'''simple docstring'''




import json
import os
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_A								=   logging.get_logger(__name__)

_A								=   {'vocab_file': 'vocab.json'}

_A								=   {
    'vocab_file': {
        'mgp-str': 'https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json',
    }
}

_A								=   {'mgp-str': 2_7}


class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       List[Any]     =    VOCAB_FILES_NAMES
   A							:       Union[str, Any]     =    PRETRAINED_VOCAB_FILES_MAP
   A							:       Tuple     =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   def __init__(self       ,				_a       ,				_a="[GO]"       ,				_a="[GO]"       ,				_a="[s]"       ,				_a="[GO]"       ,				**_a				)    ->     Tuple:
        super().__init__(
            unk_token=_a       ,				bos_token=_a       ,				eos_token=_a       ,				pad_token=_a       ,				**_a       ,				)

        with open(_a       ,				encoding='utf-8'				) as vocab_handle:
             lowercase_					:       Optional[Any]     				=					json.load(_a				)
        lowercase_					:       Tuple     				=					{v: k for k, v in self.vocab.items()}
   @property
   def 		_lowerCamelCase (self				)    ->     Tuple:
        return len(self.vocab				)
   def 		_lowerCamelCase (self				)    ->     Union[str, Any]:
        return dict(self.vocab       ,				**self.added_tokens_encoder				)
   def 		_lowerCamelCase (self       ,				_a				)    ->     List[str]:
        lowercase_					:       Tuple     				=					[]
        for s in text:
             char_tokens.extend(_a				)
        return char_tokens
   def 		_lowerCamelCase (self       ,				_a				)    ->     Optional[int]:
        return self.vocab.get(_a       ,				self.vocab.get(self.unk_token				)				)
   def 		_lowerCamelCase (self       ,				_a				)    ->     Tuple:
        return self.decoder.get(_a				)





   def 		_lowerCamelCase (self       ,				_a       ,				_a = None				)    ->     Tuple[str]:
        if not os.path.isdir(_a				):
             logger.error('Vocabulary path ({}) should be a directory'.format(_a				)				)
             return
        lowercase_					:       List[Any]     				=					os.path.join(
            _a       ,				(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

        with open(_a       ,				'w'       ,				encoding='utf-8'				) as f:
             f.write(json.dumps(self.vocab       ,				indent=2       ,				sort_keys=_a       ,				ensure_ascii=_a				) + '\n'				)

        return (vocab_file,)





'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


_A								=   logging.get_logger(__name__)

_A								=   {
    'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}


class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       Any     =    '''mra'''
   def __init__(self       ,				_a=50_265       ,				_a=768       ,				_a=12       ,				_a=12       ,				_a=3_072       ,				_a="gelu"       ,				_a=0.1       ,				_a=0.1       ,				_a=512       ,				_a=1       ,				_a=0.02       ,				_a=1e-5       ,				_a="absolute"       ,				_a=4       ,				_a="full"       ,				_a=0       ,				_a=0       ,				_a=1       ,				_a=0       ,				_a=2       ,				**_a       ,				)    ->     int:
        super().__init__(pad_token_id=_a       ,				bos_token_id=_a       ,				eos_token_id=_a       ,				**_a				)

        lowercase_					:       Union[str, Any]     				=					vocab_size
        lowercase_					:       List[str]     				=					max_position_embeddings
        lowercase_					:       Optional[Any]     				=					hidden_size
        lowercase_					:       Optional[int]     				=					num_hidden_layers
        lowercase_					:       Dict     				=					num_attention_heads
        lowercase_					:       Optional[int]     				=					intermediate_size
        lowercase_					:       Dict     				=					hidden_act
        lowercase_					:       str     				=					hidden_dropout_prob
        lowercase_					:       int     				=					attention_probs_dropout_prob
        lowercase_					:       str     				=					initializer_range
        lowercase_					:       Union[str, Any]     				=					type_vocab_size
        lowercase_					:       Any     				=					layer_norm_eps
        lowercase_					:       Union[str, Any]     				=					position_embedding_type
        lowercase_					:       Any     				=					block_per_row
        lowercase_					:       Optional[int]     				=					approx_mode
        lowercase_					:       int     				=					initial_prior_first_n_blocks
        lowercase_					:       str     				=					initial_prior_diagonal_n_blocks




