


'''simple docstring'''







from __future__ import annotations

import math
import random
from typing import Any
class 						UpperCamelCase__       :



     """simple docstring"""






     def __init__(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				list[Any]       =							[]
            _lowerCAmelCase     :				int       =							0
            _lowerCAmelCase     :				int       =							0







     def a						(			self ):

            '''simple docstring'''

            return self.head == self.tail







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            self.data.append(__UpperCAmelCase )
            _lowerCAmelCase     :				Optional[int]       =							self.tail + 1







     def a						(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				Union[str, Any]       =							self.data[self.head]
            _lowerCAmelCase     :				List[str]       =							self.head + 1
            return ret







     def a						(			self ):

            '''simple docstring'''

            return self.tail - self.head







     def a						(			self ):

            '''simple docstring'''

            print(self.data )
            print('**************' )
            print(self.data[self.head : self.tail] )
class 						UpperCamelCase__       :



     """simple docstring"""






     def __init__(			self   ,						snake_case__ ):

            '''simple docstring'''

            _lowerCAmelCase     :				int       =							data
            _lowerCAmelCase     :				MyNode | None       =							None
            _lowerCAmelCase     :				MyNode | None       =							None
            _lowerCAmelCase     :				int       =							1







     def a						(			self ):

            '''simple docstring'''

            return self.data







     def a						(			self ):

            '''simple docstring'''

            return self.left







     def a						(			self ):

            '''simple docstring'''

            return self.right







     def a						(			self ):

            '''simple docstring'''

            return self.height







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            _lowerCAmelCase     :				str       =							data







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            _lowerCAmelCase     :				Any       =							node







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            _lowerCAmelCase     :				Union[str, Any]       =							node







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            _lowerCAmelCase     :				Tuple       =							height






def       lowercase					(_A       ):







       """simple docstring"""







       if node is None:
              return 0
       return node.get_height()






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if a > b:
              return a
       return b






def       lowercase					(_A       ):







       """simple docstring"""







       print('left rotation node:' ,    node.get_data()       )
       _lowerCAmelCase     :				List[str]       =							node.get_left()
       assert ret is not None
       node.set_left(ret.get_right()       )
       ret.set_right(__UpperCamelCase       )
       _lowerCAmelCase     :				Optional[Any]       =							my_max(get_height(node.get_right()       ) ,    get_height(node.get_left()       )       ) + 1
       node.set_height(__UpperCamelCase       )
       _lowerCAmelCase     :				Union[str, Any]       =							my_max(get_height(ret.get_right()       ) ,    get_height(ret.get_left()       )       ) + 1
       ret.set_height(__UpperCamelCase       )
       return ret






def       lowercase					(_A       ):







       """simple docstring"""







       print('right rotation node:' ,    node.get_data()       )
       _lowerCAmelCase     :				Tuple       =							node.get_right()
       assert ret is not None
       node.set_right(ret.get_left()       )
       ret.set_left(__UpperCamelCase       )
       _lowerCAmelCase     :				Optional[int]       =							my_max(get_height(node.get_right()       ) ,    get_height(node.get_left()       )       ) + 1
       node.set_height(__UpperCamelCase       )
       _lowerCAmelCase     :				Dict       =							my_max(get_height(ret.get_right()       ) ,    get_height(ret.get_left()       )       ) + 1
       ret.set_height(__UpperCamelCase       )
       return ret






def       lowercase					(_A       ):







       """simple docstring"""







       _lowerCAmelCase     :				str       =							node.get_left()
       assert left_child is not None
       node.set_left(left_rotation(__UpperCamelCase       )       )
       return right_rotation(__UpperCamelCase       )






def       lowercase					(_A       ):







       """simple docstring"""







       _lowerCAmelCase     :				str       =							node.get_right()
       assert right_child is not None
       node.set_right(right_rotation(__UpperCamelCase       )       )
       return left_rotation(__UpperCamelCase       )






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       if node is None:
              return MyNode(__UpperCamelCase       )
       if data < node.get_data():
              node.set_left(insert_node(node.get_left() ,    __UpperCamelCase       )       )
              if (
                  get_height(node.get_left()       ) - get_height(node.get_right()       ) == 2
              ):  # an unbalance detected
                     _lowerCAmelCase     :				str       =							node.get_left()
                     assert left_child is not None
                     if (
                         data < left_child.get_data()
                     ):  # new node is the left child of the left child
                            _lowerCAmelCase     :				List[Any]       =							right_rotation(__UpperCamelCase       )
                     else:
                            _lowerCAmelCase     :				str       =							lr_rotation(__UpperCamelCase       )
       else:
              node.set_right(insert_node(node.get_right() ,    __UpperCamelCase       )       )
              if get_height(node.get_right()       ) - get_height(node.get_left()       ) == 2:
                     _lowerCAmelCase     :				List[str]       =							node.get_right()
                     assert right_child is not None
                     if data < right_child.get_data():
                            _lowerCAmelCase     :				Optional[int]       =							rl_rotation(__UpperCamelCase       )
                     else:
                            _lowerCAmelCase     :				Tuple       =							left_rotation(__UpperCamelCase       )
       _lowerCAmelCase     :				List[str]       =							my_max(get_height(node.get_right()       ) ,    get_height(node.get_left()       )       ) + 1
       node.set_height(__UpperCamelCase       )
       return node






def       lowercase					(_A       ):







       """simple docstring"""







       while True:
              _lowerCAmelCase     :				Tuple       =							root.get_right()
              if right_child is None:
                     break
              _lowerCAmelCase     :				Optional[Any]       =							right_child
       return root.get_data()






def       lowercase					(_A       ):







       """simple docstring"""







       while True:
              _lowerCAmelCase     :				int       =							root.get_left()
              if left_child is None:
                     break
              _lowerCAmelCase     :				List[Any]       =							left_child
       return root.get_data()






def       lowercase					(_A ,    _A       ):







       """simple docstring"""







       _lowerCAmelCase     :				Union[str, Any]       =							root.get_left()
       _lowerCAmelCase     :				List[Any]       =							root.get_right()
       if root.get_data() == data:
              if left_child is not None and right_child is not None:
                     _lowerCAmelCase     :				Optional[Any]       =							get_left_most(__UpperCamelCase       )
                     root.set_data(__UpperCamelCase       )
                     root.set_right(del_node(__UpperCamelCase ,    __UpperCamelCase       )       )
              elif left_child is not None:
                     _lowerCAmelCase     :				Dict       =							left_child
              elif right_child is not None:
                     _lowerCAmelCase     :				List[str]       =							right_child
              else:
                     return None
       elif root.get_data() > data:
              if left_child is None:
                     print('No such data'       )
                     return root
              else:
                     root.set_left(del_node(__UpperCamelCase ,    __UpperCamelCase       )       )
       else:  # root.get_data() < data
              if right_child is None:
                     return root
              else:
                     root.set_right(del_node(__UpperCamelCase ,    __UpperCamelCase       )       )

       if get_height(__UpperCamelCase       ) - get_height(__UpperCamelCase       ) == 2:
              assert right_child is not None
              if get_height(right_child.get_right()       ) > get_height(right_child.get_left()       ):
                     _lowerCAmelCase     :				List[Any]       =							left_rotation(__UpperCamelCase       )
              else:
                     _lowerCAmelCase     :				Dict       =							rl_rotation(__UpperCamelCase       )
       elif get_height(__UpperCamelCase       ) - get_height(__UpperCamelCase       ) == -2:
              assert left_child is not None
              if get_height(left_child.get_left()       ) > get_height(left_child.get_right()       ):
                     _lowerCAmelCase     :				Tuple       =							right_rotation(__UpperCamelCase       )
              else:
                     _lowerCAmelCase     :				Tuple       =							lr_rotation(__UpperCamelCase       )
       _lowerCAmelCase     :				List[str]       =							my_max(get_height(root.get_right()       ) ,    get_height(root.get_left()       )       ) + 1
       root.set_height(__UpperCamelCase       )
       return root
class 						UpperCamelCase__       :



     """simple docstring"""






     def __init__(			self ):

            '''simple docstring'''

            _lowerCAmelCase     :				MyNode | None       =							None







     def a						(			self ):

            '''simple docstring'''

            return get_height(self.root )







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            print('insert:' + str(__UpperCAmelCase ) )
            _lowerCAmelCase     :				List[Any]       =							insert_node(self.root   ,						__UpperCAmelCase )







     def a						(			self   ,						snake_case__ ):

            '''simple docstring'''

            print('delete:' + str(__UpperCAmelCase ) )
            if self.root is None:
                   print('Tree is empty!' )
                   return
            _lowerCAmelCase     :				Union[str, Any]       =							del_node(self.root   ,						__UpperCAmelCase )







     def __str__(			self   ,						):  # a level traversale, gives a more intuitive look on the tree

            '''simple docstring'''

            _lowerCAmelCase     :				str       =							""
            _lowerCAmelCase     :				int       =							MyQueue()
            q.push(self.root )
            _lowerCAmelCase     :				List[Any]       =							self.get_height()
            if layer == 0:
                   return output
            _lowerCAmelCase     :				int       =							0
            while not q.is_empty():
                   _lowerCAmelCase     :				str       =							q.pop()
                   _lowerCAmelCase     :				Dict       =							" " * int(math.pow(2   ,						layer - 1 ) )
                   output += space
                   if node is None:
                          output += "*"
                          q.push(__UpperCAmelCase )
                          q.push(__UpperCAmelCase )
                   else:
                          output += str(node.get_data() )
                          q.push(node.get_left() )
                          q.push(node.get_right() )
                   output += space
                   _lowerCAmelCase     :				Optional[int]       =							cnt + 1
                   for i in range(100 ):
                          if cnt == math.pow(2   ,						__UpperCAmelCase ) - 1:
                                 _lowerCAmelCase     :				List[Any]       =							layer - 1
                                 if layer == 0:
                                        output += "\n*************************************"
                                        return output
                                 output += "\n"
                                 break
            output += "\n*************************************"
            return output






def       lowercase					():







       """simple docstring"""







       import doctest

       doctest.testmod()


if __name__ == "__main__":
       _test()
       lowerCAmelCase     :  str											=    AVLtree()
       lowerCAmelCase     :  Optional[Any]											=    list(range(10))
       random.shuffle(lst)
       for i in lst:
              t.insert(i)
              print(str(t))
       random.shuffle(lst)
       for i in lst:
              t.del_node(i)
              print(str(t))






import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List

import torch
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import (
    SeqaSeqDataset,
    calculate_bleu,
    calculate_rouge,
    chunks,
    lmap,
    load_json,
    parse_numeric_n_bool_cl_kwargs,
    save_json,
    use_task_specific_params,
    write_txt_file,
)


lowerCamelCase		       =      getLogger(__name__)






def     SCREAMING_SNAKE_CASE(      __UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase = 8	,				__UpperCamelCase = 10_24	,				__UpperCamelCase="val"	,				__UpperCamelCase=None	,				__UpperCamelCase=False	,				__UpperCamelCase="summarization"	,				__UpperCamelCase=None	,				__UpperCamelCase=1	,				__UpperCamelCase = None	,				__UpperCamelCase=""	,				**__UpperCamelCase	,				)	->						Dict:
				a__	:							Any      						= str(__UpperCamelCase )
				assert local_rank is not None
				torch.distributed.init_process_group(backend="nccl"	,				rank=__UpperCamelCase )

				a__	:							int      						= Path(__UpperCamelCase )
				a__	:							List[Any]      						= save_dir.joinpath(F'rank_{local_rank}_output.json' )
				torch.cuda.set_device(__UpperCamelCase )
				a__	:							Any      						= AutoModelForSeqaSeqLM.from_pretrained(__UpperCamelCase ).cuda()
				if fpaa:
								a__	:							Optional[int]      						= model.half()
				# determine if we need to increase num_beams
				use_task_specific_params(__UpperCamelCase	,				__UpperCamelCase )  # update config with task specific params
				a__	:							Optional[Any]      						= generate_kwargs.pop("num_beams"	,				model.config.num_beams )  # AttributeError risk?
				if num_return_sequences > num_beams:
								a__	:							Optional[Any]      						= num_return_sequences

				a__	:							Any      						= AutoTokenizer.from_pretrained(__UpperCamelCase )
				logger.info(F'Inferred tokenizer type: {tokenizer.__class__}' )  # if this is wrong, check config.model_type.

				if max_source_length is None:
								a__	:							Optional[Any]      						= tokenizer.model_max_length
				if prefix is None:
								a__	:							str      						= prefix or getattr(model.config	,				"prefix"	,				"" ) or ""
				a__	:							str      						= SeqaSeqDataset(
				    __UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase	,				max_target_length=10_24	,				type_path=__UpperCamelCase	,				n_obs=__UpperCamelCase	,				prefix=__UpperCamelCase	,				**__UpperCamelCase	,				)
				# I set shuffle=True for a more accurate progress bar.
				# If all the longest samples are first, the prog bar estimate is too high at the beginning.
				a__	:							Any      						= ds.make_sortish_sampler(__UpperCamelCase	,				distributed=__UpperCamelCase	,				add_extra_examples=__UpperCamelCase	,				shuffle=__UpperCamelCase )
				a__	:							Optional[int]      						= DataLoader(__UpperCamelCase	,				sampler=__UpperCamelCase	,				batch_size=__UpperCamelCase	,				collate_fn=ds.collate_fn )
				a__	:							Optional[int]      						= []
				for batch in tqdm(__UpperCamelCase ):
								a__	:							Optional[Any]      						= model.generate(
								    input_ids=batch["input_ids"].to(model.device )	,				attention_mask=batch["attention_mask"].to(model.device )	,				num_return_sequences=__UpperCamelCase	,				num_beams=__UpperCamelCase	,				**__UpperCamelCase	,				)
								a__	:							Any      						= tokenizer.batch_decode(__UpperCamelCase	,				skip_special_tokens=__UpperCamelCase	,				clean_up_tokenization_spaces=__UpperCamelCase )
								a__	:							Dict      						= batch["ids"]
								if num_return_sequences > 1:
												a__	:							int      						= chunks(__UpperCamelCase	,				__UpperCamelCase )  # batch size chunks, each of size num_return_seq
								for i, pred in enumerate(__UpperCamelCase ):
												results.append({"pred": pred, "id": ids[i].item()} )
				save_json(__UpperCamelCase	,				__UpperCamelCase )
				return results, sampler.num_replicas






def     SCREAMING_SNAKE_CASE(      )	->						List[str]:
				a__	:							List[str]      						= argparse.ArgumentParser(
				    epilog="Unspecified args like --num_beams=2 --decoder_start_token_id=4 are passed to model.generate" )
				parser.add_argument("--data_dir"	,				type=__UpperCamelCase	,				help="like cnn_dm/test.source" )
				parser.add_argument(
				    "--model_name"	,				type=__UpperCamelCase	,				help="like facebook/bart-large-cnn,t5-base, etc."	,				default="sshleifer/distilbart-xsum-12-3"	,				)
				parser.add_argument("--save_dir"	,				type=__UpperCamelCase	,				help="where to save"	,				default="tmp_gen" )
				parser.add_argument("--max_source_length"	,				type=__UpperCamelCase	,				default=__UpperCamelCase )
				parser.add_argument(
				    "--type_path"	,				type=__UpperCamelCase	,				default="test"	,				help="which subset to evaluate typically train/val/test" )
				parser.add_argument("--task"	,				type=__UpperCamelCase	,				default="summarization"	,				help="used for task_specific_params + metrics" )
				parser.add_argument("--bs"	,				type=__UpperCamelCase	,				default=8	,				required=__UpperCamelCase	,				help="batch size" )
				parser.add_argument(
				    "--local_rank"	,				type=__UpperCamelCase	,				default=-1	,				required=__UpperCamelCase	,				help="should be passed by distributed.launch" )

				parser.add_argument(
				    "--n_obs"	,				type=__UpperCamelCase	,				default=__UpperCamelCase	,				required=__UpperCamelCase	,				help="How many observations. Defaults to all." )
				parser.add_argument(
				    "--num_return_sequences"	,				type=__UpperCamelCase	,				default=1	,				required=__UpperCamelCase	,				help="How many sequences to return" )
				parser.add_argument(
				    "--sync_timeout"	,				type=__UpperCamelCase	,				default=6_00	,				required=__UpperCamelCase	,				help="How long should master process wait for other processes to finish."	,				)
				parser.add_argument("--src_lang"	,				type=__UpperCamelCase	,				default=__UpperCamelCase	,				required=__UpperCamelCase )
				parser.add_argument("--tgt_lang"	,				type=__UpperCamelCase	,				default=__UpperCamelCase	,				required=__UpperCamelCase )
				parser.add_argument(
				    "--prefix"	,				type=__UpperCamelCase	,				required=__UpperCamelCase	,				default=__UpperCamelCase	,				help="will be added to the begininng of src examples" )
				parser.add_argument("--fp16"	,				action="store_true" )
				parser.add_argument("--debug"	,				action="store_true" )
				a__	:							str      						= time.time()
				a__						,   a__	:							Dict      						= parser.parse_known_args()
				a__	:							Optional[Any]      						= parse_numeric_n_bool_cl_kwargs(__UpperCamelCase )
				if generate_kwargs and args.local_rank <= 0:
								print(F'parsed the following generate kwargs: {generate_kwargs}' )
				a__	:							List[str]      						= Path(args.save_dir + "_tmp" )
				Path(__UpperCamelCase ).mkdir(exist_ok=__UpperCamelCase )  # this handles locking.
				a__	:							List[Any]      						= list(json_save_dir.glob("rank_*.json" ) )
				if intermediate_files:
								raise ValueError(F'Found files at {json_save_dir} please move or remove them.' )
								# In theory, a node could finish and save before another node hits this. If this happens, we can address later.
				a__	:							List[Any]      						= {}
				if args.src_lang is not None:
								a__	:							str      						= args.src_lang
				if args.tgt_lang is not None:
								a__	:							int      						= args.tgt_lang

				Path(args.save_dir ).mkdir(exist_ok=__UpperCamelCase )
				a__						,   a__	:							Tuple      						= eval_data_dir(
				    args.data_dir	,				__UpperCamelCase	,				args.model_name	,				type_path=args.type_path	,				bs=args.bs	,				fpaa=args.fpaa	,				task=args.task	,				local_rank=args.local_rank	,				n_obs=args.n_obs	,				max_source_length=args.max_source_length	,				num_return_sequences=args.num_return_sequences	,				prefix=args.prefix	,				dataset_kwargs=__UpperCamelCase	,				**__UpperCamelCase	,				)

				if args.local_rank <= 0:
								a__	:							str      						= Path(args.save_dir )
								save_dir.mkdir(exist_ok=__UpperCamelCase )
								a__	:							Optional[int]      						= gather_results_from_each_node(__UpperCamelCase	,				__UpperCamelCase	,				args.sync_timeout )
								a__	:							Tuple      						= combine_partial_results(__UpperCamelCase )
								if args.num_return_sequences > 1:
												a__	:							Optional[int]      						= save_dir.joinpath("pseudolabel_results.json" )
												print(F'Saving aggregated results at {save_path}, intermediate in {json_save_dir}/' )
												save_json(__UpperCamelCase	,				__UpperCamelCase )
												return
								a__	:							Any      						= Path(args.data_dir ).joinpath(args.type_path + ".target" )
								with open(__UpperCamelCase ) as f:
												a__	:							Optional[int]      						= [x.rstrip() for x in f.readlines()][: len(__UpperCamelCase )]

								# Calculate metrics, save metrics,  and save _generations.txt
								a__	:							Any      						= "translation" in args.task
								a__	:							List[Any]      						= calculate_bleu if calc_bleu else calculate_rouge
								a__	:							List[Any]      						= "bleu" if calc_bleu else "rouge"
								a__	:							Dict      						= score_fn(__UpperCamelCase	,				__UpperCamelCase )
								a__	:							int      						= len(__UpperCamelCase )
								a__	:							Union[str, Any]      						= time.time() - start_time
								a__	:							List[Any]      						= round(runtime / metrics["n_obs"]	,				4 )
								a__	:							List[str]      						= num_replicas
								# TODO(@stas00): add whatever metadata to metrics
								a__	:							int      						= save_dir.joinpath(F'{args.type_path}_{metric_name}.json' )
								save_json(__UpperCamelCase	,				__UpperCamelCase	,				indent=__UpperCamelCase )
								print(__UpperCamelCase )
								write_txt_file(__UpperCamelCase	,				save_dir.joinpath(F'{args.type_path}_generations.txt' ) )
								if args.debug:
												write_txt_file(__UpperCamelCase	,				save_dir.joinpath(F'{args.type_path}.target' ) )
								else:
												shutil.rmtree(__UpperCamelCase )






def     SCREAMING_SNAKE_CASE(      __UpperCamelCase )	->						List:
				a__	:							Optional[Any]      						= []
				for partial_result in partial_results:
								records.extend(__UpperCamelCase )
				a__	:							Tuple      						= sorted(__UpperCamelCase	,				key=lambda __UpperCamelCase : x["id"] )
				a__	:							Tuple      						= [x["pred"] for x in records]
				return preds






def     SCREAMING_SNAKE_CASE(      __UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase )	->						List[Dict[str, List]]:
				# WAIT FOR lots of .json files
				a__	:							Optional[Any]      						= time.time()
				logger.info("waiting for all nodes to finish" )
				a__	:							int      						= None
				while (time.time() - start_wait) < timeout:
								a__	:							List[str]      						= list(save_dir.glob("rank_*.json" ) )
								if len(__UpperCamelCase ) < num_replicas:
												continue
								try:
												# make sure all json files are fully saved
												a__	:							int      						= lmap(__UpperCamelCase	,				__UpperCamelCase )
												return json_data
								except JSONDecodeError:
												continue
				else:
								raise TimeoutError("Rank 0 gave up on waiting for other processes" )
				# Unreachable


if __name__ == "__main__":
						# Usage for MT:
						run_generate()


