


'''simple docstring'''




import argparse
import json
from pathlib import Path

import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image

from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging


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






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__=False    )     ->   str:
    __lowerCamelCase          =  []
    for i in range(config.num_hidden_layers    ):
        # encoder layers: output projection, 2 feedforward neural networks and 2 layernorms
        rename_keys.append((f"""blocks.{i}.norm1.weight""", f"""deit.encoder.layer.{i}.layernorm_before.weight""")    )
        rename_keys.append((f"""blocks.{i}.norm1.bias""", f"""deit.encoder.layer.{i}.layernorm_before.bias""")    )
        rename_keys.append((f"""blocks.{i}.attn.proj.weight""", f"""deit.encoder.layer.{i}.attention.output.dense.weight""")    )
        rename_keys.append((f"""blocks.{i}.attn.proj.bias""", f"""deit.encoder.layer.{i}.attention.output.dense.bias""")    )
        rename_keys.append((f"""blocks.{i}.norm2.weight""", f"""deit.encoder.layer.{i}.layernorm_after.weight""")    )
        rename_keys.append((f"""blocks.{i}.norm2.bias""", f"""deit.encoder.layer.{i}.layernorm_after.bias""")    )
        rename_keys.append((f"""blocks.{i}.mlp.fc1.weight""", f"""deit.encoder.layer.{i}.intermediate.dense.weight""")    )
        rename_keys.append((f"""blocks.{i}.mlp.fc1.bias""", f"""deit.encoder.layer.{i}.intermediate.dense.bias""")    )
        rename_keys.append((f"""blocks.{i}.mlp.fc2.weight""", f"""deit.encoder.layer.{i}.output.dense.weight""")    )
        rename_keys.append((f"""blocks.{i}.mlp.fc2.bias""", f"""deit.encoder.layer.{i}.output.dense.bias""")    )

    # projection layer + position embeddings
    rename_keys.extend(
        [
            ('''cls_token''', '''deit.embeddings.cls_token'''),
            ('''dist_token''', '''deit.embeddings.distillation_token'''),
            ('''patch_embed.proj.weight''', '''deit.embeddings.patch_embeddings.projection.weight'''),
            ('''patch_embed.proj.bias''', '''deit.embeddings.patch_embeddings.projection.bias'''),
            ('''pos_embed''', '''deit.embeddings.position_embeddings'''),
        ]    )

    if base_model:
        # layernorm + pooler
        rename_keys.extend(
            [
                ('''norm.weight''', '''layernorm.weight'''),
                ('''norm.bias''', '''layernorm.bias'''),
                ('''pre_logits.fc.weight''', '''pooler.dense.weight'''),
                ('''pre_logits.fc.bias''', '''pooler.dense.bias'''),
            ]    )

        # if just the base model, we should remove "deit" from all keys that start with "deit"
        __lowerCamelCase          =  [(pair[0], pair[1][4:]) if pair[1].startswith('''deit'''    ) else pair for pair in rename_keys]
    else:
        # layernorm + classification heads
        rename_keys.extend(
            [
                ('''norm.weight''', '''deit.layernorm.weight'''),
                ('''norm.bias''', '''deit.layernorm.bias'''),
                ('''head.weight''', '''cls_classifier.weight'''),
                ('''head.bias''', '''cls_classifier.bias'''),
                ('''head_dist.weight''', '''distillation_classifier.weight'''),
                ('''head_dist.bias''', '''distillation_classifier.bias'''),
            ]    )

    return rename_keys






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__=False    )     ->   Union[str, Any]:
    for i in range(config.num_hidden_layers    ):
        if base_model:
            __lowerCamelCase          =  ''''''
        else:
            __lowerCamelCase          =  '''deit.'''
        # read in weights + bias of input projection layer (in timm, this is a single matrix + bias)
        __lowerCamelCase          =  state_dict.pop(f"""blocks.{i}.attn.qkv.weight"""    )
        __lowerCamelCase          =  state_dict.pop(f"""blocks.{i}.attn.qkv.bias"""    )
        # next, add query, keys and values (in that order) to the state dict
        __lowerCamelCase          =  in_proj_weight[
            : config.hidden_size, :
        ]
        __lowerCamelCase          =  in_proj_bias[: config.hidden_size]
        __lowerCamelCase          =  in_proj_weight[
            config.hidden_size : config.hidden_size * 2, :
        ]
        __lowerCamelCase          =  in_proj_bias[
            config.hidden_size : config.hidden_size * 2
        ]
        __lowerCamelCase          =  in_proj_weight[
            -config.hidden_size :, :
        ]
        __lowerCamelCase          =  in_proj_bias[-config.hidden_size :]






def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    )     ->   List[str]:
    __lowerCamelCase          =  dct.pop(UpperCamelCase__    )
    __lowerCamelCase          =  val






def __lowerCAmelCase			(							)     ->   Dict:
    __lowerCamelCase          =  '''http://images.cocodataset.org/val2017/000000039769.jpg'''
    __lowerCamelCase          =  Image.open(requests.get(UpperCamelCase__    ,  stream=UpperCamelCase__    ).raw    )
    return im






@torch.no_grad()
def __lowerCAmelCase			(							UpperCamelCase__    ,  UpperCamelCase__    )     ->   Optional[Any]:
    __lowerCamelCase          =  DeiTConfig()
    # all deit models have fine-tuned heads
    __lowerCamelCase          =  False
    # dataset (fine-tuned on ImageNet 2012), patch_size and image_size
    __lowerCamelCase          =  10_00
    __lowerCamelCase          =  '''huggingface/label-files'''
    __lowerCamelCase          =  '''imagenet-1k-id2label.json'''
    __lowerCamelCase          =  json.load(open(hf_hub_download(UpperCamelCase__    ,  UpperCamelCase__    ,  repo_type='''dataset'''    )    ,  '''r'''    )    )
    __lowerCamelCase          =  {int(UpperCamelCase__    ): v for k, v in idalabel.items()}
    __lowerCamelCase          =  idalabel
    __lowerCamelCase          =  {v: k for k, v in idalabel.items()}
    __lowerCamelCase          =  int(deit_name[-6:-4]    )
    __lowerCamelCase          =  int(deit_name[-3:]    )
    # size of the architecture
    if deit_name[9:].startswith('''tiny'''    ):
        __lowerCamelCase          =  1_92
        __lowerCamelCase          =  7_68
        __lowerCamelCase          =  12
        __lowerCamelCase          =  3
    elif deit_name[9:].startswith('''small'''    ):
        __lowerCamelCase          =  3_84
        __lowerCamelCase          =  15_36
        __lowerCamelCase          =  12
        __lowerCamelCase          =  6
    if deit_name[9:].startswith('''base'''    ):
        pass
    elif deit_name[4:].startswith('''large'''    ):
        __lowerCamelCase          =  10_24
        __lowerCamelCase          =  40_96
        __lowerCamelCase          =  24
        __lowerCamelCase          =  16

    # load original model from timm
    __lowerCamelCase          =  timm.create_model(UpperCamelCase__    ,  pretrained=UpperCamelCase__    )
    timm_model.eval()

    # load state_dict of original model, remove and rename some keys
    __lowerCamelCase          =  timm_model.state_dict()
    __lowerCamelCase          =  create_rename_keys(UpperCamelCase__    ,  UpperCamelCase__    )
    for src, dest in rename_keys:
        rename_key(UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    )
    read_in_q_k_v(UpperCamelCase__    ,  UpperCamelCase__    ,  UpperCamelCase__    )

    # load HuggingFace model
    __lowerCamelCase          =  DeiTForImageClassificationWithTeacher(UpperCamelCase__    ).eval()
    model.load_state_dict(UpperCamelCase__    )

    # Check outputs on an image, prepared by DeiTImageProcessor
    __lowerCamelCase          =  int(
        (2_56 / 2_24) * config.image_size    )  # to maintain same ratio w.r.t. 224 images, see https://github.com/facebookresearch/deit/blob/ab5715372db8c6cad5740714b2216d55aeae052e/datasets.py#L103
    __lowerCamelCase          =  DeiTImageProcessor(size=UpperCamelCase__    ,  crop_size=config.image_size    )
    __lowerCamelCase          =  image_processor(images=prepare_img()    ,  return_tensors='''pt'''    )
    __lowerCamelCase          =  encoding['''pixel_values''']
    __lowerCamelCase          =  model(UpperCamelCase__    )

    __lowerCamelCase          =  timm_model(UpperCamelCase__    )
    assert timm_logits.shape == outputs.logits.shape
    assert torch.allclose(UpperCamelCase__    ,  outputs.logits    ,  atol=1E-3    )

    Path(UpperCamelCase__    ).mkdir(exist_ok=UpperCamelCase__    )
    print(f"""Saving model {deit_name} to {pytorch_dump_folder_path}"""    )
    model.save_pretrained(UpperCamelCase__    )
    print(f"""Saving image processor to {pytorch_dump_folder_path}"""    )
    image_processor.save_pretrained(UpperCamelCase__    )


if __name__ == "__main__":
  __UpperCAmelCase												=argparse.ArgumentParser()
  # Required parameters
  parser.add_argument(
      "--deit_name",
      default="vit_deit_base_distilled_patch16_224",
      type=str,
      help="Name of the DeiT timm model you'd like to convert.",
  )
  parser.add_argument(
      "--pytorch_dump_folder_path", default=None, type=str, help="Path to the output PyTorch model directory."
  )

  __UpperCAmelCase												=parser.parse_args()
  convert_deit_checkpoint(args.deit_name, args.pytorch_dump_folder_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'''  ,    )
