


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


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






@require_sentencepiece
@require_tokenizers
class 						_A  (  _a   ,unittest.TestCase  ):







    """simple docstring"""




    UpperCAmelCase	:							int     =	DebertaVaTokenizer
    UpperCAmelCase	:							str     =	DebertaVaTokenizerFast
    UpperCAmelCase	:							str     =	True
    UpperCAmelCase	:							Tuple     =	True






    def      __snake_case							( self    :   Tuple):
      super().setUp()

      # We have a SentencePiece fixture for testing
      a						:		Dict											=      DebertaVaTokenizer(__UpperCAmelCase    ,			unk_token="<unk>")
      tokenizer.save_pretrained(self.tmpdirname)






    def      __snake_case							( self    :   Optional[Any]    ,			__UpperCAmelCase    :   str):
      a						:		Union[str, Any]											=      "this is a test"
      a						:		List[Any]											=      "this is a test"
      return input_text, output_text






    def      __snake_case							( self    :   List[str]):
      a						:		str											=      "<pad>"
      a						:		Tuple											=      0

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






    def      __snake_case							( self    :   Optional[int]):
      a						:		List[str]											=      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(__UpperCAmelCase)    ,			30001)






    def      __snake_case							( self    :   Dict):
      self.assertEqual(self.get_tokenizer().vocab_size    ,			30000)






    def      __snake_case							( self    :   Optional[Any]):
      # fmt: off
      a						:		Optional[Any]											=      " \tHeLLo!how  \n Are yoU?  "
      a						:		Dict											=      ["▁hello", "!", "how", "▁are", "▁you", "?"]
      # fmt: on

      a						:		List[Any]											=      DebertaVaTokenizer(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase)
      a						:		Optional[int]											=      tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		Union[str, Any]											=      DebertaVaTokenizerFast(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase)
      a						:		Tuple											=      rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    @unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.")
    def      __snake_case							( self    :   Any):
      pass






    @unittest.skip("There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.")
    def      __snake_case							( self    :   Union[str, Any]):
      pass






    def      __snake_case							( self    :   Optional[int]):
      # fmt: off
      a						:		int											=      "I was born in 92000, and this is falsé."
      a						:		List[str]											=      ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
      # fmt: on

      a						:		int											=      DebertaVaTokenizer(__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		int											=      tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		Dict											=      DebertaVaTokenizerFast(__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		Optional[int]											=      rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    def      __snake_case							( self    :   int):
      # fmt: off
      a						:		Dict											=      "I was born in 92000, and this is falsé."
      a						:		List[str]											=      ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
      # fmt: on

      a						:		Union[str, Any]											=      DebertaVaTokenizer(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		List[str]											=      tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		Tuple											=      DebertaVaTokenizerFast(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		Union[str, Any]											=      rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    def      __snake_case							( self    :   Union[str, Any]):
      # fmt: off
      a						:		Optional[Any]											=      "I was born in 92000, and this is falsé."
      a						:		Optional[int]											=      ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
      # fmt: on

      a						:		Tuple											=      DebertaVaTokenizer(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		Any											=      tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		str											=      DebertaVaTokenizerFast(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		Optional[Any]											=      rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    def      __snake_case							( self    :   Union[str, Any]):
      # fmt: off
      a						:		str											=      "I was born in 92000, and this is falsé."
      a						:		Optional[int]											=      ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", "▁", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "▁", ".", ]
      # fmt: on

      a						:		List[Any]											=      DebertaVaTokenizer(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		str											=      tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		str											=      DebertaVaTokenizerFast(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		List[Any]											=      rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    def      __snake_case							( self    :   Optional[int]):
      # fmt: off
      a						:		Union[str, Any]											=      " \tHeLLo!how  \n Are yoU?  "
      a						:		Tuple											=      ["▁", "<unk>", "e", "<unk>", "o", "!", "how", "▁", "<unk>", "re", "▁yo", "<unk>", "?"]
      # fmt: on

      a						:		List[Any]											=      DebertaVaTokenizer(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		Optional[int]											=      tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		Optional[int]											=      DebertaVaTokenizerFast(__UpperCAmelCase    ,			do_lower_case=__UpperCAmelCase    ,			split_by_punct=__UpperCAmelCase)
      a						:		Tuple											=      rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))

      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    def      __snake_case							( self    :   int):
      a						:		Optional[Any]											=      self.get_tokenizer()
      a						:		Optional[int]											=      self.get_rust_tokenizer()

      a						:		Dict											=      "I was born in 92000, and this is falsé."

      a						:		Any											=      tokenizer.convert_ids_to_tokens(tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))
      a						:		Union[str, Any]											=      rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase))
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		Any											=      tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase)
      a						:		Dict											=      rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		Optional[int]											=      self.get_rust_tokenizer()
      a						:		List[str]											=      tokenizer.encode(__UpperCAmelCase)
      a						:		int											=      rust_tokenizer.encode(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    def      __snake_case							( self    :   Dict):
      a						:		Dict											=      "This is a test"
      a						:		str											=      [13, 1, 4398, 25, 21, 1289]
      a						:		Optional[int]											=      ["▁", "T", "his", "▁is", "▁a", "▁test"]
      a						:		List[str]											=      ["▁", "<unk>", "his", "▁is", "▁a", "▁test"]

      a						:		str											=      DebertaVaTokenizer(__UpperCAmelCase    ,			keep_accents=__UpperCAmelCase)
      a						:		int											=      DebertaVaTokenizerFast(__UpperCAmelCase    ,			keep_accents=__UpperCAmelCase)

      a						:		Tuple											=      tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		List[Any]											=      tokenizer.tokenize(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		Dict											=      tokenizer.convert_ids_to_tokens(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		str											=      rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		Any											=      rust_tokenizer.tokenize(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		int											=      rust_tokenizer.convert_ids_to_tokens(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      # fmt: off
      a						:		Dict											=      "I was born in 92000, and this is falsé."
      a						:		str											=      [13, 1, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]
      a						:		Tuple											=      ["▁", "I", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", ".", ]
      a						:		List[str]											=      ["▁", "<unk>", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", ".", ]
      # fmt: on

      a						:		Optional[Any]											=      tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		Dict											=      tokenizer.tokenize(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		Tuple											=      tokenizer.convert_ids_to_tokens(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)

      a						:		Optional[int]											=      rust_tokenizer.encode(__UpperCAmelCase    ,			add_special_tokens=__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		List[str]											=      rust_tokenizer.tokenize(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)
      a						:		Dict											=      rust_tokenizer.convert_ids_to_tokens(__UpperCAmelCase)
      self.assertListEqual(__UpperCAmelCase    ,			__UpperCAmelCase)






    def      __snake_case							( self    :   List[str]):
      a						:		Dict											=      DebertaVaTokenizer(__UpperCAmelCase)

      a						:		Union[str, Any]											=      tokenizer.encode("sequence builders")
      a						:		Any											=      tokenizer.encode("multi-sequence build")

      a						:		str											=      tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase)
      a						:		Any											=      tokenizer.build_inputs_with_special_tokens(__UpperCAmelCase    ,			__UpperCAmelCase)

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






    @slow
    def      __snake_case							( self    :   str):
      # fmt: off
      a						:		int											=      {"input_ids": [[1, 39867, 36, 19390, 486, 27, 35052, 81436, 18, 60685, 1225, 7, 35052, 81436, 18, 9367, 16899, 18, 15937, 53, 594, 773, 18, 16287, 30465, 36, 15937, 6, 41139, 38, 36979, 60763, 191, 6, 34132, 99, 6, 50538, 390, 43230, 6, 34132, 2779, 20850, 14, 699, 1072, 1194, 36, 382, 10901, 53, 7, 699, 1072, 2084, 36, 20422, 630, 53, 19, 105, 3049, 1896, 1053, 16899, 1506, 11, 37978, 4243, 7, 1237, 31869, 200, 16566, 654, 6, 35052, 81436, 7, 55630, 13593, 4, 2], [1, 26, 15011, 13, 667, 8, 1053, 18, 23611, 1237, 72356, 12820, 34, 104134, 1209, 35, 13313, 6627, 21, 202, 347, 7, 164, 2399, 11, 46, 4485, 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, 1232, 2864, 15785, 14951, 105, 5, 8581, 1250, 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=__UpperCAmelCase    ,			model_name="microsoft/deberta-v2-xlarge"    ,			revision="ad6e42c1532ddf3a15c39246b63f5559d558b670"    ,			)










"""simple docstring"""







from typing import Any, Dict, List, Union

from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline


if is_vision_available():
 from PIL import Image

 from ..image_utils import load_image

if is_torch_available():
 import torch

 from transformers.modeling_outputs import BaseModelOutput

 from ..models.auto.modeling_auto import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING

__lowercase    =				logging.get_logger(__name__)






@add_end_docstrings(_a  )
class 						_A  (  _a  ):







    """simple docstring"""




    def __init__( self    :   List[Any]    ,			**__UpperCAmelCase    :   List[Any]):
      super().__init__(**__UpperCAmelCase)

      if self.framework == "tf":
        raise ValueError(f'''The {self.__class__} is only available in PyTorch.''')

      requires_backends(self    ,			"vision")
      self.check_model_type(__UpperCAmelCase)






    def __call__( self    :   str    ,			__UpperCAmelCase    :   Union[str, "Image.Image", List[Dict[str, Any]]]    ,			__UpperCAmelCase    :   Union[str, List[str]] = None    ,			**__UpperCAmelCase    :   List[Any]    ,			):
      if "text_queries" in kwargs:
        a						:		List[Any]											=      kwargs.pop("text_queries")

      if isinstance(__UpperCAmelCase    ,			(str, Image.Image)):
        a						:		Any											=      {"image": image, "candidate_labels": candidate_labels}
      else:
        a						:		Optional[int]											=      image
      a						:		Optional[int]											=      super().__call__(__UpperCAmelCase    ,			**__UpperCAmelCase)
      return results






    def      __snake_case							( self    :   Optional[int]    ,			**__UpperCAmelCase    :   List[Any]):
      a						:		str											=      {}
      if "threshold" in kwargs:
        a						:		Dict											=      kwargs["threshold"]
      if "top_k" in kwargs:
        a						:		str											=      kwargs["top_k"]
      return {}, {}, postprocess_params






    def      __snake_case							( self    :   List[Any]    ,			__UpperCAmelCase    :   Optional[Any]):
      a						:		Union[str, Any]											=      load_image(inputs["image"])
      a						:		Any											=      inputs["candidate_labels"]
      if isinstance(__UpperCAmelCase    ,			__UpperCAmelCase):
        a						:		Optional[Any]											=      candidate_labels.split(",")

      a						:		Union[str, Any]											=      torch.tensor([[image.height, image.width]]    ,			dtype=torch.intaa)
      for i, candidate_label in enumerate(__UpperCAmelCase):
        a						:		int											=      self.tokenizer(__UpperCAmelCase    ,			return_tensors=self.framework)
        a						:		int											=      self.image_processor(__UpperCAmelCase    ,			return_tensors=self.framework)
        yield {
            "is_last": i == len(__UpperCAmelCase) - 1,
            "target_size": target_size,
            "candidate_label": candidate_label,
            **text_inputs,
            **image_features,
        }






    def      __snake_case							( self    :   Dict    ,			__UpperCAmelCase    :   Optional[int]):
      a						:		List[Any]											=      model_inputs.pop("target_size")
      a						:		Optional[int]											=      model_inputs.pop("candidate_label")
      a						:		List[Any]											=      model_inputs.pop("is_last")

      a						:		List[Any]											=      self.model(**__UpperCAmelCase)

      a						:		Union[str, Any]											=      {"target_size": target_size, "candidate_label": candidate_label, "is_last": is_last, **outputs}
      return model_outputs






    def      __snake_case							( self    :   str    ,			__UpperCAmelCase    :   Dict    ,			__UpperCAmelCase    :   Optional[int]=0.1    ,			__UpperCAmelCase    :   List[str]=None):
      a						:		Dict											=      []
      for model_output in model_outputs:
        a						:		int											=      model_output["candidate_label"]
        a						:		Any											=      BaseModelOutput(__UpperCAmelCase)
        a						:		Optional[Any]											=      self.image_processor.post_process_object_detection(
            outputs=__UpperCAmelCase    ,			threshold=__UpperCAmelCase    ,			target_sizes=model_output["target_size"])[0]

        for index in outputs["scores"].nonzero():
          a						:		Any											=      outputs["scores"][index].item()
          a						:		str											=      self._get_bounding_box(outputs["boxes"][index][0])

          a						:		Optional[Any]											=      {"score": score, "label": label, "box": box}
          results.append(__UpperCAmelCase)

      a						:		str											=      sorted(__UpperCAmelCase    ,			key=lambda __UpperCAmelCase: x["score"]    ,			reverse=__UpperCAmelCase)
      if top_k:
        a						:		Union[str, Any]											=      results[:top_k]

      return results






    def      __snake_case							( self    :   Union[str, Any]    ,			__UpperCAmelCase    :   "torch.Tensor"):
      if self.framework != "pt":
        raise ValueError("The ZeroShotObjectDetectionPipeline is only available in PyTorch.")
      a							,		a							,		a							,		a						:		List[Any]											=      box.int().tolist()
      a						:		str											=      {
          "xmin": xmin,
          "ymin": ymin,
          "xmax": xmax,
          "ymax": ymax,
      }
      return bbox






