
"""simple docstring"""





import math

import flax.linen as nn
import jax.numpy as jnp
def 							A_     (__a				,   __a				,   __a = 1				,   __a = 1				,   __a = 1.0e4				,   __a = False				,   __a = 1.0				,   ):

					'''simple docstring'''





					assert timesteps.ndim == 1, "Timesteps should be a 1d-array"
					assert embedding_dim % 2 == 0, f'Embedding dimension {embedding_dim} should be even'
					A_				 =						float(embedding_dim // 2				)
					A_				 =						math.log(max_timescale / min_timescale				) / (num_timescales - freq_shift)
					A_				 =						min_timescale * jnp.exp(jnp.arange(__a				,   dtype=jnp.floataa				) * -log_timescale_increment				)
					A_				 =						jnp.expand_dims(__a				,   1				) * jnp.expand_dims(__a				,   0				)

					# scale embeddings
					A_				 =						scale * emb

					if flip_sin_to_cos:
										A_				 =						jnp.concatenate([jnp.cos(__a				), jnp.sin(__a				)]				,   axis=1				)
					else:
										A_				 =						jnp.concatenate([jnp.sin(__a				), jnp.cos(__a				)]				,   axis=1				)
					A_				 =						jnp.reshape(__a				,   [jnp.shape(__a				)[0], embedding_dim]				)
					return signal



class __lowerCAmelCase				(					nn.Module      ):




			"""simple docstring"""







			snake_case	      =				32
			snake_case	      =				jnp.floataa




			@nn.compact
			def __call__(				self						:					List[str]       ,   _snake_case						:					List[str]	)      -> Any:







								"""simple docstring"""
								A_				 =						nn.Dense(self.time_embed_dim       ,   dtype=self.dtype       ,   name="linear_1"	)(_snake_case	)
								A_				 =						nn.silu(_snake_case	)
								A_				 =						nn.Dense(self.time_embed_dim       ,   dtype=self.dtype       ,   name="linear_2"	)(_snake_case	)
								return temb





class __lowerCAmelCase				(					nn.Module      ):




			"""simple docstring"""







			snake_case	      =				32
			snake_case	      =				False
			snake_case	      =				1




			@nn.compact
			def __call__(				self						:					int       ,   _snake_case						:					Dict	)      -> List[Any]:







								"""simple docstring"""
								return get_sinusoidal_embeddings(
								    _snake_case       ,   embedding_dim=self.dim       ,   flip_sin_to_cos=self.flip_sin_to_cos       ,   freq_shift=self.freq_shift	)






"""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_retribert import RetriBertTokenizer


UpperCamelCase_					:						Any				= logging.get_logger(__name__)

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

UpperCamelCase_					:						List[str]				= {
    '''vocab_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

UpperCamelCase_					:						Union[str, Any]				= {
    '''yjernite/retribert-base-uncased''': 512,
}


UpperCamelCase_					:						str				= {
    '''yjernite/retribert-base-uncased''': {'''do_lower_case''': True},
}



class __lowerCAmelCase				(					_lowercase      ):




			"""simple docstring"""







			snake_case	      =				VOCAB_FILES_NAMES
			snake_case	      =				PRETRAINED_VOCAB_FILES_MAP
			snake_case	      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			snake_case	      =				PRETRAINED_INIT_CONFIGURATION
			snake_case	      =				RetriBertTokenizer
			snake_case	      =				["input_ids", "attention_mask"]




			def __init__(				self						:					Tuple       ,   _snake_case						:					int=None       ,   _snake_case						:					Any=None       ,   _snake_case						:					str=True       ,   _snake_case						:					List[Any]="[UNK]"       ,   _snake_case						:					Optional[Any]="[SEP]"       ,   _snake_case						:					str="[PAD]"       ,   _snake_case						:					List[str]="[CLS]"       ,   _snake_case						:					List[str]="[MASK]"       ,   _snake_case						:					Dict=True       ,   _snake_case						:					Optional[int]=None       ,   **_snake_case						:					Tuple       ,   )      -> Union[str, Any]:







								"""simple docstring"""
								super().__init__(
								    _snake_case       ,   tokenizer_file=_snake_case       ,   do_lower_case=_snake_case       ,   unk_token=_snake_case       ,   sep_token=_snake_case       ,   pad_token=_snake_case       ,   cls_token=_snake_case       ,   mask_token=_snake_case       ,   tokenize_chinese_chars=_snake_case       ,   strip_accents=_snake_case       ,   **_snake_case       ,   )

								A_				 =						json.loads(self.backend_tokenizer.normalizer.__getstate__()	)
								if (
								    normalizer_state.get("lowercase"       ,   _snake_case	) != do_lower_case
								    or normalizer_state.get("strip_accents"       ,   _snake_case	) != strip_accents
								    or normalizer_state.get("handle_chinese_chars"       ,   _snake_case	) != tokenize_chinese_chars
								):
													A_				 =						getattr(_snake_case       ,   normalizer_state.pop("type"	)	)
													A_				 =						do_lower_case
													A_				 =						strip_accents
													A_				 =						tokenize_chinese_chars
													A_				 =						normalizer_class(**_snake_case	)

								A_				 =						do_lower_case




			def      lowerCamelCase__     (				self						:					Union[str, Any]       ,   _snake_case						:					List[Any]       ,   _snake_case						:					Union[str, Any]=None	)      -> List[Any]:







								"""simple docstring"""
								A_				 =						[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						:					Any       ,   _snake_case						:					List[int]       ,   _snake_case						:					Optional[List[int]] = None	)      -> List[int]:







								"""simple docstring"""
								A_				 =						[self.sep_token_id]
								A_				 =						[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						:					Union[str, Any]       ,   _snake_case						:					str       ,   _snake_case						:					Optional[str] = None	)      -> Tuple[str]:







								"""simple docstring"""
								A_				 =						self._tokenizer.model.save(_snake_case       ,   name=_snake_case	)
								return tuple(_snake_case	)




