							)




      def 		lowerCAmelCase__					(				self							)			->			List[str]:



         '''simple docstring'''



         pass




      def 		lowerCAmelCase__					(				self							)			->			List[Any]:



         '''simple docstring'''



         pass




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         pass




      def 		lowerCAmelCase__					(				self							)			->			Union[str, Any]:



         '''simple docstring'''



         pass




      def 		lowerCAmelCase__					(				self							)			->			Dict:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[Any]   				=  self.get_tokenizers(fast=lowerCamelCase_					,do_lower_case=lowerCamelCase_							)
         for tokenizer in tokenizers:
            with self.subTest(f'''{tokenizer.__class__.__name__}'''							):
               UpperCAmelCase__							:				List[Any]   				=  ['''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''x''', '''t''', '''</s>''']
               UpperCAmelCase__							:				List[Any]   				=  tokenizer.convert_tokens_to_string(lowerCamelCase_							)

               self.assertIsInstance(lowerCamelCase_					,lowerCamelCase_							)




      def 		lowerCAmelCase__					(				self							)			->			int:



         '''simple docstring'''



         UpperCAmelCase__							:				int   				=  self.get_tokenizers()
         for tokenizer in tokenizers:
            with self.subTest(f'''{tokenizer.__class__.__name__}'''							):
               UpperCAmelCase__							:				Tuple   				=  [
                   '''bos_token''',
                   '''eos_token''',
                   '''unk_token''',
                   '''sep_token''',
                   '''pad_token''',
                   '''cls_token''',
                   '''mask_token''',
               ]

               UpperCAmelCase__							:				Optional[int]   				=  0
               UpperCAmelCase__							:				List[str]   				=  tokenizer.convert_ids_to_tokens(
                   lowerCamelCase_					,skip_special_tokens=lowerCamelCase_							)

               for attr in attributes_list:
                  setattr(lowerCamelCase_					,attr + '''_id'''					,lowerCamelCase_							)
                  self.assertEqual(getattr(lowerCamelCase_					,lowerCamelCase_							)					,lowerCamelCase_							)
                  self.assertEqual(getattr(lowerCamelCase_					,attr + '''_id'''							)					,lowerCamelCase_							)

                  setattr(lowerCamelCase_					,attr + '''_id'''					,lowerCamelCase_							)
                  self.assertEqual(getattr(lowerCamelCase_					,lowerCamelCase_							)					,lowerCamelCase_							)
                  self.assertEqual(getattr(lowerCamelCase_					,attr + '''_id'''							)					,lowerCamelCase_							)

               setattr(lowerCamelCase_					,'''additional_special_tokens_ids'''					,[]							)
               self.assertListEqual(getattr(lowerCamelCase_					,'''additional_special_tokens'''							)					,[]							)
               self.assertListEqual(getattr(lowerCamelCase_					,'''additional_special_tokens_ids'''							)					,[]							)

               setattr(lowerCamelCase_					,'''additional_special_tokens_ids'''					,[token_id_to_test_setters]							)
               self.assertListEqual(getattr(lowerCamelCase_					,'''additional_special_tokens'''							)					,[token_to_test_setters]							)
               self.assertListEqual(getattr(lowerCamelCase_					,'''additional_special_tokens_ids'''							)					,[token_id_to_test_setters]							)





'''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 __UpperCamelCase(   _A					:				Optional[int]  ,			_A					:				Union[str, Any]  ,			_A					:				Optional[int]  ,			_A					:				Any  ,			_A					:				Optional[int]=True  ,			_A					:				List[Any]="pt"    ):
   '''simple docstring'''
   UpperCAmelCase__							:				List[str]   				=  {'''add_prefix_space''': True} if isinstance(_A  ,			_A    ) and not line.startswith(''' '''    ) else {}
   UpperCAmelCase__							:				str   				=  padding_side
   return tokenizer(
       [line]  ,			max_length=_A  ,			padding='''max_length''' if pad_to_max_length else None  ,			truncation=_A  ,			return_tensors=_A  ,			add_special_tokens=_A  ,			**_A  ,			)







def __UpperCamelCase(   _A					:				Any  ,			_A					:				Union[str, Any]  ,			_A					:				str=None  ,			):
   '''simple docstring'''
   UpperCAmelCase__							:				List[Any]   				=  input_ids.ne(_A    ).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 				_lowercase	(      lowerCAmelCase   ):
      '''simple docstring'''


      def __init__(				self					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_					,lowerCamelCase_="train"					,lowerCamelCase_=None					,lowerCamelCase_=None					,lowerCamelCase_=None					,lowerCamelCase_=""					,)			->			Any:



         '''simple docstring'''



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




      def __len__(				self							)			->			Optional[int]:



         '''simple docstring'''



         return len(self.src_lens							)




      def __getitem__(				self					,lowerCamelCase_							)			->			Dict[str, torch.Tensor]:



         '''simple docstring'''



         UpperCAmelCase__							:				Optional[Any]   				=  index + 1  # linecache starts at 1
         UpperCAmelCase__							:				Tuple   				=  self.prefix + linecache.getline(str(self.src_file							)					,lowerCamelCase_							).rstrip('''\n'''							)
         UpperCAmelCase__							:				List[str]   				=  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
         UpperCAmelCase__							:				int   				=  (
             self.tokenizer.question_encoder if isinstance(self.tokenizer					,lowerCamelCase_							) else self.tokenizer
         )
         UpperCAmelCase__							:				Any   				=  self.tokenizer.generator if isinstance(self.tokenizer					,lowerCamelCase_							) else self.tokenizer

         UpperCAmelCase__							:				List[Any]   				=  encode_line(lowerCamelCase_					,lowerCamelCase_					,self.max_source_length					,'''right'''							)
         UpperCAmelCase__							:				Dict   				=  encode_line(lowerCamelCase_					,lowerCamelCase_					,self.max_target_length					,'''right'''							)

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




      @staticmethod
      def 		lowerCAmelCase__					(				lowerCamelCase_							)			->			Any:



         '''simple docstring'''



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




      def 		lowerCAmelCase__					(				self					,lowerCamelCase_							)			->			Dict[str, torch.Tensor]:



         '''simple docstring'''



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




UpperCamelCase__     :	int				=			getLogger(__name__)







def __UpperCamelCase(   _A					:				List[List]    ):
   '''simple docstring'''
   return list(itertools.chain.from_iterable(_A    )    )







def __UpperCamelCase(   _A					:				str    ):
   '''simple docstring'''
   UpperCAmelCase__							:				Dict   				=  get_git_info()
   save_json(_A  ,			os.path.join(_A  ,			'''git_log.json'''    )    )







def __UpperCamelCase(   _A					:				Tuple  ,			_A					:				Optional[Any]  ,			_A					:				List[Any]=4  ,			**_A					:				Optional[Any]    ):
   '''simple docstring'''
   with open(_A  ,			'''w'''    ) as f:
      json.dump(_A  ,			_A  ,			indent=_A  ,			**_A    )







def __UpperCamelCase(   _A					:				Tuple    ):
   '''simple docstring'''
   with open(_A    ) as f:
      return json.load(_A    )







def __UpperCamelCase(   ):
   '''simple docstring'''
   UpperCAmelCase__							:				int   				=  git.Repo(search_parent_directories=_A    )
   UpperCAmelCase__							:				int   				=  {
       '''repo_id''': str(_A    ),
       '''repo_sha''': str(repo.head.object.hexsha    ),
       '''repo_branch''': str(repo.active_branch    ),
       '''hostname''': str(socket.gethostname()    ),
   }
   return repo_infos







def __UpperCamelCase(   _A					:				Callable  ,			_A					:				Iterable    ):
   '''simple docstring'''
   return list(map(_A  ,			_A    )    )







def __UpperCamelCase(   _A					:				str  ,			_A					:				str    ):
   '''simple docstring'''
   with open(_A  ,			'''wb'''    ) as f:
      return pickle.dump(_A  ,			_A    )







def __UpperCamelCase(   _A					:				int    ):
   '''simple docstring'''

   def remove_articles(_A					:				int    ):
      return re.sub(R'''\b(a|an|the)\b'''  ,			''' '''  ,			_A    )

   def white_space_fix(_A					:				List[Any]    ):
      return " ".join(text.split()    )

   def remove_punc(_A					:				Tuple    ):
      UpperCAmelCase__							:				Optional[int]   				=  set(string.punctuation    )
      return "".join(ch for ch in text if ch not in exclude    )

   def lower(_A					:				Any    ):
      return text.lower()

   return white_space_fix(remove_articles(remove_punc(lower(_A    )    )    )    )







def __UpperCamelCase(   _A					:				Optional[Any]  ,			_A					:				Any    ):
   '''simple docstring'''
   UpperCAmelCase__							:				Dict   				=  normalize_answer(_A    ).split()
   UpperCAmelCase__							:				str   				=  normalize_answer(_A    ).split()
   UpperCAmelCase__							:				str   				=  Counter(_A    ) & Counter(_A    )
   UpperCAmelCase__							:				Optional[Any]   				=  sum(common.values()    )
   if num_same == 0:
      return 0
   UpperCAmelCase__							:				Union[str, Any]   				=  1.0 * num_same / len(_A    )
   UpperCAmelCase__							:				List[Any]   				=  1.0 * num_same / len(_A    )
   UpperCAmelCase__							:				Dict   				=  (2 * precision * recall) / (precision + recall)
   return fa







def __UpperCamelCase(   _A					:				Dict  ,			_A					:				Tuple    ):
   '''simple docstring'''
   return normalize_answer(_A    ) == normalize_answer(_A    )







def __UpperCamelCase(   _A					:				List[str]  ,			_A					:				List[str]    ):
   '''simple docstring'''
   assert len(_A    ) == len(_A    )
   UpperCAmelCase__							:				Optional[int]   				=  0
   for hypo, pred in zip(_A  ,			_A    ):
      em += exact_match_score(_A  ,			_A    )
   if len(_A    ) > 0:
      em /= len(_A    )
   return {"em": em}







def __UpperCamelCase(   _A					:				int    ):
   '''simple docstring'''
   return model_prefix.startswith('''rag'''    )







def __UpperCamelCase(   _A					:				str  ,			_A					:				Any  ,			_A					:				Tuple    ):
   '''simple docstring'''
   UpperCAmelCase__							:				Any   				=  {p: p for p in extra_params}
   # T5 models don't have `dropout` param, they have `dropout_rate` instead
   UpperCAmelCase__							:				Optional[int]   				=  '''dropout_rate'''
   for p in extra_params:
      if getattr(_A  ,			_A  ,			_A    ):
         if not hasattr(_A  ,			_A    ) and not hasattr(_A  ,			equivalent_param[p]    ):
            logger.info('''config doesn\'t have a `{}` attribute'''.format(_A    )    )
            delattr(_A  ,			_A    )
            continue
         UpperCAmelCase__							:				int   				=  p if hasattr(_A  ,			_A    ) else equivalent_param[p]
         setattr(_A  ,			_A  ,			getattr(_A  ,			_A    )    )
         delattr(_A  ,			_A    )
   return hparams, config




