





'''simple docstring'''



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       _lowerCAmelCase  ( ):
			__lowercase   =							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"]:
						__lowercase   =							getattr(transformers.models.auto						,				lowerCamelCase_						,				lowerCamelCase_ )
						if module is None:
									continue
						# all mappings in a single auto modeling file
						__lowercase   =							[
						    x
						    for x in dir(lowerCamelCase_ )
						    if x.endswith('''_MAPPING_NAMES''' )
						    and (x.startswith('''MODEL_''' ) or x.startswith('''TF_MODEL_''' ) or x.startswith('''FLAX_MODEL_''' ))
						]
						for name in mapping_names:
									__lowercase   =							getattr(lowerCamelCase_						,				lowerCamelCase_ )
									if mapping is not None:
												for v in mapping.values():
															if isinstance(lowerCamelCase_						,				(list, tuple) ):
																		model_names.update(lowerCamelCase_ )
															elif isinstance(lowerCamelCase_						,				lowerCamelCase_ ):
																		model_names.add(lowerCamelCase_ )

			return sorted(lowerCamelCase_ )




def       _lowerCAmelCase  ( ):
			# All model names defined in auto mappings
			__lowercase   =							set(get_all_model_names() )

			with open('''tests/utils/tiny_model_summary.json''' ) as fp:
						__lowercase   =							json.load(lowerCamelCase_ )
			__lowercase   =							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.
			__lowercase   =							model_names.difference(lowerCamelCase_ )
			for model_name in copy.copy(lowerCamelCase_ ):
						if not model_name.startswith('''TF''' ) and f"TF{model_name}" in not_on_hub:
									tiny_models_names.remove(lowerCamelCase_ )
						elif model_name.startswith('''TF''' ) and model_name[2:] in not_on_hub:
									tiny_models_names.remove(lowerCamelCase_ )

			return sorted(lowerCamelCase_ )




def       _lowerCAmelCase  ( lowerCamelCase_	:     Optional[int] ):
			__lowercase   =							COMPOSITE_MODELS.values()

			# All tiny model base names on Hub
			__lowercase   =							get_all_model_names()
			__lowercase   =							hf_api.list_models(
			    filter=ModelFilter(
			        author='''hf-internal-testing'''						,				) )
			__lowercase   =							set()
			for x in models:
						__lowercase   =							x.modelId
						__lowercase  ,						__lowercase   =							model.split('''/''' )
						if not model.startswith('''tiny-random-''' ):
									continue
						__lowercase   =							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(lowerCamelCase_ )

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

						__lowercase   =							sorted(content['''tokenizer_classes'''] )
						__lowercase   =							sorted(content['''processor_classes'''] )
						__lowercase   =							sorted(content['''model_classes'''] )

						__lowercase   =							content
						with open(os.path.join(lowerCamelCase_						,				'''hub_tiny_model_summary.json''' )						,				'''w''' ) as fp:
									json.dump(lowerCamelCase_						,				lowerCamelCase_						,				ensure_ascii=lowerCamelCase_						,				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,
	)












'''simple docstring'''



class 							__lowercase				:







	'''simple docstring'''

	def __init__(self   ,_lowerCamelCase       )							->							Optional[Any]:







				'''simple docstring'''





				__lowercase   =							val
				# Number of nodes in left subtree
				__lowercase   =							0
				__lowercase   =							None
				__lowercase   =							None
				__lowercase   =							None


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							Tuple:







				'''simple docstring'''





				assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"

				if self.val < other.val:
							__lowercase   =							self.right
							__lowercase   =							None
							if self.right:
										__lowercase   =							other
							__lowercase   =							other
							__lowercase   =							self.left_tree_size * 2 + 1
							return self
				else:
							__lowercase   =							other.right
							__lowercase   =							None
							if other.right:
										__lowercase   =							self
							__lowercase   =							self
							__lowercase   =							other.left_tree_size * 2 + 1
							return other






class 							__lowercase				:







	'''simple docstring'''

	def __init__(self   ,_lowerCamelCase=None   ,_lowerCamelCase=None   ,_lowerCamelCase=0       )							->							int:







				'''simple docstring'''





				__lowercase   =							heap_size
				__lowercase   =							bottom_root
				__lowercase   =							min_node


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							Tuple:







				'''simple docstring'''





				if other.size == 0:
							return None
				if self.size == 0:
							__lowercase   =							other.size
							__lowercase   =							other.bottom_root
							__lowercase   =							other.min_node
							return None
				# Update size
				__lowercase   =							self.size + other.size

				# Update min.node
				if self.min_node.val > other.min_node.val:
							__lowercase   =							other.min_node
				# Merge

				# Order roots by left_subtree_size
				__lowercase   =							[]
				__lowercase  ,						__lowercase   =							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)       )
										__lowercase   =							i.parent
							else:
										combined_roots_list.append((j, False)       )
										__lowercase   =							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]:
										__lowercase   =							combined_roots_list[i + 1][0]
										__lowercase   =							combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
				__lowercase   =							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
										__lowercase   =							i.left
										__lowercase   =							i.parent.parent

										# Merging trees
										__lowercase   =							i.merge_trees(i.parent       )

										# Updating links
										__lowercase   =							previous_node
										__lowercase   =							next_node
										if previous_node:
													__lowercase   =							i
										if next_node:
													__lowercase   =							i
							else:
										__lowercase   =							i.parent
        # Updating self.bottom_root
				while i.left:
							__lowercase   =							i.left
				__lowercase   =							i

				# Update other
				__lowercase   =							self.size
				__lowercase   =							self.bottom_root
				__lowercase   =							self.min_node

				# Return the merged heap
				return self


	def   _UpperCAmelCase   (self   ,_lowerCamelCase       )							->							Dict:







				'''simple docstring'''





				if self.size == 0:
							__lowercase   =							Node(_lowerCamelCase       )
							__lowercase   =							1
							__lowercase   =							self.bottom_root
				else:
							# Create new node
							__lowercase   =							Node(_lowerCamelCase       )

							# Update size
							self.size += 1

							# update min_node
							if val < self.min_node.val:
										__lowercase   =							new_node
							# Put new_node as a bottom_root in heap
							__lowercase   =							new_node
							__lowercase   =							self.bottom_root
							__lowercase   =							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
										__lowercase   =							self.bottom_root.parent.parent

										# Merge
										__lowercase   =							self.bottom_root.merge_trees(self.bottom_root.parent       )

										# Update Links
										__lowercase   =							next_node
										__lowercase   =							None
										if next_node:
													__lowercase   =							self.bottom_root


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







				'''simple docstring'''





				return self.min_node.val


	def   _UpperCAmelCase   (self       )							->							List[Any]:







				'''simple docstring'''





				return self.size == 0


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







				'''simple docstring'''





				__lowercase   =							self.min_node.val

				# Last element in heap corner case
				if self.size == 1:
							# Update size
							__lowercase   =							0

							# Update bottom root
							__lowercase   =							None

							# Update min_node
							__lowercase   =							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
							__lowercase   =							self.bottom_root.parent
							__lowercase   =							None

							# Update min_node
							__lowercase   =							self.bottom_root
							__lowercase   =							self.bottom_root.parent
							while i:
										if i.val < self.min_node.val:
													__lowercase   =							i
										__lowercase   =							i.parent
							return min_value
				# General case
				# Find the BinomialHeap of the right subtree of min_node
				__lowercase   =							self.min_node.right
				__lowercase   =							None
				__lowercase   =							bottom_of_new
				__lowercase   =							1

				# Size, min_node and bottom_root
				while bottom_of_new.left:
							__lowercase   =							size_of_new * 2 + 1
							__lowercase   =							bottom_of_new.left
							if bottom_of_new.val < min_of_new.val:
										__lowercase   =							bottom_of_new
        # Corner case of single root on top left path
				if (not self.min_node.left) and (not self.min_node.parent):
							__lowercase   =							size_of_new
							__lowercase   =							bottom_of_new
							__lowercase   =							min_of_new
							# print("Single root, multiple nodes case")
							return min_value
				# Remaining cases
				# Construct heap of right subtree
				__lowercase   =							BinomialHeap(
				    bottom_root=_lowerCamelCase   ,min_node=_lowerCamelCase   ,heap_size=_lowerCamelCase       )

				# Update size
				__lowercase   =							self.size - 1 - size_of_new

				# Neighbour nodes
				__lowercase   =							self.min_node.left
				__lowercase   =							self.min_node.parent

				# Initialize new bottom_root and min_node
				__lowercase   =							previous_node or next_node
				__lowercase   =							next_node

				# Update links of previous_node and search below for new min_node and
				# bottom_root
				if previous_node:
							__lowercase   =							next_node

							# Update bottom_root and search for min_node below
							__lowercase   =							previous_node
							__lowercase   =							previous_node
							while self.bottom_root.left:
										__lowercase   =							self.bottom_root.left
										if self.bottom_root.val < self.min_node.val:
													__lowercase   =							self.bottom_root
				if next_node:
							__lowercase   =							previous_node

							# Search for new min_node above min_node
							__lowercase   =							next_node
							while i:
										if i.val < self.min_node.val:
													__lowercase   =							i
										__lowercase   =							i.parent
        # Merge heaps
				self.merge_heaps(_lowerCamelCase       )

				return min_value


	def   _UpperCAmelCase   (self       )							->							str:







				'''simple docstring'''





				__lowercase   =							self.bottom_root
				while top_root.parent:
							__lowercase   =							top_root.parent
				# preorder
				__lowercase   =							[]
				self.__traversal(_lowerCamelCase   ,_lowerCamelCase       )
				return heap_pre_order


	def   _UpperCAmelCase   (self   ,_lowerCamelCase   ,_lowerCamelCase   ,_lowerCamelCase=0       )							->							str:







				'''simple docstring'''





				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[str]:







				'''simple docstring'''





				if self.is_empty():
							return ""
				__lowercase   =							self.pre_order()

				return "\n".join(('''-''' * level + str(_lowerCamelCase       )) for value, level in preorder_heap       )


# Unit Tests
if __name__ == "__main__":
	import doctest

	doctest.testmod()





