

from __future__ import annotations

import random
from collections.abc import Iterable


class     lowerCamelCase_   :




 def __init__( self     ,     _UpperCAmelCase       ):
   __UpperCAmelCase  :     dict[str, bool | None]		=    {literal: None for literal in literals}




 def __str__( self       ):
   return "{" + " , ".join(self.literals       ) + "}"




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




 def 						a					( self     ,     _UpperCAmelCase       ):
   for literal in self.literals:
     __UpperCAmelCase  :     int		=    literal[:2]
     if symbol in model:
       __UpperCAmelCase  :     Tuple		=    model[symbol]
     else:
       continue
     if value is not None:
       # Complement assignment if literal is in complemented form
       if literal.endswith('\''       ):
         __UpperCAmelCase  :     Optional[int]		=    not value
     __UpperCAmelCase  :     int		=    value




 def 						a					( self     ,     _UpperCAmelCase       ):
   for literal in self.literals:
     __UpperCAmelCase  :     Any		=    literal.rstrip('\''       ) if literal.endswith('\''       ) else literal + '\''
     if symbol in self.literals:
       return True

   self.assign(_UpperCAmelCase       )
   for value in self.literals.values():
     if value in (True, None):
       return value
   return any(self.literals.values()       )



class     lowerCamelCase_   :




 def __init__( self     ,     _UpperCAmelCase       ):
   __UpperCAmelCase  :     Any		=    list(_UpperCAmelCase       )




 def __str__( self       ):
   return "{" + " , ".join(str(_UpperCAmelCase       ) for clause in self.clauses       ) + "}"





def    _snake_case		()       ->		Clause:
  __UpperCAmelCase  :     Any		=    []
  __UpperCAmelCase  :     Union[str, Any]		=    random.randint(1						,					5     )
  __UpperCAmelCase  :     int		=    'A'
  __UpperCAmelCase  :     int		=    0
  while i < no_of_literals:
    __UpperCAmelCase  :     int		=    random.randint(1						,					5     )
    __UpperCAmelCase  :     Optional[int]		=    base_var + str(snake_case_     )
    __UpperCAmelCase  :     Optional[Any]		=    random.randint(0						,					1     )
    if var_complement == 1:
      var_name += "'"
    if var_name in literals:
      i -= 1
    else:
      literals.append(snake_case_     )
    i += 1
  return Clause(snake_case_     )





def    _snake_case		()       ->		Formula:
  __UpperCAmelCase  :     set[Clause]		=    set()
  __UpperCAmelCase  :     str		=    random.randint(1						,					10     )
  while len(snake_case_     ) < no_of_clauses:
    clauses.add(generate_clause()     )
  return Formula(snake_case_     )





def    _snake_case		(snake_case_				:    Formula     )       ->		tuple[list[Clause], list[str]]:
  __UpperCAmelCase  :     Optional[int]		=    formula.clauses
  __UpperCAmelCase  :     Optional[Any]		=    []
  for clause in formula.clauses:
    for literal in clause.literals:
      __UpperCAmelCase  :     Optional[int]		=    literal[:2]
      if symbol not in symbols_set:
        symbols_set.append(snake_case_     )
  return clauses, symbols_set





def    _snake_case		(snake_case_				:    list[Clause]						,					snake_case_				:    list[str]						,					snake_case_				:    dict[str, bool | None]     )       ->		tuple[list[str], dict[str, bool | None]]:
  __UpperCAmelCase  :     Any		=    []
  __UpperCAmelCase  :     dict[str, bool | None]		=    {}
  __UpperCAmelCase  :     int		=    []

  for clause in clauses:
    if clause.evaluate(snake_case_     ):
      continue
    for literal in clause.literals:
      literals.append(snake_case_     )

  for s in symbols:
    __UpperCAmelCase  :     Any		=    s + '\''
    if (s in literals and sym not in literals) or (
        s not in literals and sym in literals
    ):
      pure_symbols.append(snake_case_     )
  for p in pure_symbols:
    __UpperCAmelCase  :     str		=    None
  for s in pure_symbols:
    __UpperCAmelCase  :     Tuple		=    s + '\''
    if s in literals:
      __UpperCAmelCase  :     Any		=    True
    elif sym in literals:
      __UpperCAmelCase  :     Any		=    False
  return pure_symbols, assignment





def    _snake_case		(snake_case_				:    list[Clause]						,					snake_case_				:    dict[str, bool | None]     )       ->		tuple[list[str], dict[str, bool | None]]:
  __UpperCAmelCase  :     Optional[Any]		=    []
  for clause in clauses:
    if len(snake_case_     ) == 1:
      unit_symbols.append(list(clause.literals.keys()     )[0]     )
    else:
      __UpperCAmelCase, __UpperCAmelCase  :     int		=    0, 0
      for literal, value in clause.literals.items():
        if value is False:
          f_count += 1
        elif value is None:
          __UpperCAmelCase  :     str		=    literal
          n_count += 1
      if f_count == len(snake_case_     ) - 1 and n_count == 1:
        unit_symbols.append(snake_case_     )
  __UpperCAmelCase  :     dict[str, bool | None]		=    {}
  for i in unit_symbols:
    __UpperCAmelCase  :     Any		=    i[:2]
    __UpperCAmelCase  :     List[str]		=    len(snake_case_     ) == 2
  __UpperCAmelCase  :     str		=    [i[:2] for i in unit_symbols]

  return unit_symbols, assignment





def    _snake_case		(snake_case_				:    list[Clause]						,					snake_case_				:    list[str]						,					snake_case_				:    dict[str, bool | None]     )       ->		tuple[bool | None, dict[str, bool | None] | None]:
  __UpperCAmelCase  :     List[str]		=    True
  for clause in clauses:
    __UpperCAmelCase  :     Optional[Any]		=    clause.evaluate(snake_case_     )
    if clause_check is False:
      return False, None
    elif clause_check is None:
      __UpperCAmelCase  :     Union[str, Any]		=    False
      continue

  if check_clause_all_true:
    return True, model

  try:
    __UpperCAmelCase, __UpperCAmelCase  :     List[str]		=    find_pure_symbols(snake_case_						,					snake_case_						,					snake_case_     )
  except RecursionError:
    print('raises a RecursionError and is'     )
    return None, {}
  __UpperCAmelCase  :     Dict		=    None
  if len(snake_case_     ) > 0:
    __UpperCAmelCase, __UpperCAmelCase  :     List[str]		=    pure_symbols[0], assignment[pure_symbols[0]]

  if p:
    __UpperCAmelCase  :     Optional[int]		=    model
    __UpperCAmelCase  :     Any		=    value
    __UpperCAmelCase  :     List[Any]		=    list(snake_case_     )
    if p in tmp_symbols:
      tmp_symbols.remove(snake_case_     )
    return dpll_algorithm(snake_case_						,					snake_case_						,					snake_case_     )

  __UpperCAmelCase, __UpperCAmelCase  :     int		=    find_unit_clauses(snake_case_						,					snake_case_     )
  __UpperCAmelCase  :     int		=    None
  if len(snake_case_     ) > 0:
    __UpperCAmelCase, __UpperCAmelCase  :     str		=    unit_symbols[0], assignment[unit_symbols[0]]
  if p:
    __UpperCAmelCase  :     Tuple		=    model
    __UpperCAmelCase  :     Optional[int]		=    value
    __UpperCAmelCase  :     List[Any]		=    list(snake_case_     )
    if p in tmp_symbols:
      tmp_symbols.remove(snake_case_     )
    return dpll_algorithm(snake_case_						,					snake_case_						,					snake_case_     )
  __UpperCAmelCase  :     Dict		=    symbols[0]
  __UpperCAmelCase  :     List[Any]		=    symbols[1:]
  __UpperCAmelCase, __UpperCAmelCase  :     List[Any]		=    model, model
  __UpperCAmelCase, __UpperCAmelCase  :     Union[str, Any]		=    True, False

  return dpll_algorithm(snake_case_						,					snake_case_						,					snake_case_     ) or dpll_algorithm(snake_case_						,					snake_case_						,					snake_case_     )


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      _SCREAMING_SNAKE_CASE          = generate_formula()
      print(F'''The formula {formula} is''', end=''' ''')

      _SCREAMING_SNAKE_CASE   , _SCREAMING_SNAKE_CASE          = generate_parameters(formula)
      _SCREAMING_SNAKE_CASE   , _SCREAMING_SNAKE_CASE          = dpll_algorithm(clauses, symbols, {})

      if solution:
            print(F'''satisfiable with the assignment {model}.''')
      else:
            print('''not satisfiable.''')








import argparse
import copy
import json
import multiprocessing
import os
import time

from create_dummy_models import COMPOSITE_MODELS, create_tiny_models
from huggingface_hub import ModelFilter, hf_api

import transformers
from transformers import AutoFeatureExtractor, AutoImageProcessor, AutoTokenizer
from transformers.image_processing_utils import BaseImageProcessor





def    _snake_case		()       ->		Optional[int]:
  __UpperCAmelCase  :     Any		=    set()
  # Each auto modeling files contains multiple mappings. Let's get them in a dynamic way.
  for module_name in ["modeling_auto", "modeling_tf_auto", "modeling_flax_auto"]:
    __UpperCAmelCase  :     str		=    getattr(transformers.models.auto						,					snake_case_						,					snake_case_     )
    if module is None:
      continue
    # all mappings in a single auto modeling file
    __UpperCAmelCase  :     Dict		=    [
        x
        for x in dir(snake_case_     )
        if x.endswith('_MAPPING_NAMES'     )
        and (x.startswith('MODEL_'     ) or x.startswith('TF_MODEL_'     ) or x.startswith('FLAX_MODEL_'     ))
    ]
    for name in mapping_names:
      __UpperCAmelCase  :     Optional[int]		=    getattr(snake_case_						,					snake_case_     )
      if mapping is not None:
        for v in mapping.values():
          if isinstance(snake_case_						,					(list, tuple)     ):
            model_names.update(snake_case_     )
          elif isinstance(snake_case_						,					snake_case_     ):
            model_names.add(snake_case_     )

  return sorted(snake_case_     )





def    _snake_case		()       ->		Any:
  # All model names defined in auto mappings
  __UpperCAmelCase  :     int		=    set(get_all_model_names()     )

  with open('tests/utils/tiny_model_summary.json'     ) as fp:
    __UpperCAmelCase  :     Tuple		=    json.load(snake_case_     )
  __UpperCAmelCase  :     int		=    set()
  for model_base_name in tiny_model_info:
    tiny_models_names.update(tiny_model_info[model_base_name]['model_classes']     )

  # Remove a tiny model name if one of its framework implementation hasn't yet a tiny version on the Hub.
  __UpperCAmelCase  :     Tuple		=    model_names.difference(snake_case_     )
  for model_name in copy.copy(snake_case_     ):
    if not model_name.startswith('TF'     ) and F"TF{model_name}" in not_on_hub:
      tiny_models_names.remove(snake_case_     )
    elif model_name.startswith('TF'     ) and model_name[2:] in not_on_hub:
      tiny_models_names.remove(snake_case_     )

  return sorted(snake_case_     )





def    _snake_case		(snake_case_				:    List[str]     )       ->		Tuple:
  __UpperCAmelCase  :     Dict		=    COMPOSITE_MODELS.values()

  # All tiny model base names on Hub
  __UpperCAmelCase  :     Optional[int]		=    get_all_model_names()
  __UpperCAmelCase  :     List[Any]		=    hf_api.list_models(
      filter=ModelFilter(
          author='hf-internal-testing'						,					)     )
  __UpperCAmelCase  :     Dict		=    set()
  for x in models:
    __UpperCAmelCase  :     Union[str, Any]		=    x.modelId
    __UpperCAmelCase, __UpperCAmelCase  :     List[str]		=    model.split('/'     )
    if not model.startswith('tiny-random-'     ):
      continue
    __UpperCAmelCase  :     Optional[Any]		=    model.replace('tiny-random-'						,					''     )
    if not model[0].isupper():
      continue
    if model not in model_names and model not in special_models:
      continue
    _models.add(snake_case_     )

  __UpperCAmelCase  :     Optional[Any]		=    sorted(_models     )
  # All tiny model names on Hub
  __UpperCAmelCase  :     List[Any]		=    {}
  for model in models:
    __UpperCAmelCase  :     Any		=    F"hf-internal-testing/tiny-random-{model}"
    __UpperCAmelCase  :     Optional[Any]		=    model.split('-'     )[0]
    try:
      __UpperCAmelCase  :     Tuple		=    hf_api.repo_info(snake_case_     )
      __UpperCAmelCase  :     Optional[int]		=    {
          'tokenizer_classes': set(),
          'processor_classes': set(),
          'model_classes': set(),
          'sha': repo_info.sha,
      }
    except Exception:
      continue
    try:
      time.sleep(1     )
      __UpperCAmelCase  :     List[Any]		=    AutoTokenizer.from_pretrained(snake_case_     )
      content["tokenizer_classes"].add(tokenizer_fast.__class__.__name__     )
    except Exception:
      pass
    try:
      time.sleep(1     )
      __UpperCAmelCase  :     Optional[int]		=    AutoTokenizer.from_pretrained(snake_case_						,					use_fast=snake_case_     )
      content["tokenizer_classes"].add(tokenizer_slow.__class__.__name__     )
    except Exception:
      pass
    try:
      time.sleep(1     )
      __UpperCAmelCase  :     Optional[int]		=    AutoImageProcessor.from_pretrained(snake_case_     )
      content["processor_classes"].add(img_p.__class__.__name__     )
    except Exception:
      pass
    try:
      time.sleep(1     )
      __UpperCAmelCase  :     Optional[int]		=    AutoFeatureExtractor.from_pretrained(snake_case_     )
      if not isinstance(snake_case_						,					snake_case_     ):
        content["processor_classes"].add(feat_p.__class__.__name__     )
    except Exception:
      pass
    try:
      time.sleep(1     )
      __UpperCAmelCase  :     Tuple		=    getattr(snake_case_						,					snake_case_     )
      __UpperCAmelCase  :     str		=    model_class.from_pretrained(snake_case_     )
      content["model_classes"].add(m.__class__.__name__     )
    except Exception:
      pass
    try:
      time.sleep(1     )
      __UpperCAmelCase  :     Any		=    getattr(snake_case_						,					F"TF{model}"     )
      __UpperCAmelCase  :     List[str]		=    model_class.from_pretrained(snake_case_     )
      content["model_classes"].add(m.__class__.__name__     )
    except Exception:
      pass

    __UpperCAmelCase  :     Optional[int]		=    sorted(content['tokenizer_classes']     )
    __UpperCAmelCase  :     List[str]		=    sorted(content['processor_classes']     )
    __UpperCAmelCase  :     Tuple		=    sorted(content['model_classes']     )

    __UpperCAmelCase  :     str		=    content
    with open(os.path.join(snake_case_						,					'hub_tiny_model_summary.json'     )						,					'w'     ) as fp:
      json.dump(snake_case_						,					snake_case_						,					ensure_ascii=snake_case_						,					indent=4     )


if __name__ == "__main__":
      _SCREAMING_SNAKE_CASE          = argparse.ArgumentParser()
      parser.add_argument('''--num_workers''', default=1, type=int, help='''The number of workers to run.''')
      _SCREAMING_SNAKE_CASE          = parser.parse_args()

      # This has to be `spawn` to avoid hanging forever!
      multiprocessing.set_start_method('''spawn''')

      _SCREAMING_SNAKE_CASE          = '''tiny_models'''
      _SCREAMING_SNAKE_CASE          = True
      _SCREAMING_SNAKE_CASE          = None
      _SCREAMING_SNAKE_CASE          = get_tiny_model_names_from_repo()
      _SCREAMING_SNAKE_CASE          = True
      _SCREAMING_SNAKE_CASE          = True
      _SCREAMING_SNAKE_CASE          = '''hf-internal-testing'''

      create_tiny_models(
          output_path,
          all,
          model_types,
          models_to_skip,
          no_check,
          upload,
          organization,
          token=os.environ.get('''TOKEN''', None),
          num_workers=args.num_workers,
      )





