


'''simple docstring'''

import torch

from transformers import AutoTokenizer
class 						__lowerCAmelCase		(lowercase_  ):





      '''simple docstring'''






      def __init__(self					:					int     ,		UpperCamelCase					:					Dict				):

             '''simple docstring'''







             lowercase__       =				AutoTokenizer.from_pretrained(UpperCamelCase				)



      def    UpperCamelCase__	(self					:					str     ,		UpperCamelCase					:					int				):

             '''simple docstring'''







             if isinstance(UpperCamelCase     ,		UpperCamelCase				) and all(isinstance(_x     ,		UpperCamelCase				) for _x in x				):
                    lowercase__       =				None
                    for l in x:
                           lowercase__       =				self.tokenizer(
                               UpperCamelCase     ,		padding='''max_length'''     ,		max_length=384     ,		truncation=UpperCamelCase     ,		return_tensors='''pt'''     ,		)
                           lowercase__       =				torch.tensor([len(UpperCamelCase				)]				)
                           if d is not None:
                                  for k in d.keys():
                                         lowercase__       =				torch.cat((d[k], t[k])     ,		0				)
                           else:
                                  lowercase__       =				t

                    lowercase__       =				torch.tensor(self.tokenizer.convert_tokens_to_ids('''[E]'''				)				)
                    lowercase__       =				torch.tensor(self.tokenizer.convert_tokens_to_ids('''[/E]'''				)				)

             elif isinstance(UpperCamelCase     ,		UpperCamelCase				) and all(isinstance(_x     ,		UpperCamelCase				) for _x in x				):
                    lowercase__       =				self.tokenizer(
                        UpperCamelCase     ,		padding='''max_length'''     ,		max_length=384     ,		truncation=UpperCamelCase     ,		return_tensors='''pt'''     ,		)

             else:
                    raise Exception(
                        '''Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of'''
                        ''' strings` for supports are supported.'''				)

             return d






      def    UpperCamelCase__	(self					:					Tuple     ,		UpperCamelCase					:					List[Any]     ,		UpperCamelCase					:					str     ,		UpperCamelCase					:					str     ,		UpperCamelCase					:					Dict     ,		UpperCamelCase					:					Optional[Any]=0.70				):

             '''simple docstring'''







             lowercase__       =				[]
             for idx in range(len(W_query['''input_ids''']				)				):
                    lowercase__       =				lowercase__       =				range(p_start.shape[1]				)

                    lowercase__       =				[]
                    for start_id in start_indexes:
                           for end_id in end_indexes:
                                  if start_id < end_id:
                                         output.append(
                                             (
                                                 start_id,
                                                 end_id,
                                                 p_start[idx][start_id].item(),
                                                 p_end[idx][end_id].item(),
                                             )				)

                    output.sort(key=lambda UpperCamelCase				: (tup[2] * tup[3])     ,		reverse=UpperCamelCase				)
                    lowercase__       =				[]
                    for k in range(len(UpperCamelCase				)				):
                           if output[k][2] * output[k][3] >= thresh:
                                  lowercase__    ,lowercase__       =				output[k][0], output[k][1]
                                  lowercase__       =				self.tokenizer.decode(W_query['''input_ids'''][idx][c_start_pos:c_end_pos]				)
                                  temp.append((decoded, output[k][2] * output[k][3])				)

                    final_outputs.append(UpperCamelCase				)

             return final_outputs








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


lowerCamelCase							:     Optional[Any]								=			{
    'configuration_mobilevitv2': [
        'MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileViTV2Config',
        'MobileViTV2OnnxConfig',
    ],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase							:     Optional[int]								=			[
     'MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST',
     'MobileViTV2ForImageClassification',
     'MobileViTV2ForSemanticSegmentation',
     'MobileViTV2Model',
     'MobileViTV2PreTrainedModel',
 ]

if TYPE_CHECKING:
 from .configuration_mobilevitva import (
     MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
     MobileViTVaConfig,
     MobileViTVaOnnxConfig,
 )

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_mobilevitva import (
      MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
      MobileViTVaForImageClassification,
      MobileViTVaForSemanticSegmentation,
      MobileViTVaModel,
      MobileViTVaPreTrainedModel,
  )

else:
 import sys

 lowerCamelCase							:     Dict								=			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




