
"""simple docstring"""

import os
from typing import Dict, List, Union

import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs

from .tokenization_gpta import GPTaTokenizer
class      _UpperCAmelCase							(		tf.keras.layers.Layer							):




      def __init__(							self   ,       lowercase_   ,       lowercase_   ,       lowercase_ = None   ,       lowercase_ = None							)						->					List[str]:
          super().__init__()
          UpperCAmelCase									=					pad_token_id
          UpperCAmelCase									=					max_length
          UpperCAmelCase									=					vocab
          UpperCAmelCase									=					merges
          UpperCAmelCase									=					BytePairTokenizer(lowercase_   ,       lowercase_   ,       sequence_length=lowercase_							)




      @classmethod
      def     a_      (							cls   ,       lowercase_   ,       *lowercase_   ,       **lowercase_							)						->					Optional[int]:
          UpperCAmelCase									=					[' '.join(lowercase_							) for m in tokenizer.bpe_ranks.keys()]
          UpperCAmelCase									=					tokenizer.get_vocab()
          return cls(lowercase_   ,       lowercase_   ,       *lowercase_   ,       **lowercase_							)




      @classmethod
      def     a_      (							cls   ,       lowercase_   ,       *lowercase_   ,       **lowercase_							)						->					Union[str, Any]:
          UpperCAmelCase									=					GPTaTokenizer.from_pretrained(lowercase_   ,       *lowercase_   ,       **lowercase_							)
          return cls.from_tokenizer(lowercase_   ,       *lowercase_   ,       **lowercase_							)




      @classmethod
      def     a_      (							cls   ,       lowercase_							)						->					Union[str, Any]:
          return cls(**lowercase_							)




      def     a_      (							self							)						->					Optional[int]:
          return {
              "vocab": self.vocab,
              "merges": self.merges,
              "max_length": self.max_length,
              "pad_token_id": self.pad_token_id,
          }




      def     a_      (							self   ,       lowercase_   ,       lowercase_ = None							)						->					int:
          UpperCAmelCase									=					self.tf_tokenizer(lowercase_							)
          UpperCAmelCase									=					tf.ones_like(lowercase_							)

          if self.pad_token_id is not None:
              # pad the tokens up to max length
              UpperCAmelCase									=					max_length if max_length is not None else self.max_length

              if max_length is not None:
                  UpperCAmelCase			,							UpperCAmelCase									=					pad_model_inputs(
                      lowercase_   ,       max_seq_length=lowercase_   ,       pad_value=self.pad_token_id							)

          return {"attention_mask": attention_mask, "input_ids": input_ids}





"""simple docstring"""

def     lowercase__						(					lowerCAmelCase				:					int ,				lowerCAmelCase				:					list ) ->      int:






    """simple docstring"""




    _enforce_args(lowerCAmelCase ,				lowerCAmelCase )
    if n == 0:
        return 0
    UpperCAmelCase									=					float('-inf' )
    for i in range(1 ,				n + 1 ):
        UpperCAmelCase									=					max(
            lowerCAmelCase ,				prices[i - 1] + naive_cut_rod_recursive(n - i ,				lowerCAmelCase ) )

    return max_revue




def     lowercase__						(					lowerCAmelCase				:					int ,				lowerCAmelCase				:					list ) ->      Dict:






    """simple docstring"""




    _enforce_args(lowerCAmelCase ,				lowerCAmelCase )
    UpperCAmelCase									=					[float('-inf' ) for _ in range(n + 1 )]
    return _top_down_cut_rod_recursive(lowerCAmelCase ,				lowerCAmelCase ,				lowerCAmelCase )




def     lowercase__						(					lowerCAmelCase				:					int ,				lowerCAmelCase				:					list ,				lowerCAmelCase				:					list ) ->      int:






    """simple docstring"""




    if max_rev[n] >= 0:
        return max_rev[n]
    elif n == 0:
        return 0
    else:
        UpperCAmelCase									=					float('-inf' )
        for i in range(1 ,				n + 1 ):
            UpperCAmelCase									=					max(
                lowerCAmelCase ,				prices[i - 1] + _top_down_cut_rod_recursive(n - i ,				lowerCAmelCase ,				lowerCAmelCase ) ,				)

        UpperCAmelCase									=					max_revenue

    return max_rev[n]




def     lowercase__						(					lowerCAmelCase				:					int ,				lowerCAmelCase				:					list ) ->      Optional[int]:






    """simple docstring"""




    _enforce_args(lowerCAmelCase ,				lowerCAmelCase )

    # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
    # length 0.
    UpperCAmelCase									=					[float('-inf' ) for _ in range(n + 1 )]
    UpperCAmelCase									=					0

    for i in range(1 ,				n + 1 ):
        UpperCAmelCase									=					max_rev[i]
        for j in range(1 ,				i + 1 ):
            UpperCAmelCase									=					max(lowerCAmelCase ,				prices[j - 1] + max_rev[i - j] )

        UpperCAmelCase									=					max_revenue_i

    return max_rev[n]




def     lowercase__						(					lowerCAmelCase				:					int ,				lowerCAmelCase				:					list ) ->      Union[str, Any]:






    """simple docstring"""




    if n < 0:
        UpperCAmelCase									=					F"n must be greater than or equal to 0. Got n = {n}"
        raise ValueError(lowerCAmelCase )

    if n > len(lowerCAmelCase ):
        UpperCAmelCase									=					(
            'Each integral piece of rod must have a corresponding price. '
            F"Got n = {n} but length of prices = {len(lowerCAmelCase )}"
        )
        raise ValueError(lowerCAmelCase )




def     lowercase__						(					) ->      Optional[int]:






    """simple docstring"""




    UpperCAmelCase									=					[6, 10, 12, 15, 20, 23]
    UpperCAmelCase									=					len(lowerCAmelCase )

    # the best revenue comes from cutting the rod into 6 pieces, each
    # of length 1 resulting in a revenue of 6 * 6 = 36.
    UpperCAmelCase									=					36

    UpperCAmelCase									=					top_down_cut_rod(lowerCAmelCase ,				lowerCAmelCase )
    UpperCAmelCase									=					bottom_up_cut_rod(lowerCAmelCase ,				lowerCAmelCase )
    UpperCAmelCase									=					naive_cut_rod_recursive(lowerCAmelCase ,				lowerCAmelCase )

    assert expected_max_revenue == max_rev_top_down
    assert max_rev_top_down == max_rev_bottom_up
    assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
   main()



