



"""simple docstring"""

import argparse
import logging
import pickle
import random
import time

import numpy as np

from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
lowercase__    :  str							    =	logging.getLogger(__name__)




def __lowercase			(							):
    snake_case_ :     Union[str, Any]				=	argparse.ArgumentParser(
        description='''Preprocess the data to avoid re-doing it several times by (tokenization + token_to_ids).'''    )
    parser.add_argument('''--file_path'''		,			type=__A		,			default='''data/dump.txt'''		,			help='''The path to the data.'''    )
    parser.add_argument('''--tokenizer_type'''		,			type=__A		,			default='''bert'''		,			choices=['''bert''', '''roberta''', '''gpt2''']    )
    parser.add_argument('''--tokenizer_name'''		,			type=__A		,			default='''bert-base-uncased'''		,			help='''The tokenizer to use.'''    )
    parser.add_argument('''--dump_file'''		,			type=__A		,			default='''data/dump'''		,			help='''The dump file prefix.'''    )
    snake_case_ :     Union[str, Any]				=	parser.parse_args()

    logger.info(f"Loading Tokenizer ({args.tokenizer_name})"    )
    if args.tokenizer_type == "bert":
        snake_case_ :     Dict				=	BertTokenizer.from_pretrained(args.tokenizer_name    )
        snake_case_ :     int				=	tokenizer.special_tokens_map['''cls_token''']  # `[CLS]`
        snake_case_ :     List[Any]				=	tokenizer.special_tokens_map['''sep_token''']  # `[SEP]`
    elif args.tokenizer_type == "roberta":
        snake_case_ :     Any				=	RobertaTokenizer.from_pretrained(args.tokenizer_name    )
        snake_case_ :     Optional[Any]				=	tokenizer.special_tokens_map['''cls_token''']  # `<s>`
        snake_case_ :     List[Any]				=	tokenizer.special_tokens_map['''sep_token''']  # `</s>`
    elif args.tokenizer_type == "gpt2":
        snake_case_ :     Union[str, Any]				=	GPTaTokenizer.from_pretrained(args.tokenizer_name    )
        snake_case_ :     int				=	tokenizer.special_tokens_map['''bos_token''']  # `<|endoftext|>`
        snake_case_ :     str				=	tokenizer.special_tokens_map['''eos_token''']  # `<|endoftext|>`

    logger.info(f"Loading text from {args.file_path}"    )
    with open(args.file_path		,			'''r'''		,			encoding='''utf8'''    ) as fp:
        snake_case_ :     Dict				=	fp.readlines()

    logger.info('''Start encoding'''    )
    logger.info(f"{len(__A    )} examples to process."    )

    snake_case_ :     Any				=	[]
    snake_case_ :     Any				=	0
    snake_case_ :     List[str]				=	10_000
    snake_case_ :     Any				=	time.time()
    for text in data:
        snake_case_ :     str				=	f"{bos} {text.strip()} {sep}"
        snake_case_ :     List[Any]				=	tokenizer.encode(__A		,			add_special_tokens=__A    )
        rslt.append(__A    )

        iter += 1
        if iter % interval == 0:
            snake_case_ :     Optional[Any]				=	time.time()
            logger.info(f"{iter} examples processed. - {(end-start):.2f}s/{interval}expl"    )
            snake_case_ :     Optional[Any]				=	time.time()
    logger.info('''Finished binarization'''    )
    logger.info(f"{len(__A    )} examples processed."    )

    snake_case_ :     int				=	f"{args.dump_file}.{args.tokenizer_name}.pickle"
    snake_case_ :     List[Any]				=	tokenizer.vocab_size
    if vocab_size < (1 << 16):
        snake_case_ :     Union[str, Any]				=	[np.uintaa(__A    ) for d in rslt]
    else:
        snake_case_ :     Union[str, Any]				=	[np.intaa(__A    ) for d in rslt]
    random.shuffle(rslt_    )
    logger.info(f"Dump to {dp_file}"    )
    with open(__A		,			'''wb'''    ) as handle:
        pickle.dump(rslt_		,			__A		,			protocol=pickle.HIGHEST_PROTOCOL    )


if __name__ == "__main__":
     main()






from __future__ import annotations

from scipy.special import comb  # type: ignore





class      A							:


   def __init__(self     :						List[Any]       ,  __UpperCAmelCase     :						list[tuple[float, float]]		)						->				List[str]:
         """simple docstring"""



         UpperCAmelCase__								=  list_of_points
         # Degree determines the flexibility of the curve.
         # Degree = 1 will produce a straight line.
         UpperCAmelCase__								=  len(__UpperCAmelCase		) - 1


   def 			lowercase_      (self     :						int       ,  __UpperCAmelCase     :						float		)						->				list[float]:
         """simple docstring"""



         assert 0 <= t <= 1, "Time t must be between 0 and 1."
         UpperCAmelCase__								=  []
         for i in range(len(self.list_of_points		)		):
               # basis function for each i
               output_values.append(
                   comb(self.degree       ,  __UpperCAmelCase		) * ((1 - t) ** (self.degree - i)) * (t**i)		)
         # the basis must sum up to 1 for it to produce a valid Bezier curve.
         assert round(sum(__UpperCAmelCase		)       ,  5		) == 1
         return output_values


   def 			lowercase_      (self     :						Dict       ,  __UpperCAmelCase     :						float		)						->				tuple[float, float]:
         """simple docstring"""



         assert 0 <= t <= 1, "Time t must be between 0 and 1."

         UpperCAmelCase__								=  self.basis_function(__UpperCAmelCase		)
         UpperCAmelCase__								=  0.0
         UpperCAmelCase__								=  0.0
         for i in range(len(self.list_of_points		)		):
               # For all points, sum up the product of i-th basis function and i-th point.
               x += basis_function[i] * self.list_of_points[i][0]
               y += basis_function[i] * self.list_of_points[i][1]
         return (x, y)





   def 			lowercase_      (self     :						Optional[int]       ,  __UpperCAmelCase     :						float = 0.01		)						->				Optional[int]:
         """simple docstring"""



         from matplotlib import pyplot as plt  # type: ignore

         UpperCAmelCase__								=  []  # x coordinates of points to plot
         UpperCAmelCase__								=  []  # y coordinates of points to plot

         UpperCAmelCase__								=  0.0
         while t <= 1:
               UpperCAmelCase__								=  self.bezier_curve_function(__UpperCAmelCase		)
               to_plot_x.append(value[0]		)
               to_plot_y.append(value[1]		)
               t += step_size

         UpperCAmelCase__								=  [i[0] for i in self.list_of_points]
         UpperCAmelCase__								=  [i[1] for i in self.list_of_points]

         plt.plot(
             __UpperCAmelCase       ,  __UpperCAmelCase       ,  color="blue"       ,  label="Curve of Degree " + str(self.degree		)       ,  )
         plt.scatter(__UpperCAmelCase       ,  __UpperCAmelCase       ,  color="red"       ,  label="Control Points"		)
         plt.legend()
         plt.show()


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      BezierCurve([(1, 2), (3, 5)]).plot_curve()  # degree 1
      BezierCurve([(0, 0), (5, 5), (5, 0)]).plot_curve()  # degree 2
      BezierCurve([(0, 0), (5, 5), (5, 0), (2.5, -2.5)]).plot_curve()  # degree 3



