

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_					(  _lowercase    :       List[str]						,       _lowercase    :       str						,       _lowercase    :       Optional[Any]						,       _lowercase    :       Tuple						,       _lowercase    :       str=True						,       _lowercase    :       Optional[int]="pt")							->	Any:







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

def      lowerCAmelCase_					(  _lowercase    :       Any						,       _lowercase    :       Optional[Any]						,       _lowercase    :       Union[str, Any]=None						,       )							->	Union[str, Any]:







			"""simple docstring"""
			a__       :						Dict							=  input_ids.ne(_lowercase).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        snake_case__    (A__		):







						"""simple docstring"""




						def __init__(       self ,       __lowercase ,       __lowercase ,       __lowercase ,       __lowercase ,       __lowercase="train" ,       __lowercase=None ,       __lowercase=None ,       __lowercase=None ,       __lowercase="" ,       ) ->				List[str]:
									"""simple docstring"""




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

						def __len__(       self  ) ->				str:
									"""simple docstring"""




									return len(self.src_lens  )

						def __getitem__(       self ,       __lowercase  ) ->				Dict[str, torch.Tensor]:
									"""simple docstring"""




									a__       :						List[Any]							=  index + 1  # linecache starts at 1
									a__       :						Optional[int]							=  self.prefix + linecache.getline(str(self.src_file  ) ,       __lowercase  ).rstrip("""\n"""  )
									a__       :						List[Any]							=  linecache.getline(str(self.tgt_file  ) ,       __lowercase  ).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 ,       __lowercase  ):
												source_line += self.tokenizer.eos_token
												tgt_line += self.tokenizer.eos_token

									# Pad source and target to the right
									a__       :						Optional[int]							=  (
									    self.tokenizer.question_encoder if isinstance(self.tokenizer ,       __lowercase  ) else self.tokenizer
									)
									a__       :						Optional[Any]							=  self.tokenizer.generator if isinstance(self.tokenizer ,       __lowercase  ) else self.tokenizer

									a__       :						Any							=  encode_line(__lowercase ,       __lowercase ,       self.max_source_length ,       """right"""  )
									a__       :						Optional[int]							=  encode_line(__lowercase ,       __lowercase ,       self.max_target_length ,       """right"""  )

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

						@staticmethod
						def 							SCREAMING_SNAKE_CASE__(       __lowercase  ) ->				Tuple:
									"""simple docstring"""




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

						def 							SCREAMING_SNAKE_CASE__(       self ,       __lowercase  ) ->				Dict[str, torch.Tensor]:
									"""simple docstring"""




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




_lowercase		:				Tuple      		=getLogger(__name__)

def      lowerCAmelCase_					(  _lowercase    :       List[List])							->	Optional[int]:







			"""simple docstring"""
			return list(itertools.chain.from_iterable(_lowercase))

def      lowerCAmelCase_					(  _lowercase    :       str)							->	None:







			"""simple docstring"""
			a__       :						List[str]							=  get_git_info()
			save_json(_lowercase						,       os.path.join(_lowercase						,       """git_log.json"""))

def      lowerCAmelCase_					(  _lowercase    :       Optional[int]						,       _lowercase    :       Optional[int]						,       _lowercase    :       int=4						,       **_lowercase    :       List[str])							->	Tuple:







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

def      lowerCAmelCase_					(  _lowercase    :       List[Any])							->	List[str]:







			"""simple docstring"""
			with open(_lowercase) as f:
						return json.load(_lowercase)

def      lowerCAmelCase_					(  )							->	Optional[int]:







			"""simple docstring"""
			a__       :						Optional[int]							=  git.Repo(search_parent_directories=_lowercase)
			a__       :						Union[str, Any]							=  {
			    """repo_id""": str(_lowercase),
			    """repo_sha""": str(repo.head.object.hexsha),
			    """repo_branch""": str(repo.active_branch),
			    """hostname""": str(socket.gethostname()),
			}
			return repo_infos

def      lowerCAmelCase_					(  _lowercase    :       Callable						,       _lowercase    :       Iterable)							->	List:







			"""simple docstring"""
			return list(map(_lowercase						,       _lowercase))

def      lowerCAmelCase_					(  _lowercase    :       Optional[Any]						,       _lowercase    :       int)							->	List[Any]:







			"""simple docstring"""
			with open(_lowercase						,       """wb""") as f:
						return pickle.dump(_lowercase						,       _lowercase)

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







			"""simple docstring"""

			def remove_articles(_lowercase    :       Optional[Any]):
						return re.sub(R"""\b(a|an|the)\b"""						,       """ """						,       _lowercase)

			def white_space_fix(_lowercase    :       Union[str, Any]):
						return " ".join(text.split())

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

			def lower(_lowercase    :       Optional[int]):
						return text.lower()

			return white_space_fix(remove_articles(remove_punc(lower(_lowercase))))

def      lowerCAmelCase_					(  _lowercase    :       Optional[Any]						,       _lowercase    :       List[str])							->	Union[str, Any]:







			"""simple docstring"""
			a__       :						List[Any]							=  normalize_answer(_lowercase).split()
			a__       :						List[Any]							=  normalize_answer(_lowercase).split()
			a__       :						List[Any]							=  Counter(_lowercase) & Counter(_lowercase)
			a__       :						Union[str, Any]							=  sum(common.values())
			if num_same == 0:
						return 0
			a__       :						List[Any]							=  1.0 * num_same / len(_lowercase)
			a__       :						Any							=  1.0 * num_same / len(_lowercase)
			a__       :						List[Any]							=  (2 * precision * recall) / (precision + recall)
			return fa

def      lowerCAmelCase_					(  _lowercase    :       int						,       _lowercase    :       Optional[Any])							->	Optional[int]:







			"""simple docstring"""
			return normalize_answer(_lowercase) == normalize_answer(_lowercase)

def      lowerCAmelCase_					(  _lowercase    :       List[str]						,       _lowercase    :       List[str])							->	Dict:







			"""simple docstring"""
			assert len(_lowercase) == len(_lowercase)
			a__       :						Dict							=  0
			for hypo, pred in zip(_lowercase						,       _lowercase):
						em += exact_match_score(_lowercase						,       _lowercase)
			if len(_lowercase) > 0:
						em /= len(_lowercase)
			return {"em": em}

def      lowerCAmelCase_					(  _lowercase    :       Any)							->	Dict:







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





def      lowerCAmelCase_					(  _lowercase    :       Tuple						,       _lowercase    :       Tuple						,       _lowercase    :       int)							->	str:







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









import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request

from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version

from .. import __version__
from . import DIFFUSERS_DYNAMIC_MODULE_NAME, HF_MODULES_CACHE, logging


_lowercase		:				int      		=(
    "https://raw.githubusercontent.com/huggingface/diffusers/{revision}/examples/community/{pipeline}.py"
)


_lowercase		:				Dict      		=logging.get_logger(__name__)  # pylint: disable=invalid-name

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







			"""simple docstring"""
			a__       :						List[Any]							=  """https://pypi.org/pypi/diffusers/json"""
			a__       :						Tuple							=  json.loads(request.urlopen(_lowercase).read())["""releases"""].keys()
			return sorted(_lowercase						,       key=lambda _lowercase: version.Version(_lowercase))

def      lowerCAmelCase_					(  )							->	Optional[Any]:







			"""simple docstring"""
			# This function has already been executed if HF_MODULES_CACHE already is in the Python path.
			if HF_MODULES_CACHE in sys.path:
						return

			sys.path.append(_lowercase)
			os.makedirs(_lowercase						,       exist_ok=_lowercase)
			a__       :						Tuple							=  Path(_lowercase) / """__init__.py"""
			if not init_path.exists():
						init_path.touch()

def      lowerCAmelCase_					(  _lowercase    :       Union[str, os.PathLike])							->	Optional[Any]:







			"""simple docstring"""
			init_hf_modules()
			a__       :						Optional[int]							=  Path(_lowercase) / name
			# If the parent module does not exist yet, recursively create it.
			if not dynamic_module_path.parent.exists():
						create_dynamic_module(dynamic_module_path.parent)
			os.makedirs(_lowercase						,       exist_ok=_lowercase)
			a__       :						Any							=  dynamic_module_path / """__init__.py"""
			if not init_path.exists():
						init_path.touch()

def      lowerCAmelCase_					(  _lowercase    :       Union[str, Any])							->	Optional[int]:







			"""simple docstring"""
			with open(_lowercase						,       """r"""						,       encoding="""utf-8""") as f:
						a__       :						Union[str, Any]							=  f.read()

			# Imports of the form `import .xxx`
			a__       :						Optional[Any]							=  re.findall("""^\s*import\s+\.(\S+)\s*$"""						,       _lowercase						,       flags=re.MULTILINE)
			# Imports of the form `from .xxx import yyy`
			relative_imports += re.findall("""^\s*from\s+\.(\S+)\s+import"""						,       _lowercase						,       flags=re.MULTILINE)
			# Unique-ify
			return list(set(_lowercase))

def      lowerCAmelCase_					(  _lowercase    :       List[Any])							->	Dict:







			"""simple docstring"""
			a__       :						Dict							=  False
			a__       :						str							=  [module_file]
			a__       :						List[Any]							=  []

			# Let's recurse through all relative imports
			while not no_change:
						a__       :						Optional[Any]							=  []
						for f in files_to_check:
									new_imports.extend(get_relative_imports(_lowercase))

						a__       :						Dict							=  Path(_lowercase).parent
						a__       :						Any							=  [str(module_path / m) for m in new_imports]
						a__       :						Any							=  [f for f in new_import_files if f not in all_relative_imports]
						a__       :						List[Any]							=  [F'''{f}.py''' for f in new_import_files]

						a__       :						List[Any]							=  len(_lowercase) == 0
						all_relative_imports.extend(_lowercase)

			return all_relative_imports

def      lowerCAmelCase_					(  _lowercase    :       Optional[int])							->	Any:







			"""simple docstring"""
			with open(_lowercase						,       """r"""						,       encoding="""utf-8""") as f:
						a__       :						Optional[Any]							=  f.read()

			# Imports of the form `import xxx`
			a__       :						Optional[int]							=  re.findall("""^\s*import\s+(\S+)\s*$"""						,       _lowercase						,       flags=re.MULTILINE)
			# Imports of the form `from xxx import yyy`
			imports += re.findall("""^\s*from\s+(\S+)\s+import"""						,       _lowercase						,       flags=re.MULTILINE)
			# Only keep the top-level module
			a__       :						Any							=  [imp.split(""".""")[0] for imp in imports if not imp.startswith(""".""")]

			# Unique-ify and test we got them all
			a__       :						Optional[Any]							=  list(set(_lowercase))
			a__       :						Union[str, Any]							=  []
			for imp in imports:
						try:
									importlib.import_module(_lowercase)
						except ImportError:
									missing_packages.append(_lowercase)

			if len(_lowercase) > 0:
						raise ImportError(
						    """This modeling file requires the following packages that were not found in your environment: """
						    F'''{', '.join(_lowercase)}. Run `pip install {' '.join(_lowercase)}`''')

			return get_relative_imports(_lowercase)

def      lowerCAmelCase_					(  _lowercase    :       int						,       _lowercase    :       Tuple)							->	Union[str, Any]:







			"""simple docstring"""
			a__       :						Dict							=  module_path.replace(os.path.sep						,       """.""")
			a__       :						List[Any]							=  importlib.import_module(_lowercase)

			if class_name is None:
						return find_pipeline_class(_lowercase)
			return getattr(_lowercase						,       _lowercase)

def      lowerCAmelCase_					(  _lowercase    :       Union[str, Any])							->	Optional[int]:







			"""simple docstring"""
			from ..pipelines import DiffusionPipeline

			a__       :						Any							=  dict(inspect.getmembers(_lowercase						,       inspect.isclass))

			a__       :						str							=  None
			for cls_name, cls in cls_members.items():
						if (
						    cls_name != DiffusionPipeline.__name__
						    and issubclass(cls						,       _lowercase)
						    and cls.__module__.split(""".""")[0] != "diffusers"
						):
									if pipeline_class is not None:
												raise ValueError(
												    F'''Multiple classes that inherit from {DiffusionPipeline.__name__} have been found:'''
												    F''' {pipeline_class.__name__}, and {cls_name}. Please make sure to define only one in'''
												    F''' {loaded_module}.''')
									a__       :						str							=  cls

			return pipeline_class

def      lowerCAmelCase_					(  _lowercase    :       Union[str, os.PathLike]						,       _lowercase    :       str						,       _lowercase    :       Optional[Union[str, os.PathLike]] = None						,       _lowercase    :       bool = False						,       _lowercase    :       bool = False						,       _lowercase    :       Optional[Dict[str, str]] = None						,       _lowercase    :       Optional[Union[bool, str]] = None						,       _lowercase    :       Optional[str] = None						,       _lowercase    :       bool = False						,       )							->	Optional[int]:







			"""simple docstring"""
			a__       :						Union[str, Any]							=  str(_lowercase)

			a__       :						Union[str, Any]							=  os.path.join(_lowercase						,       _lowercase)

			if os.path.isfile(_lowercase):
						a__       :						Dict							=  module_file_or_url
						a__       :						List[str]							=  """local"""
			elif pretrained_model_name_or_path.count("""/""") == 0:
						a__       :						Optional[Any]							=  get_diffusers_versions()
						# cut ".dev0"
						a__       :						Union[str, Any]							=  """v""" + """.""".join(__version__.split(""".""")[:3])

						# retrieve github version that matches
						if revision is None:
									a__       :						List[str]							=  latest_version if latest_version[1:] in available_versions else """main"""
									logger.info(F'''Defaulting to latest_version: {revision}.''')
						elif revision in available_versions:
									a__       :						str							=  F'''v{revision}'''
						elif revision == "main":
									a__       :						List[str]							=  revision
						else:
									raise ValueError(
									    F'''`custom_revision`: {revision} does not exist. Please make sure to choose one of'''
									    F''' {', '.join(available_versions + ['main'])}.''')

						# community pipeline on GitHub
						a__       :						Any							=  COMMUNITY_PIPELINES_URL.format(revision=_lowercase						,       pipeline=_lowercase)
						try:
									a__       :						Optional[int]							=  cached_download(
									    _lowercase						,       cache_dir=_lowercase						,       force_download=_lowercase						,       proxies=_lowercase						,       resume_download=_lowercase						,       local_files_only=_lowercase						,       use_auth_token=_lowercase						,       )
									a__       :						Any							=  """git"""
									a__       :						int							=  pretrained_model_name_or_path + """.py"""
						except EnvironmentError:
									logger.error(F'''Could not locate the {module_file} inside {pretrained_model_name_or_path}.''')
									raise
			else:
						try:
									# Load from URL or cache if already cached
									a__       :						Any							=  hf_hub_download(
									    _lowercase						,       _lowercase						,       cache_dir=_lowercase						,       force_download=_lowercase						,       proxies=_lowercase						,       resume_download=_lowercase						,       local_files_only=_lowercase						,       use_auth_token=_lowercase						,       )
									a__       :						Optional[Any]							=  os.path.join("""local"""						,       """--""".join(pretrained_model_name_or_path.split("""/""")))
						except EnvironmentError:
									logger.error(F'''Could not locate the {module_file} inside {pretrained_model_name_or_path}.''')
									raise

    # Check we have all the requirements in our environment
			a__       :						List[str]							=  check_imports(_lowercase)

			# Now we move the module inside our cached dynamic modules.
			a__       :						int							=  DIFFUSERS_DYNAMIC_MODULE_NAME + os.path.sep + submodule
			create_dynamic_module(_lowercase)
			a__       :						Tuple							=  Path(_lowercase) / full_submodule
			if submodule == "local" or submodule == "git":
						# We always copy local files (we could hash the file to see if there was a change, and give them the name of
						# that hash, to only copy when there is a modification but it seems overkill for now).
						# The only reason we do the copy is to avoid putting too many folders in sys.path.
						shutil.copy(_lowercase						,       submodule_path / module_file)
						for module_needed in modules_needed:
									a__       :						Dict							=  F'''{module_needed}.py'''
									shutil.copy(os.path.join(_lowercase						,       _lowercase)						,       submodule_path / module_needed)
			else:
						# Get the commit hash
						# TODO: we will get this info in the etag soon, so retrieve it from there and not here.
						if isinstance(_lowercase						,       _lowercase):
									a__       :						Optional[Any]							=  use_auth_token
						elif use_auth_token is True:
									a__       :						Dict							=  HfFolder.get_token()
						else:
									a__       :						str							=  None

						a__       :						Any							=  model_info(_lowercase						,       revision=_lowercase						,       token=_lowercase).sha

						# The module file will end up being placed in a subfolder with the git hash of the repo. This way we get the
						# benefit of versioning.
						a__       :						Optional[int]							=  submodule_path / commit_hash
						a__       :						Tuple							=  full_submodule + os.path.sep + commit_hash
						create_dynamic_module(_lowercase)

						if not (submodule_path / module_file).exists():
									shutil.copy(_lowercase						,       submodule_path / module_file)
						# Make sure we also have every file with relative
						for module_needed in modules_needed:
									if not (submodule_path / module_needed).exists():
												get_cached_module_file(
												    _lowercase						,       F'''{module_needed}.py'''						,       cache_dir=_lowercase						,       force_download=_lowercase						,       resume_download=_lowercase						,       proxies=_lowercase						,       use_auth_token=_lowercase						,       revision=_lowercase						,       local_files_only=_lowercase						,       )
			return os.path.join(_lowercase						,       _lowercase)





def      lowerCAmelCase_					(  _lowercase    :       Union[str, os.PathLike]						,       _lowercase    :       str						,       _lowercase    :       Optional[str] = None						,       _lowercase    :       Optional[Union[str, os.PathLike]] = None						,       _lowercase    :       bool = False						,       _lowercase    :       bool = False						,       _lowercase    :       Optional[Dict[str, str]] = None						,       _lowercase    :       Optional[Union[bool, str]] = None						,       _lowercase    :       Optional[str] = None						,       _lowercase    :       bool = False						,       **_lowercase    :       Union[str, Any]						,       )							->	List[str]:







			"""simple docstring"""
			a__       :						int							=  get_cached_module_file(
			    _lowercase						,       _lowercase						,       cache_dir=_lowercase						,       force_download=_lowercase						,       resume_download=_lowercase						,       proxies=_lowercase						,       use_auth_token=_lowercase						,       revision=_lowercase						,       local_files_only=_lowercase						,       )
			return get_class_in_module(_lowercase						,       final_module.replace(""".py"""						,       """"""))




