
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       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__=True     ,							UpperCamelCase__="pt"   ):







							'''simple docstring'''






							snake_case_           =					{"""add_prefix_space""": True} if isinstance(lowerCamelCase_     ,							lowerCamelCase_   ) and not line.startswith(' '   ) else {}
							snake_case_           =					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       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__=None     ,							):







							'''simple docstring'''






							snake_case_           =					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 				lowercase       ( lowercase_    ):




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




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




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

											snake_case_           =					encode_line(lowerCamelCase_   ,     lowerCamelCase_   ,     self.max_source_length   ,     'right' )
											snake_case_           =					encode_line(lowerCamelCase_   ,     lowerCamelCase_   ,     self.max_target_length   ,     'right' )

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




				@staticmethod
				def 					a							(      snake_case ):
											return [len(lowerCamelCase_ ) for x in Path(lowerCamelCase_ ).open().readlines()]




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



_UpperCAmelCase	:     Optional[Any]		       = getLogger(__name__)





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






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





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					get_git_info()
							save_json(lowerCamelCase_     ,							os.path.join(lowerCamelCase_     ,							'git_log.json'   )   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__=4     ,							**UpperCamelCase__   ):







							'''simple docstring'''






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





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






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





def       __lowerCamelCase			(				):







							'''simple docstring'''






							snake_case_           =					git.Repo(search_parent_directories=lowerCamelCase_   )
							snake_case_           =					{
							    """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       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							return list(map(lowerCamelCase_     ,							lowerCamelCase_   )   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






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





def       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							def remove_articles(UpperCamelCase__   ):
														return re.sub(r'\b(a|an|the)\b'     ,							' '     ,							lowerCamelCase_   )

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

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

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

							return white_space_fix(remove_articles(remove_punc(lower(lowerCamelCase_   )   )   )   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






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





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							return normalize_answer(lowerCamelCase_   ) == normalize_answer(lowerCamelCase_   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							assert len(lowerCamelCase_   ) == len(lowerCamelCase_   )
							snake_case_           =					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       __lowerCamelCase			(				UpperCamelCase__   ):







							'''simple docstring'''






							return model_prefix.startswith('rag'   )





def       __lowerCamelCase			(				UpperCamelCase__     ,							UpperCamelCase__     ,							UpperCamelCase__   ):







							'''simple docstring'''






							snake_case_           =					{p: p for p in extra_params}
							# T5 models don't have `dropout` param, they have `dropout_rate` instead
							snake_case_           =					"""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
																					snake_case_           =					p if hasattr(lowerCamelCase_     ,							lowerCamelCase_   ) else equivalent_param[p]
																					setattr(lowerCamelCase_     ,							lowerCamelCase_     ,							getattr(lowerCamelCase_     ,							lowerCamelCase_   )   )
																					delattr(lowerCamelCase_     ,							lowerCamelCase_   )
							return hparams, config







from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
    fastaa_timesteps,
    smartaa_timesteps,
    smartaa_timesteps,
    smartaaa_timesteps,
    smartaaa_timesteps,
    superaa_timesteps,
    superaa_timesteps,
    superaaa_timesteps,
)







@dataclass
class 				lowercase       ( lowercase_    ):
				__SCREAMING_SNAKE_CASE      :				Union[List[PIL.Image.Image], np.ndarray]
				__SCREAMING_SNAKE_CASE      :				Optional[List[bool]]
				__SCREAMING_SNAKE_CASE      :				Optional[List[bool]]


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
					from .pipeline_if import IFPipeline
					from .pipeline_if_imgaimg import IFImgaImgPipeline
					from .pipeline_if_imgaimg_superresolution import IFImgaImgSuperResolutionPipeline
					from .pipeline_if_inpainting import IFInpaintingPipeline
					from .pipeline_if_inpainting_superresolution import IFInpaintingSuperResolutionPipeline
					from .pipeline_if_superresolution import IFSuperResolutionPipeline
					from .safety_checker import IFSafetyChecker
					from .watermark import IFWatermarker




