



"""simple docstring"""


class  A_     :



						"""simple docstring"""






						def __init__(   self					:List[str]  ,    lowercase_					:Any   )							->     Tuple:
												UpperCAmelCase			 =					val
												# Number of nodes in left subtree
												UpperCAmelCase			 =					0
												UpperCAmelCase			 =					None
												UpperCAmelCase			 =					None
												UpperCAmelCase			 =					None






						def       UpperCAmelCase__	(   self					:Optional[int]  ,    lowercase_					:Tuple   )							->     Union[str, Any]:
												assert self.left_tree_size == other.left_tree_size, "Unequal Sizes of Blocks"

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







class  A_     :



						"""simple docstring"""






						def __init__(   self					:int  ,    lowercase_					:List[str]=None  ,    lowercase_					:List[str]=None  ,    lowercase_					:Optional[int]=0   )							->     Dict:
												UpperCAmelCase			 =					heap_size
												UpperCAmelCase			 =					bottom_root
												UpperCAmelCase			 =					min_node






						def       UpperCAmelCase__	(   self					:List[Any]  ,    lowercase_					:List[Any]   )							->     Optional[Any]:

												# Empty heaps corner cases
												if other.size == 0:
																		return None
												if self.size == 0:
																		UpperCAmelCase			 =					other.size
																		UpperCAmelCase			 =					other.bottom_root
																		UpperCAmelCase			 =					other.min_node
																		return None
												# Update size
												UpperCAmelCase			 =					self.size + other.size

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

												# Order roots by left_subtree_size
												UpperCAmelCase			 =					[]
												UpperCAmelCase ,       UpperCAmelCase			 =					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)   )
																								UpperCAmelCase			 =					i.parent
																		else:
																								combined_roots_list.append((j, False)   )
																								UpperCAmelCase			 =					j.parent
        # Insert links between them
												for i in range(len(lowercase_   ) - 1   ):
																		if combined_roots_list[i][1] != combined_roots_list[i + 1][1]:
																								UpperCAmelCase			 =					combined_roots_list[i + 1][0]
																								UpperCAmelCase			 =					combined_roots_list[i][0]
        # Consecutively merge roots with same left_tree_size
												UpperCAmelCase			 =					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
																								UpperCAmelCase			 =					i.left
																								UpperCAmelCase			 =					i.parent.parent

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

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

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

												# Return the merged heap
												return self






						def       UpperCAmelCase__	(   self					:int  ,    lowercase_					:Union[str, Any]   )							->     Optional[int]:
												if self.size == 0:
																		UpperCAmelCase			 =					Node(lowercase_   )
																		UpperCAmelCase			 =					1
																		UpperCAmelCase			 =					self.bottom_root
												else:
																		# Create new node
																		UpperCAmelCase			 =					Node(lowercase_   )

																		# Update size
																		self.size += 1

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

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

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






						def       UpperCAmelCase__	(   self					:List[Any]   )							->     Optional[Any]:
												return self.min_node.val






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






						def       UpperCAmelCase__	(   self					:str   )							->     Any:
												UpperCAmelCase			 =					self.min_node.val

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

																		# Update bottom root
																		UpperCAmelCase			 =					None

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

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

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

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

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

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

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

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

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

												return min_value






						def       UpperCAmelCase__	(   self					:List[str]   )							->     int:
												UpperCAmelCase			 =					self.bottom_root
												while top_root.parent:
																		UpperCAmelCase			 =					top_root.parent
												# preorder
												UpperCAmelCase			 =					[]
												self.__traversal(lowercase_  ,    lowercase_   )
												return heap_pre_order






						def       UpperCAmelCase__	(   self					:str  ,    lowercase_					:Dict  ,    lowercase_					:Dict  ,    lowercase_					:List[str]=0   )							->     Optional[Any]:
												if curr_node:
																		preorder.append((curr_node.val, level)   )
																		self.__traversal(curr_node.left  ,    lowercase_  ,    level + 1   )
																		self.__traversal(curr_node.right  ,    lowercase_  ,    level + 1   )
												else:
																		preorder.append(('#', level)   )






						def __str__(   self					:str   )							->     Dict:
												if self.is_empty():
																		return ""
												UpperCAmelCase			 =					self.pre_order()

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


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

				doctest.testmod()










"""simple docstring"""


import os
from dataclasses import replace

import jax
import wandb
from bigbird_flax import Args, DataCollator, FlaxBigBirdForNaturalQuestions, Trainer, build_tx, train_step, val_step
from datasets import load_dataset
from flax import jax_utils

from transformers import BigBirdTokenizerFast


if __name__ == "__main__":
				print("""#################### AVAILABLE DEVICES ####################""")
				print(jax.devices())
				print("""###########################################################""")

				# setup for wandb sweep
				snake_case_								=			Args()
				snake_case_								=			wandb.init(project="""bigbird-natural-questions""", config=args.__dict__)
				snake_case_								=			dict(logger.config)
				del wandb_args["batch_size"]
				snake_case_								=			replace(args, **wandb_args)
				snake_case_								=			args.base_dir + """-""" + wandb.run.id
				snake_case_								=			replace(args, base_dir=base_dir)
				print(args)

				snake_case_								=			load_dataset("""json""", data_files=args.tr_data_path)["""train"""]
				snake_case_								=			load_dataset("""json""", data_files=args.val_data_path)["""train"""]

				# drop extra batch for now
				snake_case_								=			range(len(tr_dataset) - len(tr_dataset) % args.batch_size)
				snake_case_								=			tr_dataset.shuffle().select(indices)
				snake_case_								=			range(len(val_dataset) - len(val_dataset) % args.batch_size)
				snake_case_								=			val_dataset.shuffle().select(indices)

				if os.environ.get("""TRAIN_ON_SMALL""", """false""") == "true":
								snake_case_								=			tr_dataset.shuffle().select(range(8_0000))
								snake_case_								=			val_dataset.shuffle().select(range(8000))

				print(tr_dataset)
				print(val_dataset)

				snake_case_								=			FlaxBigBirdForNaturalQuestions.from_pretrained(
				    args.model_id, block_size=args.block_size, num_random_blocks=args.num_random_blocks
				)
				snake_case_								=			BigBirdTokenizerFast.from_pretrained(args.model_id)
				snake_case_								=			DataCollator(pad_id=tokenizer.pad_token_id, max_length=4096)

				snake_case_								=			{
				    """lr""": args.lr,
				    """init_lr""": args.init_lr,
				    """warmup_steps""": args.warmup_steps,
				    """num_train_steps""": args.max_epochs * (len(tr_dataset) // args.batch_size),
				    """weight_decay""": args.weight_decay,
				}
				snake_case_	,  snake_case_								=			build_tx(**tx_args)

				snake_case_								=			Trainer(
				    args=args,
				    data_collator=data_collator,
				    model_save_fn=model.save_pretrained,
				    train_step_fn=train_step,
				    val_step_fn=val_step,
				    logger=logger,
				    scheduler_fn=lr,
				)

				snake_case_								=			None
				snake_case_								=			trainer.create_state(model, tx, num_train_steps=tx_args["""num_train_steps"""], ckpt_dir=ckpt_dir)
				try:
								trainer.train(state, tr_dataset, val_dataset)
				except KeyboardInterrupt:
								print("""Oooops; TRAINING STOPPED UNFORTUNATELY""")

				print("""SAVING WEIGHTS IN `final-weights`""")
				snake_case_								=			jax_utils.unreplicate(state.params)
				model.save_pretrained(os.path.join(args.base_dir, """final-weights"""), params=params)





