
class      UpperCamelCase_			:







						'''simple docstring'''



						def __init__( self       :Any		,						lowerCAmelCase__       :Optional[Any]    )     ->Optional[Any]:
										lowercase						    =			val
										# Number of nodes in left subtree
										lowercase						    =			0
										lowercase						    =			None
										lowercase						    =			None
										lowercase						    =			None





						def 					SCREAMING_SNAKE_CASE( self       :int		,						lowerCAmelCase__       :Any    )     ->Any:
										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      UpperCamelCase_			:







						'''simple docstring'''



						def __init__( self       :Union[str, Any]		,						lowerCAmelCase__       :Optional[int]=None		,						lowerCAmelCase__       :int=None		,						lowerCAmelCase__       :Union[str, Any]=0    )     ->str:
										lowercase						    =			heap_size
										lowercase						    =			bottom_root
										lowercase						    =			min_node





						def 					SCREAMING_SNAKE_CASE( self       :List[Any]		,						lowerCAmelCase__       :Any    )     ->List[str]:

										# Empty heaps corner cases
										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 					SCREAMING_SNAKE_CASE( self       :Tuple		,						lowerCAmelCase__       :str    )     ->Optional[Any]:
										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 					SCREAMING_SNAKE_CASE( self       :List[str]    )     ->Dict:
										return self.min_node.val





						def 					SCREAMING_SNAKE_CASE( self       :List[Any]    )     ->Dict:
										return self.size == 0





						def 					SCREAMING_SNAKE_CASE( self       :List[Any]    )     ->int:
										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 					SCREAMING_SNAKE_CASE( self       :List[str]    )     ->List[Any]:
										lowercase						    =			self.bottom_root
										while top_root.parent:
														lowercase						    =			top_root.parent
										# preorder
										lowercase						    =			[]
										self.__traversal(lowerCAmelCase__		,						lowerCAmelCase__    )
										return heap_pre_order





						def 					SCREAMING_SNAKE_CASE( self       :Dict		,						lowerCAmelCase__       :Tuple		,						lowerCAmelCase__       :int		,						lowerCAmelCase__       :Optional[Any]=0    )     ->Tuple:
										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       :Any    )     ->Tuple:
										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()


# This test is meant to be run in on an instance with TPUs like this:
#
#   python examples/pytorch/xla_spawn.py --num_cores=8 tests/test_trainer_tpu.py
#
# Replace 8 with the number of TPU cores you have.
#

import sys
from typing import Dict

from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.utils import logging


_snake_case			:       Optional[Any]      =						logging.get_logger(__name__)


if is_torch_available():
						import torch
						from torch import nn
						from torch.utils.data import Dataset

						from transformers import Trainer





						class      UpperCamelCase_			(			__a		):







												'''simple docstring'''



												def __init__( self       :Optional[int]		,						lowerCAmelCase__       :int = 101    )     ->Any:
																lowercase						    =			length





												def __len__( self       :Tuple    )     ->Any:
																return self.length





												def __getitem__( self       :Any		,						lowerCAmelCase__       :Tuple    )     ->int:
																return i





						class      UpperCamelCase_			:







												'''simple docstring'''



												def __call__( self       :Optional[Any]		,						lowerCAmelCase__       :List[Any]    )     ->int:
																return {"input_ids": torch.tensor(lowerCAmelCase__    ), "labels": torch.tensor(lowerCAmelCase__    )}





						class      UpperCamelCase_			(			nn.Module		):







												'''simple docstring'''



												def __init__( self       :Any    )     ->str:
																super().__init__()
																# Add some (unused) params otherwise DDP will complain.
																lowercase						    =			nn.Linear(120		,						80    )





												def 					SCREAMING_SNAKE_CASE( self       :int		,						lowerCAmelCase__       :Optional[int]		,						lowerCAmelCase__       :Union[str, Any]=None    )     ->List[Any]:
																if labels is not None:
																				return torch.tensor(0.0		,						device=input_ids.device    ), input_ids
																else:
																				return input_ids

def    __snake_case       (  ):







				'''simple docstring'''


				lowercase						    =			HfArgumentParser((TrainingArguments,)	)
				sys.argv += ["--output_dir", "./examples"]
				lowercase						    =			parser.parse_args_into_dataclasses()[0]

				logger.warning(
				    F'''Process rank: {training_args.local_rank}, device: {training_args.device}, '''
				    F'''tpu_num_cores: {training_args.tpu_num_cores}'''		,						)

				# Essentially, what we want to verify in the distributed case is
				# that we get all samples back, in the right order.
				# (this is crucial for prediction for instance)
				for dataset_length in [1001, 256, 15]:
								lowercase						    =			DummyDataset(__magic_name__	)

								def compute_metrics(__magic_name__	) -> Dict:
												lowercase						    =			list(range(len(__magic_name__	)	)	)
												lowercase						    =			p.predictions.tolist() == sequential and p.label_ids.tolist() == sequential
												return {"success": success}

								lowercase						    =			Trainer(
								    model=DummyModel()		,						args=__magic_name__		,						data_collator=DummyDataCollator()		,						eval_dataset=__magic_name__		,						compute_metrics=__magic_name__		,						)
								lowercase						    =			trainer.evaluate()
								logger.info(__magic_name__	)
								if metrics["eval_success"] is not True:
												logger.error(__magic_name__	)
												exit(1	)

								lowercase						    =			trainer.predict(__magic_name__	)
								logger.info(p.metrics	)
								if p.metrics["test_success"] is not True:
												logger.error(p.metrics	)
												exit(1	)

								lowercase						    =			2

								lowercase						    =			trainer.evaluate()
								logger.info(__magic_name__	)
								if metrics["eval_success"] is not True:
												logger.error(__magic_name__	)
												exit(1	)

								lowercase						    =			trainer.predict(__magic_name__	)
								logger.info(p.metrics	)
								if p.metrics["test_success"] is not True:
												logger.error(p.metrics	)
												exit(1	)

								lowercase						    =			None

				logger.info("🔥 All distributed tests successful"	)

def    __snake_case       (  __magic_name__	):







				'''simple docstring'''


				main()


if __name__ == "__main__":
						main()
