

import argparse
import os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

a_     =			logging.get_logger(__name__)


a_     =			{name: getattr(transformers, name + 'Fast') for name in SLOW_TO_FAST_CONVERTERS}

def        lowerCamelCase__       (    _a							,	_a							,	_a							,	_a):
	if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
		raise ValueError(f"Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys())}.")

	if tokenizer_name is None:
		SCREAMING_SNAKE_CASE      :					List[str]    =				TOKENIZER_CLASSES
	else:
		SCREAMING_SNAKE_CASE      :					Union[str, Any]    =				{tokenizer_name: getattr(snake_case_							,	tokenizer_name + "Fast")}

	logger.info(f"Loading tokenizer classes: {tokenizer_names}")

	for tokenizer_name in tokenizer_names:
		SCREAMING_SNAKE_CASE      :					Tuple    =				TOKENIZER_CLASSES[tokenizer_name]

		SCREAMING_SNAKE_CASE      :					Optional[int]    =				True
		if checkpoint_name is None:
			SCREAMING_SNAKE_CASE      :					int    =				list(tokenizer_class.max_model_input_sizes.keys())
		else:
			SCREAMING_SNAKE_CASE      :					Dict    =				[checkpoint_name]

		logger.info(f"For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}")

		for checkpoint in checkpoint_names:
			logger.info(f"Loading {tokenizer_class.__class__.__name__} {checkpoint}")

			# Load tokenizer
			SCREAMING_SNAKE_CASE      :					List[Any]    =				tokenizer_class.from_pretrained(snake_case_							,	force_download=snake_case_)

			# Save fast tokenizer
			logger.info(f"Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}")

			# For organization names we create sub-directories
			if "/" in checkpoint:
				SCREAMING_SNAKE_CASE      :					Any    =				checkpoint.split("/")
				SCREAMING_SNAKE_CASE      :					Optional[Any]    =				os.path.join(snake_case_							,	snake_case_)
			elif add_prefix:
				SCREAMING_SNAKE_CASE      :					Optional[int]    =				checkpoint
				SCREAMING_SNAKE_CASE      :					List[str]    =				dump_path
			else:
				SCREAMING_SNAKE_CASE      :					List[Any]    =				None
				SCREAMING_SNAKE_CASE      :					int    =				dump_path

			logger.info(f"=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}")

			if checkpoint in list(tokenizer.pretrained_vocab_files_map.values())[0]:
				SCREAMING_SNAKE_CASE      :					Tuple    =				list(tokenizer.pretrained_vocab_files_map.values())[0][checkpoint]
				SCREAMING_SNAKE_CASE      :					List[Any]    =				file_path.split(snake_case_)[-1][0]
				if next_char == "/":
					SCREAMING_SNAKE_CASE      :					Optional[Any]    =				os.path.join(snake_case_							,	snake_case_)
					SCREAMING_SNAKE_CASE      :					List[str]    =				None

				logger.info(f"=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}")

			SCREAMING_SNAKE_CASE      :					Optional[Any]    =				tokenizer.save_pretrained(
			    snake_case_							,	legacy_format=snake_case_							,	filename_prefix=snake_case_)
			logger.info(f"=> File names {file_names}")

			for file_name in file_names:
				if not file_name.endswith("tokenizer.json"):
					os.remove(snake_case_)
					logger.info(f"=> removing {file_name}")


if __name__ == "__main__":
			a_     =			argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    '--dump_path', default=None, type=str, required=True, help='Path to output generated fast tokenizer files.'
			)
			parser.add_argument(
			    '--tokenizer_name',
			    default=None,
			    type=str,
			    help=(
			        F'''Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will '''
			        'download and convert all the checkpoints from AWS.'
			    ),
			)
			parser.add_argument(
			    '--checkpoint_name',
			    default=None,
			    type=str,
			    help='Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.',
			)
			parser.add_argument(
			    '--force_download',
			    action='store_true',
			    help='Re-download checkpoints.',
			)
			a_     =			parser.parse_args()

			convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)





import requests
from bsa import BeautifulSoup







def 				lowerCAmelCase_	(     snake_case_ = "AAPL"     ):
      _A							:     str			=						f'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
      _A							:     List[Any]			=						BeautifulSoup(requests.get(snake_case_     ).text,"""html.parser"""     )
      _A							:     Union[str, Any]			=						"""My(6px) Pos(r) smartphone_Mt(6px)"""
      return soup.find("""div""",class_=class_     ).find("""span"""     ).text


if __name__ == "__main__":
  for symbol in "AAPL AMZN IBM GOOG MSFT ORCL".split():
    print(f"""Current {symbol:<4} stock price is {stock_price(symbol):>8}""")

