code: 
  
  
  
  
  
  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 		_SCREAMING_SNAKE_CASE    (   ):
    lowerCamelCase_  :    List[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"]:
      lowerCamelCase_  :    Optional[int]   	=			getattr(transformers.models.auto       ,snake_case_       ,snake_case_	)
      if module is None:
        continue
      # all mappings in a single auto modeling file
      lowerCamelCase_  :    Optional[int]   	=			[
          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:
        lowerCamelCase_  :    Any   	=			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 		_SCREAMING_SNAKE_CASE    (   ):
    # All model names defined in auto mappings
    lowerCamelCase_  :    int   	=			set(get_all_model_names()	)
  
    with open('tests/utils/tiny_model_summary.json'	) as fp:
      lowerCamelCase_  :    Union[str, Any]   	=			json.load(snake_case_	)
    lowerCamelCase_  :    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.
    lowerCamelCase_  :    Optional[Any]   	=			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 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
    lowerCamelCase_  :    Dict   	=			COMPOSITE_MODELS.values()
  
    # All tiny model base names on Hub
    lowerCamelCase_  :    Union[str, Any]   	=			get_all_model_names()
    lowerCamelCase_  :    Optional[Any]   	=			hf_api.list_models(
        filter=ModelFilter(
            author='hf-internal-testing'       ,)	)
    lowerCamelCase_  :    str   	=			set()
    for x in models:
      lowerCamelCase_  :    List[Any]   	=			x.modelId
      lowerCamelCase_  :    List[str]   	=			model.split('/'	)
      if not model.startswith('tiny-random-'	):
        continue
      lowerCamelCase_  :    str   	=			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_	)
  
    lowerCamelCase_  :    Dict   	=			sorted(_models	)
    # All tiny model names on Hub
    lowerCamelCase_  :    Optional[int]   	=			{}
    for model in models:
      lowerCamelCase_  :    Optional[int]   	=			F"hf-internal-testing/tiny-random-{model}"
      lowerCamelCase_  :    str   	=			model.split('-'	)[0]
      try:
        lowerCamelCase_  :    int   	=			hf_api.repo_info(snake_case_	)
        lowerCamelCase_  :    Optional[int]   	=			{
            '''tokenizer_classes''': set(),
            '''processor_classes''': set(),
            '''model_classes''': set(),
            '''sha''': repo_info.sha,
        }
      except Exception:
        continue
      try:
        time.sleep(1	)
        lowerCamelCase_  :    List[str]   	=			AutoTokenizer.from_pretrained(snake_case_	)
        content["tokenizer_classes"].add(tokenizer_fast.__class__.__name__	)
      except Exception:
        pass
      try:
        time.sleep(1	)
        lowerCamelCase_  :    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	)
        lowerCamelCase_  :    int   	=			AutoImageProcessor.from_pretrained(snake_case_	)
        content["processor_classes"].add(img_p.__class__.__name__	)
      except Exception:
        pass
      try:
        time.sleep(1	)
        lowerCamelCase_  :    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	)
        lowerCamelCase_  :    Tuple   	=			getattr(snake_case_       ,snake_case_	)
        lowerCamelCase_  :    Tuple   	=			model_class.from_pretrained(snake_case_	)
        content["model_classes"].add(m.__class__.__name__	)
      except Exception:
        pass
      try:
        time.sleep(1	)
        lowerCamelCase_  :    int   	=			getattr(snake_case_       ,F"TF{model}"	)
        lowerCamelCase_  :    Union[str, Any]   	=			model_class.from_pretrained(snake_case_	)
        content["model_classes"].add(m.__class__.__name__	)
      except Exception:
        pass
  
      lowerCamelCase_  :    List[str]   	=			sorted(content['tokenizer_classes']	)
      lowerCamelCase_  :    Tuple   	=			sorted(content['processor_classes']	)
      lowerCamelCase_  :    Optional[Any]   	=			sorted(content['model_classes']	)
  
      lowerCamelCase_  :    List[Any]   	=			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__":
    _lowercase		:     Any 					=argparse.ArgumentParser()
    parser.add_argument("""--num_workers""", default=1, type=int, help="""The number of workers to run.""")
    _lowercase		:     int 					=parser.parse_args()
  
    # This has to be `spawn` to avoid hanging forever!
    multiprocessing.set_start_method("""spawn""")
  
    _lowercase		:     Any 					="tiny_models"
    _lowercase		:     Optional[int] 					=True
    _lowercase		:     int 					=None
    _lowercase		:     str 					=get_tiny_model_names_from_repo()
    _lowercase		:     List[Any] 					=True
    _lowercase		:     List[Any] 					=True
    _lowercase		:     Optional[Any] 					="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,
    )
  
style_context: 
  
  
  
  
  
  class 	UpperCamelCase_     :
  
  
  
  					def __init__(		self    :    List[Any]					,			lowerCamelCase    :    int	):
  							lowerCamelCase_  :    Union[str, Any]   	=			val
  							# Number of nodes in left subtree
  							lowerCamelCase_  :    Dict   	=			0
  							lowerCamelCase_  :    str   	=			None
  							lowerCamelCase_  :    int   	=			None
  							lowerCamelCase_  :    Dict   	=			None
  
  
  
  
  
  					def      __a    (		self    :    Optional[int]					,			lowerCamelCase    :    List[Any]	):
  							assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"
  
  							if self.val < other.val:
  									lowerCamelCase_  :    int   	=			self.right
  									lowerCamelCase_  :    Any   	=			None
  									if self.right:
  											lowerCamelCase_  :    Optional[Any]   	=			other
  									lowerCamelCase_  :    Union[str, Any]   	=			other
  									lowerCamelCase_  :    List[Any]   	=			self.left_tree_size * 2 + 1
  									return self
  							else:
  									lowerCamelCase_  :    str   	=			other.right
  									lowerCamelCase_  :    List[Any]   	=			None
  									if other.right:
  											lowerCamelCase_  :    Union[str, Any]   	=			self
  									lowerCamelCase_  :    Optional[int]   	=			self
  									lowerCamelCase_  :    Optional[int]   	=			other.left_tree_size * 2 + 1
  									return other
  
  
  
  
  
  
  class 	UpperCamelCase_     :
  
  
  
  					def __init__(		self    :    List[str]					,			lowerCamelCase    :    Optional[int]=None					,			lowerCamelCase    :    str=None					,			lowerCamelCase    :    List[Any]=0	):
  							lowerCamelCase_  :    Any   	=			heap_size
  							lowerCamelCase_  :    int   	=			bottom_root
  							lowerCamelCase_  :    Any   	=			min_node
  
  
  
  					def      __a    (		self    :    int					,			lowerCamelCase    :    int	):
  
  							# Empty heaps corner cases
  							if other.size == 0:
  									return None
  							if self.size == 0:
  									lowerCamelCase_  :    List[str]   	=			other.size
  									lowerCamelCase_  :    Tuple   	=			other.bottom_root
  									lowerCamelCase_  :    Tuple   	=			other.min_node
  									return None
  							# Update size
  							lowerCamelCase_  :    Optional[Any]   	=			self.size + other.size
  
  							# Update min.node
  							if self.min_node.val > other.min_node.val:
  									lowerCamelCase_  :    Optional[Any]   	=			other.min_node
  							# Merge
  
  							# Order roots by left_subtree_size
  							lowerCamelCase_  :    Dict   	=			[]
  							lowerCamelCase_	,			lowerCamelCase_  :    Optional[Any]   	=			self.bottom_root, other.bottom_root
  							while i or j:
  									if i and ((not j) or i.left_tree_size < j.left_tree_size):
  											combined_roots_list.append((i, True)	)
  											lowerCamelCase_  :    Tuple   	=			i.parent
  									else:
  											combined_roots_list.append((j, False)	)
  											lowerCamelCase_  :    Optional[Any]   	=			j.parent
          # Insert links between them
  							for i in range(len(lowerCamelCase	) - 1	):
  									if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
  											lowerCamelCase_  :    Dict   	=			combined_roots_list[i + 1][0]
  											lowerCamelCase_  :    Optional[int]   	=			combined_roots_list[i][0]
          # Consecutively merge roots with same left_tree_size
  							lowerCamelCase_  :    Any   	=			combined_roots_list[0][0]
  							while i.parent:
  									if (
  									    (i.left_tree_size == i.parent.left_tree_size) and (not i.parent.parent)
  									) or (
  									    i.left_tree_size == i.parent.left_tree_size
  									    and i.left_tree_size != i.parent.parent.left_tree_size
  									):
  											# Neighbouring Nodes
  											lowerCamelCase_  :    Dict   	=			i.left
  											lowerCamelCase_  :    int   	=			i.parent.parent
  
  											# Merging trees
  											lowerCamelCase_  :    str   	=			i.merge_trees(i.parent	)
  
  											# Updating links
  											lowerCamelCase_  :    Union[str, Any]   	=			previous_node
  											lowerCamelCase_  :    List[Any]   	=			next_node
  											if previous_node:
  													lowerCamelCase_  :    List[str]   	=			i
  											if next_node:
  													lowerCamelCase_  :    Dict   	=			i
  									else:
  											lowerCamelCase_  :    List[str]   	=			i.parent
          # Updating self.bottom_root
  							while i.left:
  									lowerCamelCase_  :    Union[str, Any]   	=			i.left
  							lowerCamelCase_  :    Any   	=			i
  
  							# Update other
  							lowerCamelCase_  :    Optional[int]   	=			self.size
  							lowerCamelCase_  :    Optional[Any]   	=			self.bottom_root
  							lowerCamelCase_  :    str   	=			self.min_node
  
  							# Return the merged heap
  							return self
  
  
  
  					def      __a    (		self    :    Any					,			lowerCamelCase    :    Dict	):
  							if self.size == 0:
  									lowerCamelCase_  :    Tuple   	=			Node(lowerCamelCase	)
  									lowerCamelCase_  :    Optional[int]   	=			1
  									lowerCamelCase_  :    Optional[int]   	=			self.bottom_root
  							else:
  									# Create new node
  									lowerCamelCase_  :    List[Any]   	=			Node(lowerCamelCase	)
  
  									# Update size
  									self.size += 1
  
  									# update min_node
  									if val < self.min_node.val:
  											lowerCamelCase_  :    List[str]   	=			new_node
  									# Put new_node as a bottom_root in heap
  									lowerCamelCase_  :    int   	=			new_node
  									lowerCamelCase_  :    Tuple   	=			self.bottom_root
  									lowerCamelCase_  :    Any   	=			new_node
  
  									# Consecutively merge roots with same left_tree_size
  									while (
  									    self.bottom_root.parent
  									    and self.bottom_root.left_tree_size
  									    == self.bottom_root.parent.left_tree_size
  									):
  											# Next node
  											lowerCamelCase_  :    Any   	=			self.bottom_root.parent.parent
  
  											# Merge
  											lowerCamelCase_  :    int   	=			self.bottom_root.merge_trees(self.bottom_root.parent	)
  
  											# Update Links
  											lowerCamelCase_  :    Dict   	=			next_node
  											lowerCamelCase_  :    Optional[Any]   	=			None
  											if next_node:
  													lowerCamelCase_  :    Union[str, Any]   	=			self.bottom_root
  
  
  
  					def      __a    (		self    :    Dict	):
  							return self.min_node.val
  
  
  
  					def      __a    (		self    :    int	):
  							return self.size == 0
  
  
  
  					def      __a    (		self    :    List[Any]	):
  							lowerCamelCase_  :    Tuple   	=			self.min_node.val
  
  							# Last element in heap corner case
  							if self.size == 1:
  									# Update size
  									lowerCamelCase_  :    Optional[Any]   	=			0
  
  									# Update bottom root
  									lowerCamelCase_  :    Any   	=			None
  
  									# Update min_node
  									lowerCamelCase_  :    List[str]   	=			None
  
  									return min_value
  							# No right subtree corner case
  							# The structure of the tree implies that this should be the bottom root
  							# and there is at least one other root
  							if self.min_node.right is None:
  									# Update size
  									self.size -= 1
  
  									# Update bottom root
  									lowerCamelCase_  :    Union[str, Any]   	=			self.bottom_root.parent
  									lowerCamelCase_  :    Union[str, Any]   	=			None
  
  									# Update min_node
  									lowerCamelCase_  :    Union[str, Any]   	=			self.bottom_root
  									lowerCamelCase_  :    Union[str, Any]   	=			self.bottom_root.parent
  									while i:
  											if i.val < self.min_node.val:
  													lowerCamelCase_  :    Union[str, Any]   	=			i
  											lowerCamelCase_  :    Optional[int]   	=			i.parent
  									return min_value
  							# General case
  							# Find the BinomialHeap of the right subtree of min_node
  							lowerCamelCase_  :    Dict   	=			self.min_node.right
  							lowerCamelCase_  :    Dict   	=			None
  							lowerCamelCase_  :    Tuple   	=			bottom_of_new
  							lowerCamelCase_  :    Dict   	=			1
  
  							# Size, min_node and bottom_root
  							while bottom_of_new.left:
  									lowerCamelCase_  :    Any   	=			size_of_new * 2 + 1
  									lowerCamelCase_  :    Tuple   	=			bottom_of_new.left
  									if bottom_of_new.val < min_of_new.val:
  											lowerCamelCase_  :    int   	=			bottom_of_new
          # Corner case of single root on top left path
  							if (not self.min_node.left) and (not self.min_node.parent):
  									lowerCamelCase_  :    Union[str, Any]   	=			size_of_new
  									lowerCamelCase_  :    Union[str, Any]   	=			bottom_of_new
  									lowerCamelCase_  :    Tuple   	=			min_of_new
  									# print("Single root, multiple nodes case")
  									return min_value
  							# Remaining cases
  							# Construct heap of right subtree
  							lowerCamelCase_  :    Optional[Any]   	=			BinomialHeap(
  							    bottom_root=lowerCamelCase					,			min_node=lowerCamelCase					,			heap_size=lowerCamelCase	)
  
  							# Update size
  							lowerCamelCase_  :    Union[str, Any]   	=			self.size - 1 - size_of_new
  
  							# Neighbour nodes
  							lowerCamelCase_  :    Union[str, Any]   	=			self.min_node.left
  							lowerCamelCase_  :    Optional[Any]   	=			self.min_node.parent
  
  							# Initialize new bottom_root and min_node
  							lowerCamelCase_  :    Optional[int]   	=			previous_node or next_node
  							lowerCamelCase_  :    Tuple   	=			next_node
  
  							# Update links of previous_node and search below for new min_node and
  							# bottom_root
  							if previous_node:
  									lowerCamelCase_  :    Dict   	=			next_node
  
  									# Update bottom_root and search for min_node below
  									lowerCamelCase_  :    int   	=			previous_node
  									lowerCamelCase_  :    Tuple   	=			previous_node
  									while self.bottom_root.left:
  											lowerCamelCase_  :    Union[str, Any]   	=			self.bottom_root.left
  											if self.bottom_root.val < self.min_node.val:
  													lowerCamelCase_  :    Any   	=			self.bottom_root
  							if next_node:
  									lowerCamelCase_  :    Any   	=			previous_node
  
  									# Search for new min_node above min_node
  									lowerCamelCase_  :    List[str]   	=			next_node
  									while i:
  											if i.val < self.min_node.val:
  													lowerCamelCase_  :    List[Any]   	=			i
  											lowerCamelCase_  :    Dict   	=			i.parent
          # Merge heaps
  							self.merge_heaps(lowerCamelCase	)
  
  							return min_value
  
  
  
  					def      __a    (		self    :    Optional[int]	):
  							lowerCamelCase_  :    List[Any]   	=			self.bottom_root
  							while top_root.parent:
  									lowerCamelCase_  :    Tuple   	=			top_root.parent
  							# preorder
  							lowerCamelCase_  :    str   	=			[]
  							self.__traversal(lowerCamelCase					,			lowerCamelCase	)
  							return heap_pre_order
  
  
  
  					def      __a    (		self    :    Dict					,			lowerCamelCase    :    Tuple					,			lowerCamelCase    :    Dict					,			lowerCamelCase    :    List[str]=0	):
  							if curr_node:
  									preorder.append((curr_node.val, level)	)
  									self.__traversal(curr_node.left					,			lowerCamelCase					,			level + 1	)
  									self.__traversal(curr_node.right					,			lowerCamelCase					,			level + 1	)
  							else:
  									preorder.append(('#', level)	)
  
  
  
  
  
  					def __str__(		self    :    List[Any]	):
  							if self.is_empty():
  									return ""
  							lowerCamelCase_  :    str   	=			self.pre_order()
  
  							return "\n".join(('-' * level + str(lowerCamelCase	)) for value, level in preorder_heap	)
  
  
  # Unit Tests
  if __name__ == "__main__":
  		import doctest
  
  		doctest.testmod()
  