






from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


if TYPE_CHECKING:
					from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType


__snake_case     :     Any       =  logging.get_logger(__name__)

__snake_case     :     Optional[Any]       =  {
    "microsoft/deberta-base": "https://huggingface.co/microsoft/deberta-base/resolve/main/config.json",
    "microsoft/deberta-large": "https://huggingface.co/microsoft/deberta-large/resolve/main/config.json",
    "microsoft/deberta-xlarge": "https://huggingface.co/microsoft/deberta-xlarge/resolve/main/config.json",
    "microsoft/deberta-base-mnli": "https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/config.json",
    "microsoft/deberta-large-mnli": "https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/config.json",
    "microsoft/deberta-xlarge-mnli": "https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/config.json",
}


class      __SCREAMING_SNAKE_CASE       ( __lowercase):
						_SCREAMING_SNAKE_CASE						:							Union[str, Any]				=       '''deberta'''






						def __init__(						self  ,    _UpperCamelCase=5_02_65  ,    _UpperCamelCase=7_68  ,    _UpperCamelCase=12  ,    _UpperCamelCase=12  ,    _UpperCamelCase=30_72  ,    _UpperCamelCase="gelu"  ,    _UpperCamelCase=0.1  ,    _UpperCamelCase=0.1  ,    _UpperCamelCase=5_12  ,    _UpperCamelCase=0  ,    _UpperCamelCase=0.02  ,    _UpperCamelCase=1E-7  ,    _UpperCamelCase=False  ,    _UpperCamelCase=-1  ,    _UpperCamelCase=0  ,    _UpperCamelCase=True  ,    _UpperCamelCase=None  ,    _UpperCamelCase=0  ,    _UpperCamelCase="gelu"  ,    **_UpperCamelCase  ,    ):






												"""simple docstring"""
												super().__init__(**SCREAMING_SNAKE_CASE_ )

												lowerCAmelCase__         =    hidden_size
												lowerCAmelCase__         =    num_hidden_layers
												lowerCAmelCase__         =    num_attention_heads
												lowerCAmelCase__         =    intermediate_size
												lowerCAmelCase__         =    hidden_act
												lowerCAmelCase__         =    hidden_dropout_prob
												lowerCAmelCase__         =    attention_probs_dropout_prob
												lowerCAmelCase__         =    max_position_embeddings
												lowerCAmelCase__         =    type_vocab_size
												lowerCAmelCase__         =    initializer_range
												lowerCAmelCase__         =    relative_attention
												lowerCAmelCase__         =    max_relative_positions
												lowerCAmelCase__         =    pad_token_id
												lowerCAmelCase__         =    position_biased_input

												# Backwards compatibility
												if type(SCREAMING_SNAKE_CASE_ ) == str:
																		lowerCAmelCase__         =    [x.strip() for x in pos_att_type.lower().split('|' )]

												lowerCAmelCase__         =    pos_att_type
												lowerCAmelCase__         =    vocab_size
												lowerCAmelCase__         =    layer_norm_eps

												lowerCAmelCase__         =    kwargs.get('pooler_hidden_size'  ,    SCREAMING_SNAKE_CASE_ )
												lowerCAmelCase__         =    pooler_dropout
												lowerCAmelCase__         =    pooler_hidden_act




class      __SCREAMING_SNAKE_CASE       ( __lowercase):






						@property
						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												if self.task == "multiple-choice":
																		lowerCAmelCase__         =    {0: 'batch', 1: 'choice', 2: 'sequence'}
												else:
																		lowerCAmelCase__         =    {0: 'batch', 1: 'sequence'}
												if self._config.type_vocab_size > 0:
																		return OrderedDict(
																		    [('input_ids', dynamic_axis), ('attention_mask', dynamic_axis), ('token_type_ids', dynamic_axis)] )
												else:
																		return OrderedDict([('input_ids', dynamic_axis), ('attention_mask', dynamic_axis)] )






						@property
						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												return 12







						def    UpperCamelCase__   (						self  ,    _UpperCamelCase  ,    _UpperCamelCase = -1  ,    _UpperCamelCase = -1  ,    _UpperCamelCase = -1  ,    _UpperCamelCase = False  ,    _UpperCamelCase = None  ,    _UpperCamelCase = 3  ,    _UpperCamelCase = 40  ,    _UpperCamelCase = 40  ,    _UpperCamelCase = None  ,    ):






												"""simple docstring"""
												lowerCAmelCase__         =    super().generate_dummy_inputs(preprocessor=SCREAMING_SNAKE_CASE_  ,    framework=SCREAMING_SNAKE_CASE_ )
												if self._config.type_vocab_size == 0 and "token_type_ids" in dummy_inputs:
																		del dummy_inputs["token_type_ids"]
												return dummy_inputs







import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class  _lowerCamelCase			(lowerCamelCase							,					unittest.TestCase					):
     lowercase__				  =			HerbertTokenizer
     lowercase__				  =			HerbertTokenizerFast
     lowercase__				  =			True

     def 						__lowerCamelCase				(  self    ):
            super().setUp()

            # Use a simpler test file without japanese/chinese characters
            with open(f'''{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'''							,       encoding='utf-8'    ) as f_data:
                   __snake_case						       =   f_data.read().replace('\n\n'							,       '\n'    ).strip()

            __snake_case						       =   [
                '<s>',
                '</s>',
                'l',
                'o',
                'w',
                'e',
                'r',
                's',
                't',
                'i',
                'd',
                'n',
                'w</w>',
                'r</w>',
                't</w>',
                'lo',
                'low',
                'er</w>',
                'low</w>',
                'lowest</w>',
                'newer</w>',
                'wider</w>',
                ',</w>',
                '<unk>',
            ]
            __snake_case						       =   dict(zip(SCREAMING_SNAKE_CASE_							,       range(len(SCREAMING_SNAKE_CASE_    )    )    )    )
            __snake_case						       =   ['l o 123', 'lo w 1456', 'e r</w> 1789', '']

            __snake_case						       =   os.path.join(self.tmpdirname							,       VOCAB_FILES_NAMES['vocab_file']    )
            __snake_case						       =   os.path.join(self.tmpdirname							,       VOCAB_FILES_NAMES['merges_file']    )
            with open(self.vocab_file							,       'w'    ) as fp:
                   fp.write(json.dumps(SCREAMING_SNAKE_CASE_    )    )
            with open(self.merges_file							,       'w'    ) as fp:
                   fp.write('\n'.join(SCREAMING_SNAKE_CASE_    )    )

     def 						__lowerCamelCase				(  self							,       SCREAMING_SNAKE_CASE_    ):
            __snake_case						       =   'lower newer'
            __snake_case						       =   'lower newer'
            return input_text, output_text

     def 						__lowerCamelCase				(  self    ):
            __snake_case						       =   self.tokenizer_class(vocab_file=self.vocab_file							,       merges_file=self.merges_file    )

            __snake_case						       =   'lower'
            __snake_case						       =   ['low', 'er</w>']
            __snake_case						       =   tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
            self.assertListEqual(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_    )

            __snake_case						       =   tokens + ['<unk>']
            __snake_case						       =   [16, 17, 23]
            self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_    )							,       SCREAMING_SNAKE_CASE_    )

     def 						__lowerCamelCase				(  self    ):
            if not self.test_rust_tokenizer:
                   return

            __snake_case						       =   self.get_tokenizer()
            __snake_case						       =   self.get_rust_tokenizer()

            __snake_case						       =   'lower,newer'

            __snake_case						       =   tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
            __snake_case						       =   rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE_    )
            self.assertListEqual(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_    )

            __snake_case						       =   tokenizer.encode(SCREAMING_SNAKE_CASE_							,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
            __snake_case						       =   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_							,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
            self.assertListEqual(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_    )

            __snake_case						       =   self.get_rust_tokenizer()
            __snake_case						       =   tokenizer.encode(SCREAMING_SNAKE_CASE_    )
            __snake_case						       =   rust_tokenizer.encode(SCREAMING_SNAKE_CASE_    )
            self.assertListEqual(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_    )

     @slow
     def 						__lowerCamelCase				(  self    ):
            __snake_case						       =   self.tokenizer_class.from_pretrained('allegro/herbert-base-cased'    )

            __snake_case						       =   tokenizer.encode('konstruowanie sekwencji'							,       add_special_tokens=SCREAMING_SNAKE_CASE_    )
            __snake_case						       =   tokenizer.encode('konstruowanie wielu sekwencji'							,       add_special_tokens=SCREAMING_SNAKE_CASE_    )

            __snake_case						       =   tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_    )
            __snake_case						       =   tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE_							,       SCREAMING_SNAKE_CASE_    )

            assert encoded_sentence == [0] + text + [2]
            assert encoded_pair == [0] + text + [2] + text_a + [2]
