


'''simple docstring'''




import argparse

import torch

# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./  # create simlink
# import classes
from unilm.wavlm.WavLM import WavLM as WavLMOrig
from unilm.wavlm.WavLM import WavLMConfig as WavLMConfigOrig

from transformers import WavLMConfig, WavLMModel, logging


logging.set_verbosity_info()
__UpperCAmelCase												=logging.get_logger(__name__)

__UpperCAmelCase												={
    'post_extract_proj': 'feature_projection.projection',
    'encoder.pos_conv.0': 'encoder.pos_conv_embed.conv',
    'self_attn.k_proj': 'encoder.layers.*.attention.k_proj',
    'self_attn.v_proj': 'encoder.layers.*.attention.v_proj',
    'self_attn.q_proj': 'encoder.layers.*.attention.q_proj',
    'self_attn.out_proj': 'encoder.layers.*.attention.out_proj',
    'self_attn.grep_linear': 'encoder.layers.*.attention.gru_rel_pos_linear',
    'self_attn.relative_attention_bias': 'encoder.layers.*.attention.rel_attn_embed',
    'self_attn.grep_a': 'encoder.layers.*.attention.gru_rel_pos_const',
    'self_attn_layer_norm': 'encoder.layers.*.layer_norm',
    'fc1': 'encoder.layers.*.feed_forward.intermediate_dense',
    'fc2': 'encoder.layers.*.feed_forward.output_dense',
    'final_layer_norm': 'encoder.layers.*.final_layer_norm',
    'encoder.layer_norm': 'encoder.layer_norm',
    'w2v_model.layer_norm': 'feature_projection.layer_norm',
    'quantizer.weight_proj': 'quantizer.weight_proj',
    'quantizer.vars': 'quantizer.codevectors',
    'project_q': 'project_q',
    'final_proj': 'project_hid',
    'w2v_encoder.proj': 'ctc_proj',
    'mask_emb': 'masked_spec_embed',
}
__UpperCAmelCase												=[
    'ctc_proj',
    'quantizer.weight_proj',
    'quantizer.codevectors',
    'project_q',
    'project_hid',
]






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    )     ->   List[str]:
    for attribute in key.split('''.'''    ):
        __lowerCamelCase          =  getattr(snake_case_    ,  snake_case_    )

    if weight_type is not None:
        __lowerCamelCase          =  getattr(snake_case_    ,  snake_case_    ).shape
    else:
        __lowerCamelCase          =  hf_pointer.shape

    assert hf_shape == value.shape, (
        f"""Shape of hf {key + '.' + weight_type if weight_type is not None else ''} is {hf_shape}, but should be"""
        f""" {value.shape} for {full_name}"""
    )

    if weight_type == "weight":
        __lowerCamelCase          =  value
    elif weight_type == "weight_g":
        __lowerCamelCase          =  value
    elif weight_type == "weight_v":
        __lowerCamelCase          =  value
    elif weight_type == "bias":
        __lowerCamelCase          =  value
    else:
        __lowerCamelCase          =  value

    logger.info(f"""{key + '.' + weight_type if weight_type is not None else ''} was initialized from {full_name}."""    )






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    )     ->   Tuple:
    __lowerCamelCase          =  []
    __lowerCamelCase          =  fairseq_model.state_dict()

    __lowerCamelCase          =  hf_model.feature_extractor

    for name, value in fairseq_dict.items():
        __lowerCamelCase          =  False
        if "conv_layers" in name:
            load_conv_layer(
                snake_case_    ,  snake_case_    ,  snake_case_    ,  snake_case_    ,  hf_model.config.feat_extract_norm == '''group'''    ,  )
            __lowerCamelCase          =  True
        else:
            for key, mapped_key in MAPPING.items():
                if key in name or key.split('''w2v_model.'''    )[-1] == name.split('''.'''    )[0]:
                    __lowerCamelCase          =  True
                    if "*" in mapped_key:
                        __lowerCamelCase          =  name.split(snake_case_    )[0].split('''.'''    )[-2]
                        __lowerCamelCase          =  mapped_key.replace('''*'''    ,  snake_case_    )
                    if "weight_g" in name:
                        __lowerCamelCase          =  '''weight_g'''
                    elif "weight_v" in name:
                        __lowerCamelCase          =  '''weight_v'''
                    elif "bias" in name and "relative_attention_bias" not in name:
                        __lowerCamelCase          =  '''bias'''
                    elif "weight" in name:
                        # TODO: don't match quantizer.weight_proj
                        __lowerCamelCase          =  '''weight'''
                    else:
                        __lowerCamelCase          =  None

                    set_recursively(snake_case_    ,  snake_case_    ,  snake_case_    ,  snake_case_    ,  snake_case_    )
                continue
        if not is_used:
            unused_weights.append(snake_case_    )

    logger.warning(f"""Unused weights: {unused_weights}"""    )






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    )     ->   int:
    __lowerCamelCase          =  full_name.split('''conv_layers.'''    )[-1]
    __lowerCamelCase          =  name.split('''.'''    )
    __lowerCamelCase          =  int(items[0]    )
    __lowerCamelCase          =  int(items[1]    )

    if type_id == 0:
        if "bias" in name:
            assert value.shape == feature_extractor.conv_layers[layer_id].conv.bias.data.shape, (
                f"""{full_name} has size {value.shape}, but"""
                f""" {feature_extractor.conv_layers[layer_id].conv.bias.data.shape} was found."""
            )
            __lowerCamelCase          =  value
            logger.info(f"""Feat extract conv layer {layer_id} was initialized from {full_name}."""    )
        elif "weight" in name:
            assert value.shape == feature_extractor.conv_layers[layer_id].conv.weight.data.shape, (
                f"""{full_name} has size {value.shape}, but"""
                f""" {feature_extractor.conv_layers[layer_id].conv.weight.data.shape} was found."""
            )
            __lowerCamelCase          =  value
            logger.info(f"""Feat extract conv layer {layer_id} was initialized from {full_name}."""    )
    elif (type_id == 2 and not use_group_norm) or (type_id == 2 and layer_id == 0 and use_group_norm):
        if "bias" in name:
            assert value.shape == feature_extractor.conv_layers[layer_id].layer_norm.bias.data.shape, (
                f"""{full_name} has size {value.shape}, but {feature_extractor[layer_id].layer_norm.bias.data.shape} was"""
                " found."
            )
            __lowerCamelCase          =  value
            logger.info(f"""Feat extract layer norm weight of layer {layer_id} was initialized from {full_name}."""    )
        elif "weight" in name:
            assert value.shape == feature_extractor.conv_layers[layer_id].layer_norm.weight.data.shape, (
                f"""{full_name} has size {value.shape}, but"""
                f""" {feature_extractor[layer_id].layer_norm.weight.data.shape} was found."""
            )
            __lowerCamelCase          =  value
            logger.info(f"""Feat extract layer norm weight of layer {layer_id} was initialized from {full_name}."""    )
    else:
        unused_weights.append(snake_case_    )






@torch.no_grad()
def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__=None    )     ->   List[Any]:
    # load the pre-trained checkpoints
    __lowerCamelCase          =  torch.load(snake_case_    )
    __lowerCamelCase          =  WavLMConfigOrig(checkpoint['''cfg''']    )
    __lowerCamelCase          =  WavLMOrig(snake_case_    )
    model.load_state_dict(checkpoint['''model''']    )
    model.eval()

    if config_path is not None:
        __lowerCamelCase          =  WavLMConfig.from_pretrained(snake_case_    )
    else:
        __lowerCamelCase          =  WavLMConfig()

    __lowerCamelCase          =  WavLMModel(snake_case_    )

    recursively_load_weights(snake_case_    ,  snake_case_    )

    hf_wavlm.save_pretrained(snake_case_    )


if __name__ == "__main__":
  __UpperCAmelCase												=argparse.ArgumentParser()
  parser.add_argument("--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model.")
  parser.add_argument("--checkpoint_path", default=None, type=str, help="Path to fairseq checkpoint")
  parser.add_argument("--config_path", default=None, type=str, help="Path to hf config.json of model to convert")
  __UpperCAmelCase												=parser.parse_args()
  convert_wavlm_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path)

'''simple docstring'''




import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__UpperCAmelCase												=get_tests_dir("fixtures/spiece.model")




@require_sentencepiece
@require_tokenizers
class    a__				(       UpperCAmelCase__							,       unittest.TestCase			):
     lowerCamelCase  :					Optional[Any]							=DebertaVaTokenizer
     lowerCamelCase  :					Optional[int]							=DebertaVaTokenizerFast
     lowerCamelCase  :					Optional[Any]							=True
     lowerCamelCase  :					Tuple							=True






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         super().setUp()

         # We have a SentencePiece fixture for testing
         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    unk_token='''<unk>'''   )
         tokenizer.save_pretrained(self.tmpdirname   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]  ,    a		:		Dict   ):





         """simple docstring"""



         __lowerCamelCase          =  '''this is a test'''
         __lowerCamelCase          =  '''this is a test'''
         return input_text, output_text






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[str]   ):





         """simple docstring"""



         __lowerCamelCase          =  '''<pad>'''
         __lowerCamelCase          =  0

         self.assertEqual(self.get_tokenizer()._convert_token_to_id(a   )  ,    a   )
         self.assertEqual(self.get_tokenizer()._convert_id_to_token(a   )  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  list(self.get_tokenizer().get_vocab().keys()   )
         self.assertEqual(vocab_keys[0]  ,    '''<pad>'''   )
         self.assertEqual(vocab_keys[1]  ,    '''<unk>'''   )
         self.assertEqual(vocab_keys[-1]  ,    '''[PAD]'''   )
         self.assertEqual(len(a   )  ,    3_00_01   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		int   ):





         """simple docstring"""



         self.assertEqual(self.get_tokenizer().vocab_size  ,    3_00_00   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  ''' \tHeLLo!how  \n Are yoU?  '''
         __lowerCamelCase          =  ['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
         # fmt: on

         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    do_lower_case=a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  DebertaVaTokenizerFast(a  ,    do_lower_case=a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )






     @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''   )
     def        SCREAMING_SNAKE_CASE__       (			self		:		Dict   ):





         """simple docstring"""



         pass






     @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''   )
     def        SCREAMING_SNAKE_CASE__       (			self		:		List[Any]   ):





         """simple docstring"""



         pass






     def        SCREAMING_SNAKE_CASE__       (			self		:		Union[str, Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  '''I was born in 92000, and this is falsé.'''
         __lowerCamelCase          =  ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
         # fmt: on

         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    split_by_punct=a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  DebertaVaTokenizerFast(a  ,    split_by_punct=a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Any   ):





         """simple docstring"""



         __lowerCamelCase          =  '''I was born in 92000, and this is falsé.'''
         __lowerCamelCase          =  ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
         # fmt: on

         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(tokenizer.encode(a  ,    add_special_tokens=a   )   )
         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  DebertaVaTokenizerFast(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a  ,    add_special_tokens=a   )   )
         self.assertListEqual(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		str   ):





         """simple docstring"""



         __lowerCamelCase          =  '''I was born in 92000, and this is falsé.'''
         __lowerCamelCase          =  ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
         # fmt: on

         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  DebertaVaTokenizerFast(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  '''I was born in 92000, and this is falsé.'''
         __lowerCamelCase          =  ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
         # fmt: on

         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  DebertaVaTokenizerFast(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  ''' \tHeLLo!how  \n Are yoU?  '''
         __lowerCamelCase          =  ['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
         # fmt: on

         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  DebertaVaTokenizerFast(a  ,    do_lower_case=a  ,    split_by_punct=a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a  ,    add_special_tokens=a   )   )

         self.assertListEqual(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  self.get_tokenizer()
         __lowerCamelCase          =  self.get_rust_tokenizer()

         __lowerCamelCase          =  '''I was born in 92000, and this is falsé.'''

         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(tokenizer.encode(a  ,    add_special_tokens=a   )   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(a  ,    add_special_tokens=a   )   )
         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  tokenizer.encode(a  ,    add_special_tokens=a   )
         __lowerCamelCase          =  rust_tokenizer.encode(a  ,    add_special_tokens=a   )
         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  self.get_rust_tokenizer()
         __lowerCamelCase          =  tokenizer.encode(a   )
         __lowerCamelCase          =  rust_tokenizer.encode(a   )
         self.assertListEqual(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[Any]   ):





         """simple docstring"""



         __lowerCamelCase          =  '''This is a test'''
         __lowerCamelCase          =  [13, 1, 43_98, 25, 21, 12_89]
         __lowerCamelCase          =  ['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
         __lowerCamelCase          =  ['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

         __lowerCamelCase          =  DebertaVaTokenizer(a  ,    keep_accents=a   )
         __lowerCamelCase          =  DebertaVaTokenizerFast(a  ,    keep_accents=a   )

         __lowerCamelCase          =  tokenizer.encode(a  ,    add_special_tokens=a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  tokenizer.tokenize(a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(a   )
         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  rust_tokenizer.encode(a  ,    add_special_tokens=a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  rust_tokenizer.tokenize(a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(a   )
         self.assertListEqual(a  ,    a   )

         # fmt: off
         __lowerCamelCase          =  '''I was born in 92000, and this is falsé.'''
         __lowerCamelCase          =  [13, 1, 23, 3_86, 19, 5_61, 30_50, 15, 17, 48, 25, 82_56, 18, 1, 9]
         __lowerCamelCase          =  ['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
         __lowerCamelCase          =  ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
         # fmt: on

         __lowerCamelCase          =  tokenizer.encode(a  ,    add_special_tokens=a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  tokenizer.tokenize(a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  tokenizer.convert_ids_to_tokens(a   )
         self.assertListEqual(a  ,    a   )

         __lowerCamelCase          =  rust_tokenizer.encode(a  ,    add_special_tokens=a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  rust_tokenizer.tokenize(a   )
         self.assertListEqual(a  ,    a   )
         __lowerCamelCase          =  rust_tokenizer.convert_ids_to_tokens(a   )
         self.assertListEqual(a  ,    a   )






     def        SCREAMING_SNAKE_CASE__       (			self		:		str   ):





         """simple docstring"""



         __lowerCamelCase          =  DebertaVaTokenizer(a   )

         __lowerCamelCase          =  tokenizer.encode('''sequence builders'''   )
         __lowerCamelCase          =  tokenizer.encode('''multi-sequence build'''   )

         __lowerCamelCase          =  tokenizer.build_inputs_with_special_tokens(a   )
         __lowerCamelCase          =  tokenizer.build_inputs_with_special_tokens(a  ,    a   )

         self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]  ,    a   )
         self.assertEqual(
             [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]  ,    a  ,    )






     @slow
     def        SCREAMING_SNAKE_CASE__       (			self		:		Optional[int]   ):





         """simple docstring"""



         __lowerCamelCase          =  {'''input_ids''': [[1, 3_98_67, 36, 1_93_90, 4_86, 27, 3_50_52, 8_14_36, 18, 6_06_85, 12_25, 7, 3_50_52, 8_14_36, 18, 93_67, 1_68_99, 18, 1_59_37, 53, 5_94, 7_73, 18, 1_62_87, 3_04_65, 36, 1_59_37, 6, 4_11_39, 38, 3_69_79, 6_07_63, 1_91, 6, 3_41_32, 99, 6, 5_05_38, 3_90, 4_32_30, 6, 3_41_32, 27_79, 2_08_50, 14, 6_99, 10_72, 11_94, 36, 3_82, 1_09_01, 53, 7, 6_99, 10_72, 20_84, 36, 2_04_22, 6_30, 53, 19, 1_05, 30_49, 18_96, 10_53, 1_68_99, 15_06, 11, 3_79_78, 42_43, 7, 12_37, 3_18_69, 2_00, 1_65_66, 6_54, 6, 3_50_52, 8_14_36, 7, 5_56_30, 1_35_93, 4, 2], [1, 26, 1_50_11, 13, 6_67, 8, 10_53, 18, 2_36_11, 12_37, 7_23_56, 1_28_20, 34, 10_41_34, 12_09, 35, 1_33_13, 66_27, 21, 2_02, 3_47, 7, 1_64, 23_99, 11, 46, 44_85, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 12_32, 28_64, 1_57_85, 1_49_51, 1_05, 5, 85_81, 12_50, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
         # fmt: on

         self.tokenizer_integration_test_util(
             expected_encoding=a  ,    model_name='''microsoft/deberta-v2-xlarge'''  ,    revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''  ,    )
