


'''simple docstring'''




import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin

class 						UpperCAmelCase_ (    _lowercase			,      _lowercase			,      _lowercase						):





     @register_to_config
     def __init__(					self			: List[Any]       , UpperCAmelCase__			: Any       , UpperCAmelCase__			: Any       , UpperCAmelCase__			: Optional[Any]       , UpperCAmelCase__			: str       , UpperCAmelCase__			: Tuple       , UpperCAmelCase__			: Any       , UpperCAmelCase__			: Any       , UpperCAmelCase__			: Union[str, Any]       , UpperCAmelCase__			: Optional[Any]       , UpperCAmelCase__			: Tuple = False       , )							->    Union[str, Any]:
        super().__init__()

        lowerCAmelCase	=     nn.Embedding(__SCREAMING_SNAKE_CASE       , __SCREAMING_SNAKE_CASE       )

        lowerCAmelCase	=     nn.Embedding(__SCREAMING_SNAKE_CASE       , __SCREAMING_SNAKE_CASE       )
        lowerCAmelCase	=     False

        lowerCAmelCase	=     nn.Dropout(p=__SCREAMING_SNAKE_CASE       )

        lowerCAmelCase	=     TaConfig(
            vocab_size=__SCREAMING_SNAKE_CASE       , d_model=__SCREAMING_SNAKE_CASE       , num_heads=__SCREAMING_SNAKE_CASE       , d_kv=__SCREAMING_SNAKE_CASE       , d_ff=__SCREAMING_SNAKE_CASE       , dropout_rate=__SCREAMING_SNAKE_CASE       , feed_forward_proj=__SCREAMING_SNAKE_CASE       , is_decoder=__SCREAMING_SNAKE_CASE       , is_encoder_decoder=__SCREAMING_SNAKE_CASE       , )

        lowerCAmelCase	=     nn.ModuleList()
        for lyr_num in range(__SCREAMING_SNAKE_CASE       ):
           lowerCAmelCase	=     TaBlock(__SCREAMING_SNAKE_CASE       )
           self.encoders.append(__SCREAMING_SNAKE_CASE       )

        lowerCAmelCase	=     TaLayerNorm(__SCREAMING_SNAKE_CASE       )
        lowerCAmelCase	=     nn.Dropout(p=__SCREAMING_SNAKE_CASE       )





     def 				__UpperCAmelCase (					self			: int       , UpperCAmelCase__			: str       , UpperCAmelCase__			: Optional[Any]       )							->    List[Any]:
        lowerCAmelCase	=     self.token_embedder(__SCREAMING_SNAKE_CASE       )

        lowerCAmelCase	=     encoder_input_tokens.shape[1]
        lowerCAmelCase	=     torch.arange(__SCREAMING_SNAKE_CASE       , device=encoder_input_tokens.device       )
        x += self.position_encoding(__SCREAMING_SNAKE_CASE       )

        lowerCAmelCase	=     self.dropout_pre(__SCREAMING_SNAKE_CASE       )

        # inverted the attention mask
        lowerCAmelCase	=     encoder_input_tokens.size()
        lowerCAmelCase	=     self.get_extended_attention_mask(__SCREAMING_SNAKE_CASE       , __SCREAMING_SNAKE_CASE       )

        for lyr in self.encoders:
           lowerCAmelCase	=     lyr(__SCREAMING_SNAKE_CASE       , __SCREAMING_SNAKE_CASE       )[0]
        lowerCAmelCase	=     self.layer_norm(__SCREAMING_SNAKE_CASE       )

        return self.dropout_post(__SCREAMING_SNAKE_CASE       ), encoder_inputs_mask







"""simple docstring"""




from __future__ import annotations



def     __magic_name__		(					UpperCamelCase     :		str							,		UpperCamelCase     :		list[str] | None = None     )     ->						list[list[str]]:
    a__		=			word_bank or []
    # create a table
    a__		=			len(UpperCamelCase     ) + 1

    a__		=			[]
    for _ in range(UpperCamelCase     ):
        table.append([]     )
    # seed value
    a__		=			[[]]  # because empty string has empty combination

    # iterate through the indices
    for i in range(UpperCamelCase     ):
        # condition
        if table[i] != []:
            for word in word_bank:
                # slice condition
                if target[i : i + len(UpperCamelCase     )] == word:
                    a__		=			[
                        [word, *way] for way in table[i]
                    ]
                    # adds the word to every combination the current position holds
                    # now,push that combination to the table[i+len(word)]
                    table[i + len(UpperCamelCase     )] += new_combinations

    # combinations are in reverse order so reverse for better output
    for combination in table[len(UpperCamelCase     )]:
        combination.reverse()

    return table[len(UpperCamelCase     )]


if __name__ == "__main__":
    print(all_construct('jwajalapa', ['jwa', 'j', 'w', 'a', 'la', 'lapa']))
    print(all_construct('rajamati', ['s', 'raj', 'amat', 'raja', 'ma', 'i', 't']))
    print(
        all_construct(
            'hexagonosaurus',
            ['h', 'ex', 'hex', 'ag', 'ago', 'ru', 'auru', 'rus', 'go', 'no', 'o', 's'],
        )
    )


