





import csv
import json
import logging
import os
import re
import subprocess
import tempfile
import unittest
import zipfile
from pathlib import Path
from typing import Optional
from unittest import mock

import torch

# We use TF to parse the logs
from accelerate import Accelerator
from accelerate.test_utils.testing import (
    MockingTestCase,
    TempDirTestCase,
    require_comet_ml,
    require_tensorboard,
    require_wandb,
    skip,
)
from accelerate.tracking import CometMLTracker, GeneralTracker
from accelerate.utils import ProjectConfiguration, is_comet_ml_available, is_tensorboard_available


if is_comet_ml_available():
				from comet_ml import OfflineExperiment

if is_tensorboard_available():
				import struct

				import tensorboard.compat.proto.event_pba as event_pba

__lowerCAmelCase 	=      logging.getLogger(__name__)




@require_tensorboard
class 	_UpperCAmelCase						( unittest.TestCase       ):




					def 						snake_case_		(    self							)    ->	Optional[Any]:
							UpperCamelCase__								=						"""test_project_with_config"""
							with tempfile.TemporaryDirectory() as dirpath:
									UpperCamelCase__								=						Accelerator(log_with="""tensorboard"""     ,   project_dir=__lowerCAmelCase							)
									UpperCamelCase__								=						{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
									accelerator.init_trackers(__lowerCAmelCase     ,   __lowerCAmelCase							)
									accelerator.end_training()
									for child in Path(F"""{dirpath}/{project_name}"""							).glob("""*/**"""							):
											UpperCamelCase__								=						list(filter(lambda __lowerCAmelCase							: x.is_file()     ,   child.iterdir()							)							)[0]
									self.assertNotEqual(str(__lowerCAmelCase							)     ,   """"""							)




					def 						snake_case_		(    self							)    ->	Union[str, Any]:
							UpperCamelCase__								=						"""test_project_with_log"""
							with tempfile.TemporaryDirectory() as dirpath:
									UpperCamelCase__								=						Accelerator(log_with="""tensorboard"""     ,   project_dir=__lowerCAmelCase							)
									accelerator.init_trackers(__lowerCAmelCase							)
									UpperCamelCase__								=						{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
									accelerator.log(__lowerCAmelCase     ,   step=0							)
									accelerator.end_training()
									# Logged values are stored in the outermost-tfevents file and can be read in as a TFRecord
									# Names are randomly generated each time
									UpperCamelCase__								=						list(filter(lambda __lowerCAmelCase							: x.is_file()     ,   Path(F"""{dirpath}/{project_name}"""							).iterdir()							)							)[0]
									self.assertNotEqual(str(__lowerCAmelCase							)     ,   """"""							)




					def 						snake_case_		(    self							)    ->	Any:
							UpperCamelCase__								=						"""test_project_with_log"""
							with tempfile.TemporaryDirectory() as dirpath:
									UpperCamelCase__								=						Accelerator(log_with="""tensorboard"""     ,   project_dir=__lowerCAmelCase							)
									accelerator.init_trackers(__lowerCAmelCase							)
									UpperCamelCase__								=						{"""tensor""": torch.tensor(1							)}
									accelerator.log(__lowerCAmelCase     ,   step=0							)
									accelerator.end_training()
									# Logged values are stored in the outermost-tfevents file and can be read in as a TFRecord
									# Names are randomly generated each time
									UpperCamelCase__								=						list(filter(lambda __lowerCAmelCase							: x.is_file()     ,   Path(F"""{dirpath}/{project_name}"""							).iterdir()							)							)[0]
									# Reading implementation based on https://github.com/pytorch/pytorch/issues/45327#issuecomment-703757685
									with open(__lowerCAmelCase     ,   """rb"""							) as f:
											UpperCamelCase__								=						f.read()
									UpperCamelCase__								=						False
									while data:
											UpperCamelCase__								=						struct.unpack("""Q"""     ,   data[:8]							)

											UpperCamelCase__								=						data[12 : 12 + int(header[0]							)]  # 8+4
											UpperCamelCase__								=						data[12 + int(header[0]							) + 4 :]
											UpperCamelCase__								=						event_pba.Event()

											event.ParseFromString(__lowerCAmelCase							)
											if event.HasField("""summary"""							):
													for value in event.summary.value:
															if value.simple_value == 1.0 and value.tag == "tensor":
																	UpperCamelCase__								=						True
									self.assertTrue(__lowerCAmelCase     ,   """Converted tensor was not found in the log file!"""							)




					def 						snake_case_		(    self							)    ->	List[str]:
							with self.assertRaisesRegex(__lowerCAmelCase     ,   """Logging with `tensorboard` requires a `logging_dir`"""							):
									UpperCamelCase__								=						Accelerator(log_with="""tensorboard"""							)
							with tempfile.TemporaryDirectory() as dirpath:
									UpperCamelCase__								=						Accelerator(log_with="""tensorboard"""     ,   project_dir=__lowerCAmelCase							)




					def 						snake_case_		(    self							)    ->	str:
							UpperCamelCase__								=						ProjectConfiguration(total_limit=30							)
							with tempfile.TemporaryDirectory() as dirpath:
									UpperCamelCase__								=						Accelerator(log_with="""tensorboard"""     ,   project_dir=__lowerCAmelCase     ,   project_config=__lowerCAmelCase							)




@require_wandb
@mock.patch.dict(os.environ			,							{"WANDB_MODE": "offline"}       )
class 	_UpperCAmelCase						( _lowercase			,							_lowercase       ):




					def 						snake_case_		(    self							)    ->	List[str]:
							super().setUp()
							# wandb let's us override where logs are stored to via the WANDB_DIR env var
							self.add_mocks(mock.patch.dict(os.environ     ,   {"""WANDB_DIR""": self.tmpdir}							)							)




					@staticmethod
					def 						snake_case_		(    __lowerCAmelCase     ,   __lowerCAmelCase     ,   __lowerCAmelCase = True							)    ->	Optional[Any]:
							UpperCamelCase__								=						rF"""{section} ([\S\s]*?)\n\n"""
							if record:
									UpperCamelCase__								=						rF"""Record: {pattern}"""
							UpperCamelCase__								=						re.findall(__lowerCAmelCase     ,   __lowerCAmelCase							)[0]
							# A config
							if section == "config" or section == "history":
									UpperCamelCase__								=						re.findall(r"""\"([a-zA-Z0-9_.,]+)"""     ,   __lowerCAmelCase							)
									return {key: val for key, val in zip(cleaned_record[0::2]     ,   cleaned_record[1::2]							)}
							# Everything else
							else:
									return dict(re.findall(r"""(\w+): \"([^\s]+)\""""     ,   __lowerCAmelCase							)							)




					@skip
					def 						snake_case_		(    self							)    ->	List[str]:
							UpperCamelCase__								=						"""test_project_with_config"""
							UpperCamelCase__								=						Accelerator(log_with="""wandb"""							)
							UpperCamelCase__								=						{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
							UpperCamelCase__								=						{"""wandb""": {"""tags""": ["""my_tag"""]}}
							accelerator.init_trackers(__lowerCAmelCase     ,   __lowerCAmelCase     ,   __lowerCAmelCase							)
							UpperCamelCase__								=						{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
							accelerator.log(__lowerCAmelCase     ,   step=0							)
							accelerator.end_training()
							# The latest offline log is stored at wandb/latest-run/*.wandb
							for child in Path(F"""{self.tmpdir}/wandb/latest-run"""							).glob("""*"""							):
									if child.is_file() and child.suffix == ".wandb":
											UpperCamelCase__								=						subprocess.check_output(
											    ["""wandb""", """sync""", """--view""", """--verbose""", str(__lowerCAmelCase							)]     ,   env=os.environ.copy()							).decode("""utf8"""     ,   """ignore"""							)
											break

        # Check HPS through careful parsing and cleaning
							UpperCamelCase__								=						self.parse_log(__lowerCAmelCase     ,   """config"""							)
							self.assertEqual(logged_items["""num_iterations"""]     ,   """12"""							)
							self.assertEqual(logged_items["""learning_rate"""]     ,   """0.01"""							)
							self.assertEqual(logged_items["""some_boolean"""]     ,   """false"""							)
							self.assertEqual(logged_items["""some_string"""]     ,   """some_value"""							)
							self.assertEqual(logged_items["""some_string"""]     ,   """some_value"""							)

							# Run tags
							UpperCamelCase__								=						self.parse_log(__lowerCAmelCase     ,   """run"""     ,   __lowerCAmelCase							)
							self.assertEqual(logged_items["""tags"""]     ,   """my_tag"""							)

							# Actual logging
							UpperCamelCase__								=						self.parse_log(__lowerCAmelCase     ,   """history"""							)
							self.assertEqual(logged_items["""total_loss"""]     ,   """0.1"""							)
							self.assertEqual(logged_items["""iteration"""]     ,   """1"""							)
							self.assertEqual(logged_items["""my_text"""]     ,   """some_value"""							)
							self.assertEqual(logged_items["""_step"""]     ,   """0"""							)



def      a    (   self :  Dict			,    _lowercase :  str			,    _lowercase :  str							)  ->Optional[int]:
		UpperCamelCase__								=						run_name
		UpperCamelCase__								=						OfflineExperiment(project_name=_lowercase			,    offline_directory=_lowercase							)
		logger.info(F"""Initialized offline CometML project {self.run_name}"""							)
		logger.info("""Make sure to log any initial configurations with `self.store_init_configuration` before training!"""							)




@require_comet_ml
@mock.patch.object(_lowercase			,							"__init__"			,							_lowercase       )
class 	_UpperCAmelCase						( unittest.TestCase       ):




					@staticmethod
					def 						snake_case_		(    __lowerCAmelCase     ,   __lowerCAmelCase     ,   __lowerCAmelCase = False							)    ->	List[Any]:
							for log in log_list:
									UpperCamelCase__								=						json.loads(__lowerCAmelCase							)["""payload"""]
									if is_param and "param" in j.keys():
											if j["param"]["paramName"] == key:
													return j["param"]["paramValue"]
									if "log_other" in j.keys():
											if j["log_other"]["key"] == key:
													return j["log_other"]["val"]
									if "metric" in j.keys():
											if j["metric"]["metricName"] == key:
													return j["metric"]["metricValue"]




					def 						snake_case_		(    self							)    ->	List[Any]:
							with tempfile.TemporaryDirectory() as d:
									UpperCamelCase__								=						CometMLTracker("""test_project_with_config"""     ,   __lowerCAmelCase							)
									UpperCamelCase__								=						Accelerator(log_with=__lowerCAmelCase							)
									UpperCamelCase__								=						{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
									accelerator.init_trackers(__lowerCAmelCase     ,   __lowerCAmelCase							)
									accelerator.end_training()
									UpperCamelCase__								=						os.listdir(__lowerCAmelCase							)[0]  # Comet is nice, it's just a zip file here
									# We parse the raw logs
									UpperCamelCase__								=						os.path.join(__lowerCAmelCase     ,   __lowerCAmelCase							)
									UpperCamelCase__								=						zipfile.ZipFile(__lowerCAmelCase     ,   """r"""							)
									UpperCamelCase__								=						archive.open("""messages.json"""							).read().decode("""utf-8"""							)
							UpperCamelCase__								=						log.split("""\n"""							)[:-1]
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """num_iterations"""     ,   __lowerCAmelCase							)     ,   12							)
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """learning_rate"""     ,   __lowerCAmelCase							)     ,   0.0_1							)
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """some_boolean"""     ,   __lowerCAmelCase							)     ,   __lowerCAmelCase							)
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """some_string"""     ,   __lowerCAmelCase							)     ,   """some_value"""							)




					def 						snake_case_		(    self							)    ->	Any:
							with tempfile.TemporaryDirectory() as d:
									UpperCamelCase__								=						CometMLTracker("""test_project_with_config"""     ,   __lowerCAmelCase							)
									UpperCamelCase__								=						Accelerator(log_with=__lowerCAmelCase							)
									accelerator.init_trackers(__lowerCAmelCase							)
									UpperCamelCase__								=						{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
									accelerator.log(__lowerCAmelCase     ,   step=0							)
									accelerator.end_training()
									UpperCamelCase__								=						os.listdir(__lowerCAmelCase							)[0]  # Comet is nice, it's just a zip file here
									# We parse the raw logs
									UpperCamelCase__								=						os.path.join(__lowerCAmelCase     ,   __lowerCAmelCase							)
									UpperCamelCase__								=						zipfile.ZipFile(__lowerCAmelCase     ,   """r"""							)
									UpperCamelCase__								=						archive.open("""messages.json"""							).read().decode("""utf-8"""							)
							UpperCamelCase__								=						log.split("""\n"""							)[:-1]
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """curr_step"""     ,   __lowerCAmelCase							)     ,   0							)
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """total_loss"""							)     ,   0.1							)
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """iteration"""							)     ,   1							)
							self.assertEqual(self.get_value_from_key(__lowerCAmelCase     ,   """my_text"""							)     ,   """some_value"""							)




class 	_UpperCAmelCase						( _lowercase       ):
					__A        = [
					    "total_loss",
					    "iteration",
					    "my_text",
					    "learning_rate",
					    "num_iterations",
					    "some_boolean",
					    "some_string",
					]

					__A        = "my_custom_tracker"
					__A        = False




					def __init__(    self     ,   __lowerCAmelCase							)    ->	str:
							UpperCamelCase__								=						open(F"""{dir}/log.csv"""     ,   """w+"""							)
							UpperCamelCase__								=						csv.DictWriter(self.f     ,   fieldnames=self._col_names							)
							self.writer.writeheader()




					@property
					def 						snake_case_		(    self							)    ->	Tuple:
							return self.writer




					def 						snake_case_		(    self     ,   __lowerCAmelCase							)    ->	List[str]:
							logger.info("""Call init"""							)
							self.writer.writerow(__lowerCAmelCase							)




					def 						snake_case_		(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase							)    ->	Union[str, Any]:
							logger.info("""Call log"""							)
							self.writer.writerow(__lowerCAmelCase							)




					def 						snake_case_		(    self							)    ->	Tuple:
							self.f.close()




class 	_UpperCAmelCase						( unittest.TestCase       ):




					def 						snake_case_		(    self							)    ->	Dict:
							with tempfile.TemporaryDirectory() as d:
									UpperCamelCase__								=						MyCustomTracker(__lowerCAmelCase							)
									UpperCamelCase__								=						Accelerator(log_with=__lowerCAmelCase							)
									UpperCamelCase__								=						{"""num_iterations""": 12, """learning_rate""": 1E-2, """some_boolean""": False, """some_string""": """some_value"""}
									accelerator.init_trackers("""Some name"""     ,   __lowerCAmelCase							)
									accelerator.end_training()
									with open(F"""{d}/log.csv"""     ,   """r"""							) as f:
											UpperCamelCase__								=						csv.DictReader(__lowerCAmelCase							)
											UpperCamelCase__								=						next(__lowerCAmelCase							)
											UpperCamelCase__								=						{
											    """total_loss""": """""",
											    """iteration""": """""",
											    """my_text""": """""",
											    """learning_rate""": """0.01""",
											    """num_iterations""": """12""",
											    """some_boolean""": """False""",
											    """some_string""": """some_value""",
											}
											self.assertDictEqual(__lowerCAmelCase     ,   __lowerCAmelCase							)




					def 						snake_case_		(    self							)    ->	Any:
							with tempfile.TemporaryDirectory() as d:
									UpperCamelCase__								=						MyCustomTracker(__lowerCAmelCase							)
									UpperCamelCase__								=						Accelerator(log_with=__lowerCAmelCase							)
									accelerator.init_trackers("""Some name"""							)
									UpperCamelCase__								=						{"""total_loss""": 0.1, """iteration""": 1, """my_text""": """some_value"""}
									accelerator.log(__lowerCAmelCase     ,   step=0							)
									accelerator.end_training()
									with open(F"""{d}/log.csv"""     ,   """r"""							) as f:
											UpperCamelCase__								=						csv.DictReader(__lowerCAmelCase							)
											UpperCamelCase__								=						next(__lowerCAmelCase							)
											UpperCamelCase__								=						{
											    """total_loss""": """0.1""",
											    """iteration""": """1""",
											    """my_text""": """some_value""",
											    """learning_rate""": """""",
											    """num_iterations""": """""",
											    """some_boolean""": """""",
											    """some_string""": """""",
											}
											self.assertDictEqual(__lowerCAmelCase     ,   __lowerCAmelCase							)












import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__lowerCAmelCase 	=      logging.get_logger(__name__)


__lowerCAmelCase 	=      {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all MVP models at https://huggingface.co/models?filter=mvp
__lowerCAmelCase 	=      {
    "vocab_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json",
    },
    "added_tokens.json": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json",
    },
    "merges_file": {
        "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt",
    },
}

__lowerCAmelCase 	=      {
    "RUCAIBox/mvp": 1_024,
}

@lru_cache()
def      a    (   )  ->Any:
		UpperCamelCase__								=						(
		    list(range(ord("""!"""							)			,    ord("""~"""							) + 1							)							) + list(range(ord("""¡"""							)			,    ord("""¬"""							) + 1							)							) + list(range(ord("""®"""							)			,    ord("""ÿ"""							) + 1							)							)
		)
		UpperCamelCase__								=						bs[:]
		UpperCamelCase__								=						0
		for b in range(2**8							):
				if b not in bs:
						bs.append(_lowercase							)
						cs.append(2**8 + n							)
						n += 1
		UpperCamelCase__								=						[chr(_lowercase							) for n in cs]
		return dict(zip(_lowercase			,    _lowercase							)							)

def      a    (   _lowercase :  int							)  ->List[Any]:
		UpperCamelCase__								=						set()
		UpperCamelCase__								=						word[0]
		for char in word[1:]:
				pairs.add((prev_char, char)							)
				UpperCamelCase__								=						char
		return pairs




class 	_UpperCAmelCase						( _lowercase       ):
					__A        = VOCAB_FILES_NAMES
					__A        = PRETRAINED_VOCAB_FILES_MAP
					__A        = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__A        = ["input_ids", "attention_mask"]




					def __init__(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase     ,   __lowerCAmelCase="replace"     ,   __lowerCAmelCase="<s>"     ,   __lowerCAmelCase="</s>"     ,   __lowerCAmelCase="</s>"     ,   __lowerCAmelCase="<s>"     ,   __lowerCAmelCase="<unk>"     ,   __lowerCAmelCase="<pad>"     ,   __lowerCAmelCase="<mask>"     ,   __lowerCAmelCase=False     ,   **__lowerCAmelCase     ,   )    ->	str:
							UpperCamelCase__								=						AddedToken(__lowerCAmelCase     ,   lstrip=__lowerCAmelCase     ,   rstrip=__lowerCAmelCase							) if isinstance(__lowerCAmelCase     ,   __lowerCAmelCase							) else bos_token
							UpperCamelCase__								=						AddedToken(__lowerCAmelCase     ,   lstrip=__lowerCAmelCase     ,   rstrip=__lowerCAmelCase							) if isinstance(__lowerCAmelCase     ,   __lowerCAmelCase							) else eos_token
							UpperCamelCase__								=						AddedToken(__lowerCAmelCase     ,   lstrip=__lowerCAmelCase     ,   rstrip=__lowerCAmelCase							) if isinstance(__lowerCAmelCase     ,   __lowerCAmelCase							) else sep_token
							UpperCamelCase__								=						AddedToken(__lowerCAmelCase     ,   lstrip=__lowerCAmelCase     ,   rstrip=__lowerCAmelCase							) if isinstance(__lowerCAmelCase     ,   __lowerCAmelCase							) else cls_token
							UpperCamelCase__								=						AddedToken(__lowerCAmelCase     ,   lstrip=__lowerCAmelCase     ,   rstrip=__lowerCAmelCase							) if isinstance(__lowerCAmelCase     ,   __lowerCAmelCase							) else unk_token
							UpperCamelCase__								=						AddedToken(__lowerCAmelCase     ,   lstrip=__lowerCAmelCase     ,   rstrip=__lowerCAmelCase							) if isinstance(__lowerCAmelCase     ,   __lowerCAmelCase							) else pad_token

							# Mask token behave like a normal word, i.e. include the space before it
							UpperCamelCase__								=						AddedToken(__lowerCAmelCase     ,   lstrip=__lowerCAmelCase     ,   rstrip=__lowerCAmelCase							) if isinstance(__lowerCAmelCase     ,   __lowerCAmelCase							) else mask_token

							super().__init__(
							    errors=__lowerCAmelCase     ,   bos_token=__lowerCAmelCase     ,   eos_token=__lowerCAmelCase     ,   unk_token=__lowerCAmelCase     ,   sep_token=__lowerCAmelCase     ,   cls_token=__lowerCAmelCase     ,   pad_token=__lowerCAmelCase     ,   mask_token=__lowerCAmelCase     ,   add_prefix_space=__lowerCAmelCase     ,   **__lowerCAmelCase     ,   )
							with open(__lowerCAmelCase     ,   encoding="""utf-8"""							) as vocab_handle:
									UpperCamelCase__								=						json.load(__lowerCAmelCase							)
							UpperCamelCase__								=						{v: k for k, v in self.encoder.items()}
							UpperCamelCase__								=						errors  # how to handle errors in decoding
							UpperCamelCase__								=						bytes_to_unicode()
							UpperCamelCase__								=						{v: k for k, v in self.byte_encoder.items()}
							with open(__lowerCAmelCase     ,   encoding="""utf-8"""							) as merges_handle:
									UpperCamelCase__								=						merges_handle.read().split("""\n"""							)[1:-1]
							UpperCamelCase__								=						[tuple(merge.split()							) for merge in bpe_merges]
							UpperCamelCase__								=						dict(zip(__lowerCAmelCase     ,   range(len(__lowerCAmelCase							)							)							)							)
							UpperCamelCase__								=						{}
							UpperCamelCase__								=						add_prefix_space

							# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
							UpperCamelCase__								=						re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""							)




					@property
					def 						snake_case_		(    self							)    ->	Union[str, Any]:
							return len(self.encoder							)




					def 						snake_case_		(    self							)    ->	Any:
							return dict(self.encoder     ,   **self.added_tokens_encoder							)




					def 						snake_case_		(    self     ,   __lowerCAmelCase							)    ->	List[str]:
							if token in self.cache:
									return self.cache[token]
							UpperCamelCase__								=						tuple(__lowerCAmelCase							)
							UpperCamelCase__								=						get_pairs(__lowerCAmelCase							)

							if not pairs:
									return token

							while True:
									UpperCamelCase__								=						min(__lowerCAmelCase     ,   key=lambda __lowerCAmelCase							: self.bpe_ranks.get(__lowerCAmelCase     ,   float("""inf"""							)							)							)
									if bigram not in self.bpe_ranks:
											break
									UpperCamelCase__	,      UpperCamelCase__								=						bigram
									UpperCamelCase__								=						[]
									UpperCamelCase__								=						0
									while i < len(__lowerCAmelCase							):
											try:
													UpperCamelCase__								=						word.index(__lowerCAmelCase     ,   __lowerCAmelCase							)
											except ValueError:
													new_word.extend(word[i:]							)
													break
											else:
													new_word.extend(word[i:j]							)
													UpperCamelCase__								=						j

											if word[i] == first and i < len(__lowerCAmelCase							) - 1 and word[i + 1] == second:
													new_word.append(first + second							)
													i += 2
											else:
													new_word.append(word[i]							)
													i += 1
									UpperCamelCase__								=						tuple(__lowerCAmelCase							)
									UpperCamelCase__								=						new_word
									if len(__lowerCAmelCase							) == 1:
											break
									else:
											UpperCamelCase__								=						get_pairs(__lowerCAmelCase							)
							UpperCamelCase__								=						""" """.join(__lowerCAmelCase							)
							UpperCamelCase__								=						word
							return word




					def 						snake_case_		(    self     ,   __lowerCAmelCase							)    ->	int:
							UpperCamelCase__								=						[]
							for token in re.findall(self.pat     ,   __lowerCAmelCase							):
									UpperCamelCase__								=						"""""".join(
									    self.byte_encoder[b] for b in token.encode("""utf-8"""							)							)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
									bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__lowerCAmelCase							).split(""" """							)							)
							return bpe_tokens




					def 						snake_case_		(    self     ,   __lowerCAmelCase							)    ->	Dict:
							return self.encoder.get(__lowerCAmelCase     ,   self.encoder.get(self.unk_token							)							)




					def 						snake_case_		(    self     ,   __lowerCAmelCase							)    ->	Optional[Any]:
							return self.decoder.get(__lowerCAmelCase							)




					def 						snake_case_		(    self     ,   __lowerCAmelCase							)    ->	Any:
							UpperCamelCase__								=						"""""".join(__lowerCAmelCase							)
							UpperCamelCase__								=						bytearray([self.byte_decoder[c] for c in text]							).decode("""utf-8"""     ,   errors=self.errors							)
							return text




					def 						snake_case_		(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase = None							)    ->	Tuple[str]:
							if not os.path.isdir(__lowerCAmelCase							):
									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""							)
									return
							UpperCamelCase__								=						os.path.join(
							    __lowerCAmelCase     ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)
							UpperCamelCase__								=						os.path.join(
							    __lowerCAmelCase     ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]							)

							with open(__lowerCAmelCase     ,   """w"""     ,   encoding="""utf-8"""							) as f:
									f.write(json.dumps(self.encoder     ,   indent=2     ,   sort_keys=__lowerCAmelCase     ,   ensure_ascii=__lowerCAmelCase							) + """\n"""							)

							UpperCamelCase__								=						0
							with open(__lowerCAmelCase     ,   """w"""     ,   encoding="""utf-8"""							) as writer:
									writer.write("""#version: 0.2\n"""							)
									for bpe_tokens, token_index in sorted(self.bpe_ranks.items()     ,   key=lambda __lowerCAmelCase							: kv[1]							):
											if index != token_index:
													logger.warning(
													    F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
													    """ Please check that the tokenizer is not corrupted!"""							)
													UpperCamelCase__								=						token_index
											writer.write(""" """.join(__lowerCAmelCase							) + """\n"""							)
											index += 1

							return vocab_file, merge_file




					def 						snake_case_		(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase = None							)    ->	List[int]:
							if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							UpperCamelCase__								=						[self.cls_token_id]
							UpperCamelCase__								=						[self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep




					def 						snake_case_		(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase = None     ,   __lowerCAmelCase = False							)    ->	List[int]:
							if already_has_special_tokens:
									return super().get_special_tokens_mask(
									    token_ids_a=__lowerCAmelCase     ,   token_ids_a=__lowerCAmelCase     ,   already_has_special_tokens=__lowerCAmelCase							)

							if token_ids_a is None:
									return [1] + ([0] * len(__lowerCAmelCase							)) + [1]
							return [1] + ([0] * len(__lowerCAmelCase							)) + [1, 1] + ([0] * len(__lowerCAmelCase							)) + [1]




					def 						snake_case_		(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase = None							)    ->	List[int]:
							UpperCamelCase__								=						[self.sep_token_id]
							UpperCamelCase__								=						[self.cls_token_id]

							if token_ids_a is None:
									return len(cls + token_ids_a + sep							) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep							) * [0]




					def 						snake_case_		(    self     ,   __lowerCAmelCase     ,   __lowerCAmelCase=False     ,   **__lowerCAmelCase							)    ->	Optional[Any]:
							UpperCamelCase__								=						kwargs.pop("""add_prefix_space"""     ,   self.add_prefix_space							)
							if (is_split_into_words or add_prefix_space) and (len(__lowerCAmelCase							) > 0 and not text[0].isspace()):
									UpperCamelCase__								=						""" """ + text
							return (text, kwargs)





