


'''simple docstring'''
import gc
import threading
import time

import psutil
import torch
class        lowercase     :

		"""simple docstring"""

		def __init__(		self							):

							'''simple docstring'''


							UpperCamelCase__       :int							 =			psutil.Process()
							UpperCamelCase__       :List[Any]							 =			False




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Union[str, Any]							 =			-1

							while True:
												UpperCamelCase__       :List[str]							 =			max(self.process.memory_info().rss   ,       self.cpu_memory_peak							)

												# can't sleep or will not catch the peak right (this comment is here on purpose)
												if not self.peak_monitoring:
																	break




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Any							 =			True
							UpperCamelCase__       :List[Any]							 =			threading.Thread(target=self.peak_monitor							)
							UpperCamelCase__       :Union[str, Any]							 =			True
							self.thread.start()




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Dict							 =			False
							self.thread.join()
							return self.cpu_memory_peak



__snake_case											=					PeakCPUMemory()


def       a				(      )  ->     Any:



					'''simple docstring'''






					UpperCamelCase__       :Optional[Any]							 =			{'''time''': time.time()}

					gc.collect()
					torch.cuda.empty_cache()

					# CPU mem
					UpperCamelCase__       :int							 =			psutil.Process().memory_info().rss
					cpu_peak_tracker.start()

					# GPU mem
					for i in range(torch.cuda.device_count()       ):
										UpperCamelCase__       :Union[str, Any]							 =			torch.cuda.memory_allocated(__a       )
					torch.cuda.reset_peak_memory_stats()

					return measures


def       a				(      __a       )  ->     List[str]:



					'''simple docstring'''






					UpperCamelCase__       :Union[str, Any]							 =			{'''time''': time.time() - start_measures['''time''']}

					gc.collect()
					torch.cuda.empty_cache()

					# CPU mem
					UpperCamelCase__       :List[Any]							 =			(psutil.Process().memory_info().rss - start_measures['''cpu''']) / 2**20
					UpperCamelCase__       :Any							 =			(cpu_peak_tracker.stop() - start_measures['''cpu''']) / 2**20

					# GPU mem
					for i in range(torch.cuda.device_count()       ):
										UpperCamelCase__       :Optional[Any]							 =			(torch.cuda.memory_allocated(__a       ) - start_measures[str(__a       )]) / 2**20
										UpperCamelCase__       :int							 =			(torch.cuda.max_memory_allocated(__a       ) - start_measures[str(__a       )]) / 2**20

					return measures







def       a				(      __a			, __a       )  ->     Any:



					'''simple docstring'''






					print(f'''{description}:'''       )
					print(f'''- Time: {measures["time"]:.2f}s'''       )
					for i in range(torch.cuda.device_count()       ):
										print(f'''- GPU {i} allocated: {measures[str(__a       )]:.2f}MiB'''       )
										UpperCamelCase__       :Optional[Any]							 =			measures[f'''{i}-peak''']
										print(f'''- GPU {i} peak: {peak:.2f}MiB'''       )
					print(f'''- CPU RAM allocated: {measures["cpu"]:.2f}MiB'''       )
					print(f'''- CPU RAM peak: {measures["cpu-peak"]:.2f}MiB'''       )



'''simple docstring'''
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


__snake_case											=					logging.get_logger(__name__)

__snake_case											=					{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__snake_case											=					{
    '''vocab_file''': {
        '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt''',
        '''distilbert-base-uncased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt'''
        ),
        '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt''',
        '''distilbert-base-cased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt'''
        ),
        '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt''',
        '''distilbert-base-multilingual-cased''': (
            '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json''',
        '''distilbert-base-uncased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json''',
        '''distilbert-base-cased-distilled-squad''': (
            '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-german-cased''': (
            '''https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json'''
        ),
        '''distilbert-base-multilingual-cased''': (
            '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json'''
        ),
    },
}

__snake_case											=					{
    '''distilbert-base-uncased''': 512,
    '''distilbert-base-uncased-distilled-squad''': 512,
    '''distilbert-base-cased''': 512,
    '''distilbert-base-cased-distilled-squad''': 512,
    '''distilbert-base-german-cased''': 512,
    '''distilbert-base-multilingual-cased''': 512,
}


__snake_case											=					{
    '''distilbert-base-uncased''': {'''do_lower_case''': True},
    '''distilbert-base-uncased-distilled-squad''': {'''do_lower_case''': True},
    '''distilbert-base-cased''': {'''do_lower_case''': False},
    '''distilbert-base-cased-distilled-squad''': {'''do_lower_case''': False},
    '''distilbert-base-german-cased''': {'''do_lower_case''': False},
    '''distilbert-base-multilingual-cased''': {'''do_lower_case''': False},
}
class        lowercase     (							A__ ):

		"""simple docstring"""

		_a   			=    VOCAB_FILES_NAMES
		_a   			=    PRETRAINED_VOCAB_FILES_MAP
		_a   			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_a   			=    PRETRAINED_INIT_CONFIGURATION
		_a   			=    ['input_ids', 'attention_mask']
		_a   			=    DistilBertTokenizer




		def __init__(		self   ,       UpperCamelCase_=None   ,       UpperCamelCase_=None   ,       UpperCamelCase_=True   ,       UpperCamelCase_="[UNK]"   ,       UpperCamelCase_="[SEP]"   ,       UpperCamelCase_="[PAD]"   ,       UpperCamelCase_="[CLS]"   ,       UpperCamelCase_="[MASK]"   ,       UpperCamelCase_=True   ,       UpperCamelCase_=None   ,       **UpperCamelCase_   ,       ):

							'''simple docstring'''


							super().__init__(
							    UpperCamelCase_   ,       tokenizer_file=UpperCamelCase_   ,       do_lower_case=UpperCamelCase_   ,       unk_token=UpperCamelCase_   ,       sep_token=UpperCamelCase_   ,       pad_token=UpperCamelCase_   ,       cls_token=UpperCamelCase_   ,       mask_token=UpperCamelCase_   ,       tokenize_chinese_chars=UpperCamelCase_   ,       strip_accents=UpperCamelCase_   ,       **UpperCamelCase_   ,       )

							UpperCamelCase__       :int							 =			json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
							if (
							    normalizer_state.get('''lowercase'''   ,       UpperCamelCase_							) != do_lower_case
							    or normalizer_state.get('''strip_accents'''   ,       UpperCamelCase_							) != strip_accents
							    or normalizer_state.get('''handle_chinese_chars'''   ,       UpperCamelCase_							) != tokenize_chinese_chars
							):
												UpperCamelCase__       :int							 =			getattr(UpperCamelCase_   ,       normalizer_state.pop('''type'''							)							)
												UpperCamelCase__       :Optional[Any]							 =			do_lower_case
												UpperCamelCase__       :Optional[Any]							 =			strip_accents
												UpperCamelCase__       :List[Any]							 =			tokenize_chinese_chars
												UpperCamelCase__       :Any							 =			normalizer_class(**UpperCamelCase_							)

							UpperCamelCase__       :int							 =			do_lower_case




		def    lowerCAmelCase__    (		self   ,       UpperCamelCase_   ,       UpperCamelCase_=None							):

							'''simple docstring'''


							UpperCamelCase__       :Tuple							 =			[self.cls_token_id] + token_ids_a + [self.sep_token_id]

							if token_ids_a:
												output += token_ids_a + [self.sep_token_id]

							return output




		def    lowerCAmelCase__    (		self   ,       UpperCamelCase_   ,       UpperCamelCase_ = None							):

							'''simple docstring'''


							UpperCamelCase__       :List[str]							 =			[self.sep_token_id]
							UpperCamelCase__       :List[str]							 =			[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							) * [0] + len(token_ids_a + sep							) * [1]




		def    lowerCAmelCase__    (		self   ,       UpperCamelCase_   ,       UpperCamelCase_ = None							):

							'''simple docstring'''


							UpperCamelCase__       :str							 =			self._tokenizer.model.save(UpperCamelCase_   ,       name=UpperCamelCase_							)
							return tuple(UpperCamelCase_							)