


"""simple docstring"""






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


SCREAMING_SNAKE_CASE__				:  int						= logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__				:  Optional[Any]						= {
    "apple/mobilevit-small": "https://huggingface.co/apple/mobilevit-small/resolve/main/config.json",
    "apple/mobilevit-x-small": "https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json",
    "apple/mobilevit-xx-small": "https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json",
    "apple/deeplabv3-mobilevit-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json"
    ),
    "apple/deeplabv3-mobilevit-x-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json"
    ),
    "apple/deeplabv3-mobilevit-xx-small": (
        "https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json"
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}


class 	A_       (     snake_case__   ):





  """simple docstring"""

  lowercase		:	Dict   =						'mobilevit'
  def __init__(						self  ,					__UpperCAmelCase=3  ,					__UpperCAmelCase=2_56  ,					__UpperCAmelCase=2  ,					__UpperCAmelCase=[1_44, 1_92, 2_40]  ,					__UpperCAmelCase=[16, 32, 64, 96, 1_28, 1_60, 6_40]  ,					__UpperCAmelCase=4  ,					__UpperCAmelCase=2.0  ,					__UpperCAmelCase=4.0  ,					__UpperCAmelCase="silu"  ,					__UpperCAmelCase=3  ,					__UpperCAmelCase=32  ,					__UpperCAmelCase=0.1  ,					__UpperCAmelCase=0.0  ,					__UpperCAmelCase=0.1  ,					__UpperCAmelCase=0.02  ,					__UpperCAmelCase=1E-5  ,					__UpperCAmelCase=True  ,					__UpperCAmelCase=2_56  ,					__UpperCAmelCase=[6, 12, 18]  ,					__UpperCAmelCase=0.1  ,					__UpperCAmelCase=2_55  ,					**__UpperCAmelCase  ,					)				->					Dict:
     super().__init__(**lowerCAmelCase_						)

     a   :	Dict						=    num_channels
     a   :	Optional[int]						=    image_size
     a   :	int						=    patch_size
     a   :	int						=    hidden_sizes
     a   :	Union[str, Any]						=    neck_hidden_sizes
     a   :	Union[str, Any]						=    num_attention_heads
     a   :	Any						=    mlp_ratio
     a   :	Union[str, Any]						=    expand_ratio
     a   :	List[Any]						=    hidden_act
     a   :	Any						=    conv_kernel_size
     a   :	Optional[Any]						=    output_stride
     a   :	Tuple						=    hidden_dropout_prob
     a   :	Any						=    attention_probs_dropout_prob
     a   :	Any						=    classifier_dropout_prob
     a   :	Optional[int]						=    initializer_range
     a   :	Optional[int]						=    layer_norm_eps
     a   :	Optional[Any]						=    qkv_bias

     # decode head attributes for semantic segmentation
     a   :	int						=    aspp_out_channels
     a   :	List[Any]						=    atrous_rates
     a   :	int						=    aspp_dropout_prob
     a   :	str						=    semantic_loss_ignore_index



class 	A_       (     snake_case__   ):





  """simple docstring"""

  lowercase		:	str   =						version.parse("1.11"   )
  @property
  def 							lowercase_     (						self						)				->					Mapping[str, Mapping[int, str]]:
     return OrderedDict([('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'})]						)
  @property
  def 							lowercase_     (						self						)				->					Mapping[str, Mapping[int, str]]:
     if self.task == "image-classification":
        return OrderedDict([('logits', {0: 'batch'})]						)
     else:
        return OrderedDict([('last_hidden_state', {0: 'batch'}), ('pooler_output', {0: 'batch'})]						)






  @property
  def 							lowercase_     (						self						)				->					float:
     return 1E-4






import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase






@require_tokenizers
class 				_SCREAMING_SNAKE_CASE( unittest.TestCase						):
   UpperCamelCase_					:    int			      = EsmTokenizer
   def _lowercase(     self     )						->Dict:
        super().setUp()
        a	:     Tuple						      =    tempfile.mkdtemp()
        # fmt: off
        a	:     List[str]						      =    ["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
        # fmt: on
        a	:     Tuple						      =    os.path.join(self.tmpdirname				,  VOCAB_FILES_NAMES['''vocab_file''']     )
        with open(self.vocab_file				,  '''w'''				,  encoding='''utf-8'''     ) as vocab_writer:
             vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]     )     )
   def _lowercase(     self				,  **lowerCAmelCase_     )						->List[PreTrainedTokenizerBase]:
        return [self.get_tokenizer(**lowerCAmelCase_     )]
   def _lowercase(     self				,  **lowerCAmelCase_     )						->PreTrainedTokenizer:
        return self.tokenizer_class.from_pretrained(self.tmpdirname				,  **lowerCAmelCase_     )
   def _lowercase(     self     )						->List[Any]:
        a	:     Optional[int]						      =    self.tokenizer_class(self.vocab_file     )

        a	:     List[Any]						      =    tokenizer.tokenize('''LAGVS'''     )
        self.assertListEqual(lowerCAmelCase_				,  ['''L''', '''A''', '''G''', '''V''', '''S''']     )
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase_     )				,  [4, 5, 6, 7, 8]     )
   def _lowercase(     self     )						->Optional[Any]:
        a	:     Optional[int]						      =    self.tokenizer_class(self.vocab_file     )

        a	:     Optional[Any]						      =    '''LAGVS'''
        self.assertListEqual(tokenizer.encode(lowerCAmelCase_     )				,  [0, 4, 5, 6, 7, 8, 2]     )
   def _lowercase(     self     )						->List[Any]:
        a	:     Any						      =    self.tokenizer_class(self.vocab_file     )

        a	:     Optional[int]						      =    ['''LAGVS''', '''WCB''']
        a	:     Optional[Any]						      =    tokenizer(lowerCAmelCase_				,  padding=lowerCAmelCase_     )['''input_ids''']

        self.assertListEqual(lowerCAmelCase_				,  [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2]]     )
   def _lowercase(     self     )						->List[Any]:
        a	:     Optional[Any]						      =    self.tokenizer_class(self.vocab_file     )

        a	:     str						      =    ['''LAGVS''', '''WCB''']
        a	:     Dict						      =    tokenizer(lowerCAmelCase_				,  padding=lowerCAmelCase_     )['''input_ids''']

        self.assertListEqual(lowerCAmelCase_				,  [[0, 4, 5, 6, 7, 8, 2], [0, 22, 23, 25, 2, 1, 1]]     )


   def _lowercase(     self     )						->List[str]:
        a	:     int						      =    self.get_tokenizers(fast=lowerCAmelCase_     )
        for tokenizer in tokenizers:
             with self.subTest(F"""{tokenizer.__class__.__name__}"""     ):
                  a	:     Union[str, Any]						      =    '''<unk>'''
                  a	:     List[Any]						      =    '''<mask>'''

                  a	:     List[Any]						      =    tokenizer.tokenize(lowerCAmelCase_     )
                  a	:     Tuple						      =    tokenizer.tokenize(lowerCAmelCase_     )

                  self.assertEqual(len(lowerCAmelCase_     )				,  1     )
                  self.assertEqual(len(lowerCAmelCase_     )				,  1     )
                  self.assertEqual(token_a[0]				,  lowerCAmelCase_     )
                  self.assertEqual(token_a[0]				,  lowerCAmelCase_     )