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				(    lowerCAmelCase_       ,					lowerCAmelCase_       ,					lowerCAmelCase_       ,					lowerCAmelCase_       ,					lowerCAmelCase_=True       ,					lowerCAmelCase_="pt"   )		->						str:




       '''simple docstring'''






       _A=	{'add_prefix_space': True} if isinstance(lowerCAmelCase_       ,					lowerCAmelCase_   ) and not line.startswith(' '   ) else {}
       _A=	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 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_       ,					lowerCAmelCase_=None       ,					)		->						Union[str, Any]:




       '''simple docstring'''






       _A=	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      lowerCAmelCase						(					_a			):



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



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



     def __getitem__(					self				,      lowerCAmelCase__       ):
            _A=	index + 1  # linecache starts at 1
            _A=	self.prefix + linecache.getline(str(self.src_file       )				,      lowerCAmelCase__       ).rstrip('\n'       )
            _A=	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
            _A=	(
                self.tokenizer.question_encoder if isinstance(self.tokenizer				,      lowerCAmelCase__       ) else self.tokenizer
            )
            _A=	self.tokenizer.generator if isinstance(self.tokenizer				,      lowerCAmelCase__       ) else self.tokenizer

            _A=	encode_line(lowerCAmelCase__				,      lowerCAmelCase__				,      self.max_source_length				,      'right'       )
            _A=	encode_line(lowerCAmelCase__				,      lowerCAmelCase__				,      self.max_target_length				,      'right'       )

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



     @staticmethod
     def 			a__  (					lowerCAmelCase__       ):
            return [len(lowerCAmelCase__       ) for x in Path(lowerCAmelCase__       ).open().readlines()]





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


UpperCAmelCase_								=							getLogger(__name__)

def 							UpperCamelCase				(    lowerCAmelCase_   )		->						Optional[Any]:




       '''simple docstring'''






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

def 							UpperCamelCase				(    lowerCAmelCase_   )		->						None:




       '''simple docstring'''






       _A=	get_git_info()
       save_json(lowerCAmelCase_       ,					os.path.join(lowerCAmelCase_       ,					'git_log.json'   )   )

def 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_       ,					lowerCAmelCase_=4       ,					**lowerCAmelCase_   )		->						str:




       '''simple docstring'''






       with open(lowerCAmelCase_       ,					'w'   ) as f:
              json.dump(lowerCAmelCase_       ,					lowerCAmelCase_       ,					indent=lowerCAmelCase_       ,					**lowerCAmelCase_   )

def 							UpperCamelCase				(    lowerCAmelCase_   )		->						str:




       '''simple docstring'''






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

def 							UpperCamelCase				(    )		->						int:




       '''simple docstring'''






       _A=	git.Repo(search_parent_directories=lowerCAmelCase_   )
       _A=	{
           '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 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_   )		->						List:




       '''simple docstring'''






       return list(map(lowerCAmelCase_       ,					lowerCAmelCase_   )   )

def 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_   )		->						str:




       '''simple docstring'''






       with open(lowerCAmelCase_       ,					'wb'   ) as f:
              return pickle.dump(lowerCAmelCase_       ,					lowerCAmelCase_   )

def 							UpperCamelCase				(    lowerCAmelCase_   )		->						Optional[Any]:




       '''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_   ):
              _A=	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 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_   )		->						Optional[int]:




       '''simple docstring'''






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

def 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_   )		->						Any:




       '''simple docstring'''






       return normalize_answer(lowerCAmelCase_   ) == normalize_answer(lowerCAmelCase_   )

def 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_   )		->						Dict:




       '''simple docstring'''






       assert len(lowerCAmelCase_   ) == len(lowerCAmelCase_   )
       _A=	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 							UpperCamelCase				(    lowerCAmelCase_   )		->						Union[str, Any]:




       '''simple docstring'''






       return model_prefix.startswith('rag'   )





def 							UpperCamelCase				(    lowerCAmelCase_       ,					lowerCAmelCase_       ,					lowerCAmelCase_   )		->						Union[str, Any]:




       '''simple docstring'''






       _A=	{p: p for p in extra_params}
       # T5 models don't have `dropout` param, they have `dropout_rate` instead
       _A=	'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
                     _A=	p if hasattr(lowerCAmelCase_       ,					lowerCAmelCase_   ) else equivalent_param[p]
                     setattr(lowerCAmelCase_       ,					lowerCAmelCase_       ,					getattr(lowerCAmelCase_       ,					lowerCAmelCase_   )   )
                     delattr(lowerCAmelCase_       ,					lowerCAmelCase_   )
       return hparams, config
import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
      import torch

if is_soundfile_availble():
      import soundfile as sf

if is_vision_available():
      from PIL import Image

def 							UpperCamelCase				(    lowerCAmelCase_=""   )		->						str:




       '''simple docstring'''






       _A=	tempfile.mkdtemp()
       return os.path.join(lowerCAmelCase_       ,					str(uuid.uuida()   ) + suffix   )





@require_soundfile
@require_torch
class      lowerCAmelCase						(					unittest.TestCase			):



     def 			a__  (					self       ):
            _A=	torch.rand(12				,      dtype=torch.floataa       ) - 0.5
            _A=	AgentAudio(lowerCAmelCase__       )
            _A=	str(agent_type.to_string()       )

            # Ensure that the tensor and the agent_type's tensor are the same
            self.assertTrue(torch.allclose(lowerCAmelCase__				,      agent_type.to_raw()				,      atol=1E-4       )       )

            del agent_type

            # Ensure the path remains even after the object deletion
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )

            # Ensure that the file contains the same value as the original tensor
            _A,			_A=	sf.read(lowerCAmelCase__       )
            self.assertTrue(torch.allclose(lowerCAmelCase__				,      torch.tensor(lowerCAmelCase__       )				,      atol=1E-4       )       )





     def 			a__  (					self       ):
            _A=	torch.rand(12				,      dtype=torch.floataa       ) - 0.5
            _A=	get_new_path(suffix='.wav'       )
            sf.write(lowerCAmelCase__				,      lowerCAmelCase__				,      16000       )

            _A=	AgentAudio(lowerCAmelCase__       )

            self.assertTrue(torch.allclose(lowerCAmelCase__				,      agent_type.to_raw()				,      atol=1E-4       )       )
            self.assertEqual(agent_type.to_string()				,      lowerCAmelCase__       )





@require_vision
@require_torch
class      lowerCAmelCase						(					unittest.TestCase			):



     def 			a__  (					self       ):
            _A=	torch.randint(0				,      256				,      (64, 64, 3)       )
            _A=	AgentImage(lowerCAmelCase__       )
            _A=	str(agent_type.to_string()       )

            # Ensure that the tensor and the agent_type's tensor are the same
            self.assertTrue(torch.allclose(lowerCAmelCase__				,      agent_type._tensor				,      atol=1E-4       )       )

            self.assertIsInstance(agent_type.to_raw()				,      Image.Image       )

            # Ensure the path remains even after the object deletion
            del agent_type
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )



     def 			a__  (					self       ):
            _A=	Path(get_tests_dir('fixtures/tests_samples/COCO'       )       ) / '000000039769.png'
            _A=	Image.open(lowerCAmelCase__       )
            _A=	AgentImage(lowerCAmelCase__       )

            self.assertTrue(path.samefile(agent_type.to_string()       )       )
            self.assertTrue(image == agent_type.to_raw()       )

            # Ensure the path remains even after the object deletion
            del agent_type
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )





     def 			a__  (					self       ):
            _A=	Path(get_tests_dir('fixtures/tests_samples/COCO'       )       ) / '000000039769.png'
            _A=	Image.open(lowerCAmelCase__       )
            _A=	AgentImage(lowerCAmelCase__       )

            self.assertFalse(path.samefile(agent_type.to_string()       )       )
            self.assertTrue(image == agent_type.to_raw()       )

            # Ensure the path remains even after the object deletion
            del agent_type
            self.assertTrue(os.path.exists(lowerCAmelCase__       )       )





class      lowerCAmelCase						(					unittest.TestCase			):



     def 			a__  (					self       ):
            _A=	'Hey!'
            _A=	AgentText(lowerCAmelCase__       )

            self.assertEqual(lowerCAmelCase__				,      agent_type.to_string()       )
            self.assertEqual(lowerCAmelCase__				,      agent_type.to_raw()       )
            self.assertEqual(lowerCAmelCase__				,      lowerCAmelCase__       )