





'''simple docstring'''






import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin




class 			UpperCAmelCase					(      snake_case_							,		unittest.TestCase       ):
      _lowercase:      Any											=       CanineTokenizer
      _lowercase:      Tuple											=       False




      def     lowercase__   (      self      :			Tuple  )    ->				List[str]:
            super().setUp()
            _lowerCAmelCase												=							CanineTokenizer()
            tokenizer.save_pretrained(self.tmpdirname  )




      @cached_property
      def     lowercase__   (      self      :			Optional[int]  )    ->				str:
            return CanineTokenizer.from_pretrained("""google/canine-s"""  )




      def     lowercase__   (      self      :			Tuple      ,      **__snake_case      :			int  )    ->				CanineTokenizer:
            _lowerCAmelCase												=							self.tokenizer_class.from_pretrained(self.tmpdirname      ,      **__snake_case  )
            _lowerCAmelCase												=							10_24
            return tokenizer




      @require_torch
      def     lowercase__   (      self      :			Any  )    ->				int:
            _lowerCAmelCase												=							self.canine_tokenizer
            _lowerCAmelCase												=							["""Life is like a box of chocolates.""", """You never know what you're gonna get."""]
            # fmt: off
            _lowerCAmelCase												=							[5_73_44, 76, 1_05, 1_02, 1_01, 32, 1_05, 1_15, 32, 1_08, 1_05, 1_07, 1_01, 32, 97, 32, 98, 1_11, 1_20, 32, 1_11, 1_02, 32, 99, 1_04, 1_11, 99, 1_11, 1_08, 97, 1_16, 1_01, 1_15, 46, 5_73_45, 0, 0, 0, 0]
            # fmt: on
            _lowerCAmelCase												=							tokenizer(__snake_case      ,      padding=__snake_case      ,      return_tensors="""pt"""  )
            self.assertIsInstance(__snake_case      ,      __snake_case  )

            _lowerCAmelCase												=							list(batch.input_ids.numpy()[0]  )

            self.assertListEqual(__snake_case      ,      __snake_case  )

            self.assertEqual((2, 39)      ,      batch.input_ids.shape  )
            self.assertEqual((2, 39)      ,      batch.attention_mask.shape  )




      @require_torch
      def     lowercase__   (      self      :			Dict  )    ->				Optional[Any]:
            _lowerCAmelCase												=							self.canine_tokenizer
            _lowerCAmelCase												=							["""Once there was a man.""", """He wrote a test in HuggingFace Tranformers."""]
            _lowerCAmelCase												=							tokenizer(__snake_case      ,      padding=__snake_case      ,      return_tensors="""pt"""  )
            # check if input_ids, attention_mask and token_type_ids are returned
            self.assertIn("""input_ids"""      ,      __snake_case  )
            self.assertIn("""attention_mask"""      ,      __snake_case  )
            self.assertIn("""token_type_ids"""      ,      __snake_case  )




      @require_torch
      def     lowercase__   (      self      :			Dict  )    ->				Union[str, Any]:
            _lowerCAmelCase												=							self.canine_tokenizer
            _lowerCAmelCase												=							[
                """What's the weater?""",
                """It's about 25 degrees.""",
            ]
            _lowerCAmelCase												=							tokenizer(
                text_target=__snake_case      ,      max_length=32      ,      padding="""max_length"""      ,      truncation=__snake_case      ,      return_tensors="""pt"""  )
            self.assertEqual(32      ,      targets["""input_ids"""].shape[1]  )




      def     lowercase__   (      self      :			Union[str, Any]  )    ->				int:
            # safety check on max_len default value so we are sure the test works
            _lowerCAmelCase												=							self.get_tokenizers()
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        self.assertNotEqual(tokenizer.model_max_length      ,      42  )

        # Now let's start the test
            _lowerCAmelCase												=							self.get_tokenizers()
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        # Isolate this from the other tests because we save additional tokens/etc
                        _lowerCAmelCase												=							tempfile.mkdtemp()

                        _lowerCAmelCase												=							""" He is very happy, UNwant\u00E9d,running"""
                        _lowerCAmelCase												=							tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        tokenizer.save_pretrained(__snake_case  )

                        _lowerCAmelCase												=							tokenizer.__class__.from_pretrained(__snake_case  )
                        _lowerCAmelCase												=							after_tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        self.assertListEqual(__snake_case      ,      __snake_case  )

                        shutil.rmtree(__snake_case  )

            _lowerCAmelCase												=							self.get_tokenizers(model_max_length=42  )
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        # Isolate this from the other tests because we save additional tokens/etc
                        _lowerCAmelCase												=							tempfile.mkdtemp()

                        _lowerCAmelCase												=							""" He is very happy, UNwant\u00E9d,running"""

                        _lowerCAmelCase												=							tokenizer.additional_special_tokens

                        # We can add a new special token for Canine as follows:
                        _lowerCAmelCase												=							chr(0xe0_07  )
                        additional_special_tokens.append(__snake_case  )
                        tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}  )
                        _lowerCAmelCase												=							tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        tokenizer.save_pretrained(__snake_case  )

                        _lowerCAmelCase												=							tokenizer.__class__.from_pretrained(__snake_case  )
                        _lowerCAmelCase												=							after_tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        self.assertListEqual(__snake_case      ,      __snake_case  )
                        self.assertIn(__snake_case      ,      after_tokenizer.additional_special_tokens  )
                        self.assertEqual(after_tokenizer.model_max_length      ,      42  )

                        _lowerCAmelCase												=							tokenizer.__class__.from_pretrained(__snake_case      ,      model_max_length=43  )
                        self.assertEqual(tokenizer.model_max_length      ,      43  )

                        shutil.rmtree(__snake_case  )




      def     lowercase__   (      self      :			List[str]  )    ->				Union[str, Any]:
            _lowerCAmelCase												=							self.get_tokenizers(do_lower_case=__snake_case  )
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        _lowerCAmelCase					,							_lowerCAmelCase												=							self.get_clean_sequence(__snake_case  )

                        # a special token for Canine can be defined as follows:
                        _lowerCAmelCase												=							0xe0_05
                        _lowerCAmelCase												=							chr(__snake_case  )

                        tokenizer.add_special_tokens({"""cls_token""": special_token}  )
                        _lowerCAmelCase												=							tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        self.assertEqual(len(__snake_case  )      ,      1  )

                        _lowerCAmelCase												=							tokenizer.decode(ids + encoded_special_token      ,      clean_up_tokenization_spaces=__snake_case  )
                        _lowerCAmelCase												=							tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )

                        _lowerCAmelCase												=							tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        _lowerCAmelCase												=							tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        self.assertEqual(__snake_case      ,      input_encoded + special_token_id  )

                        _lowerCAmelCase												=							tokenizer.decode(__snake_case      ,      skip_special_tokens=__snake_case  )
                        self.assertTrue(special_token not in decoded  )




      def     lowercase__   (      self      :			str  )    ->				Optional[int]:
            _lowerCAmelCase												=							self.get_tokenizers(do_lower_case=__snake_case  )
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        _lowerCAmelCase												=							chr(0xe0_05  )
                        _lowerCAmelCase												=							chr(0xe0_06  )

                        # `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
                        tokenizer.add_tokens([SPECIAL_TOKEN_1]      ,      special_tokens=__snake_case  )
                        # `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
                        # which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
                        tokenizer.add_special_tokens({"""additional_special_tokens""": [SPECIAL_TOKEN_2]}  )

                        _lowerCAmelCase												=							tokenizer.tokenize(__snake_case  )
                        _lowerCAmelCase												=							tokenizer.tokenize(__snake_case  )

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




      @require_tokenizers
      def     lowercase__   (      self      :			Optional[int]  )    ->				Optional[int]:
            _lowerCAmelCase												=							self.get_tokenizers(do_lower_case=__snake_case  )
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        # a special token for Canine can be defined as follows:
                        _lowerCAmelCase												=							0xe0_06
                        _lowerCAmelCase												=							chr(__snake_case  )

                        _lowerCAmelCase												=							AddedToken(__snake_case      ,      lstrip=__snake_case  )
                        tokenizer.add_special_tokens({"""additional_special_tokens""": [new_token]}  )

                        with tempfile.TemporaryDirectory() as tmp_dir_name:
                              tokenizer.save_pretrained(__snake_case  )
                              tokenizer.from_pretrained(__snake_case  )




      def     lowercase__   (      self      :			Union[str, Any]  )    ->				List[str]:
            _lowerCAmelCase												=							[]
            if self.test_slow_tokenizer:
                  tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())  )

            if self.test_rust_tokenizer:
                  tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())  )

            for tokenizer_class, tokenizer_utils in tokenizer_list:
                  with tempfile.TemporaryDirectory() as tmp_dir:
                        tokenizer_utils.save_pretrained(__snake_case  )

                        with open(os.path.join(__snake_case      ,      """special_tokens_map.json"""  )      ,      encoding="""utf-8"""  ) as json_file:
                              _lowerCAmelCase												=							json.load(__snake_case  )

                        with open(os.path.join(__snake_case      ,      """tokenizer_config.json"""  )      ,      encoding="""utf-8"""  ) as json_file:
                              _lowerCAmelCase												=							json.load(__snake_case  )

                        # a special token for Canine can be defined as follows:
                        _lowerCAmelCase												=							0xe0_06
                        _lowerCAmelCase												=							chr(__snake_case  )

                        _lowerCAmelCase												=							[new_token_a]
                        _lowerCAmelCase												=							[new_token_a]

                        with open(os.path.join(__snake_case      ,      """special_tokens_map.json"""  )      ,      """w"""      ,      encoding="""utf-8"""  ) as outfile:
                              json.dump(__snake_case      ,      __snake_case  )
                        with open(os.path.join(__snake_case      ,      """tokenizer_config.json"""  )      ,      """w"""      ,      encoding="""utf-8"""  ) as outfile:
                              json.dump(__snake_case      ,      __snake_case  )

                        # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                        # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                        # "special_tokens_map.json" files
                        _lowerCAmelCase												=							tokenizer_class.from_pretrained(__snake_case      ,      extra_ids=0  )
                        self.assertIn(__snake_case      ,      tokenizer_without_change_in_init.additional_special_tokens  )
                        # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
                        self.assertEqual(
                            [new_token_a]      ,      tokenizer_without_change_in_init.convert_ids_to_tokens(
                                tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]  )  )      ,      )

                        _lowerCAmelCase												=							0xe0_07
                        _lowerCAmelCase												=							chr(__snake_case  )
                        # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                        _lowerCAmelCase												=							[AddedToken(__snake_case      ,      lstrip=__snake_case  )]
                        _lowerCAmelCase												=							tokenizer_class.from_pretrained(
                            __snake_case      ,      additional_special_tokens=__snake_case      ,      extra_ids=0  )

                        self.assertIn(__snake_case      ,      tokenizer.additional_special_tokens  )
                        # self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
                        self.assertEqual(
                            [new_token_a]      ,      tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]  )  )  )




      @require_tokenizers
      def     lowercase__   (      self      :			int  )    ->				Union[str, Any]:
            _lowerCAmelCase												=							self.get_tokenizers(do_lower_case=__snake_case  )
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        _lowerCAmelCase												=							"""hello world"""
                        if self.space_between_special_tokens:
                              _lowerCAmelCase												=							"""[CLS] hello world [SEP]"""
                        else:
                              _lowerCAmelCase												=							input
                        _lowerCAmelCase												=							tokenizer.encode(__snake_case      ,      add_special_tokens=__snake_case  )
                        _lowerCAmelCase												=							tokenizer.decode(__snake_case      ,      spaces_between_special_tokens=self.space_between_special_tokens  )
                        self.assertIn(__snake_case      ,      [output, output.lower()]  )




      def     lowercase__   (      self      :			Optional[Any]  )    ->				Any:
            _lowerCAmelCase												=							self.get_tokenizers()
            for tokenizer in tokenizers:
                  with self.subTest(f"{tokenizer.__class__.__name__}"  ):
                        _lowerCAmelCase												=							[
                            """bos_token""",
                            """eos_token""",
                            """unk_token""",
                            """sep_token""",
                            """pad_token""",
                            """cls_token""",
                            """mask_token""",
                        ]

            _lowerCAmelCase												=							"""a"""
            _lowerCAmelCase												=							ord(__snake_case  )

            for attr in attributes_list:
                  setattr(__snake_case      ,      attr + """_id"""      ,      __snake_case  )
                  self.assertEqual(getattr(__snake_case      ,      __snake_case  )      ,      __snake_case  )
                  self.assertEqual(getattr(__snake_case      ,      attr + """_id"""  )      ,      __snake_case  )

                  setattr(__snake_case      ,      attr + """_id"""      ,      __snake_case  )
                  self.assertEqual(getattr(__snake_case      ,      __snake_case  )      ,      __snake_case  )
                  self.assertEqual(getattr(__snake_case      ,      attr + """_id"""  )      ,      __snake_case  )

            setattr(__snake_case      ,      """additional_special_tokens_ids"""      ,      []  )
            self.assertListEqual(getattr(__snake_case      ,      """additional_special_tokens"""  )      ,      []  )
            self.assertListEqual(getattr(__snake_case      ,      """additional_special_tokens_ids"""  )      ,      []  )

            _lowerCAmelCase												=							0xe0_06
            _lowerCAmelCase												=							chr(__snake_case  )
            setattr(__snake_case      ,      """additional_special_tokens_ids"""      ,      [additional_special_token_id]  )
            self.assertListEqual(getattr(__snake_case      ,      """additional_special_tokens"""  )      ,      [additional_special_token]  )
            self.assertListEqual(getattr(__snake_case      ,      """additional_special_tokens_ids"""  )      ,      [additional_special_token_id]  )




      def     lowercase__   (      self      :			Any  )    ->				Optional[int]:
            pass




      def     lowercase__   (      self      :			int  )    ->				int:
            pass




      def     lowercase__   (      self      :			Optional[Any]  )    ->				List[Any]:
            pass




      def     lowercase__   (      self      :			Union[str, Any]  )    ->				Union[str, Any]:
            pass




      def     lowercase__   (      self      :			int  )    ->				Union[str, Any]:
            pass




      def     lowercase__   (      self      :			Optional[int]  )    ->				Optional[int]:
            pass




      def     lowercase__   (      self      :			str  )    ->				List[Any]:
            pass




      def     lowercase__   (      self      :			Optional[int]  )    ->				Optional[int]:
            pass













'''simple docstring'''






import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
      from PIL import Image

      from transformers import CLIPSegProcessor, ViTImageProcessor




@require_vision
class 			UpperCAmelCase					(      unittest.TestCase       ):




      def     lowercase__   (      self      :			List[str]  )    ->				Dict:
            _lowerCAmelCase												=							tempfile.mkdtemp()

            # fmt: off
            _lowerCAmelCase												=							["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
            # fmt: on
            _lowerCAmelCase												=							dict(zip(__snake_case      ,      range(len(__snake_case  )  )  )  )
            _lowerCAmelCase												=							["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
            _lowerCAmelCase												=							{"""unk_token""": """<unk>"""}

            _lowerCAmelCase												=							os.path.join(self.tmpdirname      ,      VOCAB_FILES_NAMES["""vocab_file"""]  )
            _lowerCAmelCase												=							os.path.join(self.tmpdirname      ,      VOCAB_FILES_NAMES["""merges_file"""]  )
            with open(self.vocab_file      ,      """w"""      ,      encoding="""utf-8"""  ) as fp:
                  fp.write(json.dumps(__snake_case  ) + """\n"""  )
            with open(self.merges_file      ,      """w"""      ,      encoding="""utf-8"""  ) as fp:
                  fp.write("""\n""".join(__snake_case  )  )

            _lowerCAmelCase												=							{
                """do_resize""": True,
                """size""": 20,
                """do_center_crop""": True,
                """crop_size""": 18,
                """do_normalize""": True,
                """image_mean""": [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
                """image_std""": [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
            }
            _lowerCAmelCase												=							os.path.join(self.tmpdirname      ,      __snake_case  )
            with open(self.image_processor_file      ,      """w"""      ,      encoding="""utf-8"""  ) as fp:
                  json.dump(__snake_case      ,      __snake_case  )




      def     lowercase__   (      self      :			Optional[int]      ,      **__snake_case      :			Dict  )    ->				List[str]:
            return CLIPTokenizer.from_pretrained(self.tmpdirname      ,      **__snake_case  )




      def     lowercase__   (      self      :			List[str]      ,      **__snake_case      :			Any  )    ->				List[Any]:
            return CLIPTokenizerFast.from_pretrained(self.tmpdirname      ,      **__snake_case  )




      def     lowercase__   (      self      :			Tuple      ,      **__snake_case      :			List[str]  )    ->				int:
            return ViTImageProcessor.from_pretrained(self.tmpdirname      ,      **__snake_case  )




      def     lowercase__   (      self      :			str  )    ->				Optional[Any]:
            shutil.rmtree(self.tmpdirname  )




      def     lowercase__   (      self      :			str  )    ->				List[Any]:
            _lowerCAmelCase												=							[np.random.randint(2_55      ,      size=(3, 30, 4_00)      ,      dtype=np.uinta  )]

            _lowerCAmelCase												=							[Image.fromarray(np.moveaxis(__snake_case      ,      0      ,      -1  )  ) for x in image_inputs]

            return image_inputs




      def     lowercase__   (      self      :			Optional[Any]  )    ->				List[str]:
            _lowerCAmelCase												=							self.get_tokenizer()
            _lowerCAmelCase												=							self.get_rust_tokenizer()
            _lowerCAmelCase												=							self.get_image_processor()

            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=__snake_case      ,      image_processor=__snake_case  )
            processor_slow.save_pretrained(self.tmpdirname  )
            _lowerCAmelCase												=							CLIPSegProcessor.from_pretrained(self.tmpdirname      ,      use_fast=__snake_case  )

            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=__snake_case      ,      image_processor=__snake_case  )
            processor_fast.save_pretrained(self.tmpdirname  )
            _lowerCAmelCase												=							CLIPSegProcessor.from_pretrained(self.tmpdirname  )

            self.assertEqual(processor_slow.tokenizer.get_vocab()      ,      tokenizer_slow.get_vocab()  )
            self.assertEqual(processor_fast.tokenizer.get_vocab()      ,      tokenizer_fast.get_vocab()  )
            self.assertEqual(tokenizer_slow.get_vocab()      ,      tokenizer_fast.get_vocab()  )
            self.assertIsInstance(processor_slow.tokenizer      ,      __snake_case  )
            self.assertIsInstance(processor_fast.tokenizer      ,      __snake_case  )

            self.assertEqual(processor_slow.image_processor.to_json_string()      ,      image_processor.to_json_string()  )
            self.assertEqual(processor_fast.image_processor.to_json_string()      ,      image_processor.to_json_string()  )
            self.assertIsInstance(processor_slow.image_processor      ,      __snake_case  )
            self.assertIsInstance(processor_fast.image_processor      ,      __snake_case  )




      def     lowercase__   (      self      :			Optional[int]  )    ->				Dict:
            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=self.get_tokenizer()      ,      image_processor=self.get_image_processor()  )
            processor.save_pretrained(self.tmpdirname  )

            _lowerCAmelCase												=							self.get_tokenizer(bos_token="""(BOS)"""      ,      eos_token="""(EOS)"""  )
            _lowerCAmelCase												=							self.get_image_processor(do_normalize=__snake_case      ,      padding_value=1.0  )

            _lowerCAmelCase												=							CLIPSegProcessor.from_pretrained(
                self.tmpdirname      ,      bos_token="""(BOS)"""      ,      eos_token="""(EOS)"""      ,      do_normalize=__snake_case      ,      padding_value=1.0  )

            self.assertEqual(processor.tokenizer.get_vocab()      ,      tokenizer_add_kwargs.get_vocab()  )
            self.assertIsInstance(processor.tokenizer      ,      __snake_case  )

            self.assertEqual(processor.image_processor.to_json_string()      ,      image_processor_add_kwargs.to_json_string()  )
            self.assertIsInstance(processor.image_processor      ,      __snake_case  )




      def     lowercase__   (      self      :			Tuple  )    ->				List[Any]:
            _lowerCAmelCase												=							self.get_image_processor()
            _lowerCAmelCase												=							self.get_tokenizer()

            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=__snake_case      ,      image_processor=__snake_case  )

            _lowerCAmelCase												=							self.prepare_image_inputs()

            _lowerCAmelCase												=							image_processor(__snake_case      ,      return_tensors="""np"""  )
            _lowerCAmelCase												=							processor(images=__snake_case      ,      return_tensors="""np"""  )

            for key in input_feat_extract.keys():
                  self.assertAlmostEqual(input_feat_extract[key].sum()      ,      input_processor[key].sum()      ,      delta=1E-2  )




      def     lowercase__   (      self      :			Any  )    ->				str:
            _lowerCAmelCase												=							self.get_image_processor()
            _lowerCAmelCase												=							self.get_tokenizer()

            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=__snake_case      ,      image_processor=__snake_case  )

            _lowerCAmelCase												=							"""lower newer"""

            _lowerCAmelCase												=							processor(text=__snake_case  )

            _lowerCAmelCase												=							tokenizer(__snake_case  )

            for key in encoded_tok.keys():
                  self.assertListEqual(encoded_tok[key]      ,      encoded_processor[key]  )




      def     lowercase__   (      self      :			str  )    ->				Union[str, Any]:
            _lowerCAmelCase												=							self.get_image_processor()
            _lowerCAmelCase												=							self.get_tokenizer()

            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=__snake_case      ,      image_processor=__snake_case  )

            _lowerCAmelCase												=							"""lower newer"""
            _lowerCAmelCase												=							self.prepare_image_inputs()

            _lowerCAmelCase												=							processor(text=__snake_case      ,      images=__snake_case  )

            self.assertListEqual(list(inputs.keys()  )      ,      ["""input_ids""", """attention_mask""", """pixel_values"""]  )

            # test if it raises when no input is passed
            with pytest.raises(__snake_case  ):
                  processor()




      def     lowercase__   (      self      :			Union[str, Any]  )    ->				Dict:
            _lowerCAmelCase												=							self.get_image_processor()
            _lowerCAmelCase												=							self.get_tokenizer()

            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=__snake_case      ,      image_processor=__snake_case  )

            _lowerCAmelCase												=							self.prepare_image_inputs()
            _lowerCAmelCase												=							self.prepare_image_inputs()

            _lowerCAmelCase												=							processor(images=__snake_case      ,      visual_prompt=__snake_case  )

            self.assertListEqual(list(inputs.keys()  )      ,      ["""pixel_values""", """conditional_pixel_values"""]  )

            # test if it raises when no input is passed
            with pytest.raises(__snake_case  ):
                  processor()




      def     lowercase__   (      self      :			int  )    ->				Tuple:
            _lowerCAmelCase												=							self.get_image_processor()
            _lowerCAmelCase												=							self.get_tokenizer()

            _lowerCAmelCase												=							CLIPSegProcessor(tokenizer=__snake_case      ,      image_processor=__snake_case  )

            _lowerCAmelCase												=							[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            _lowerCAmelCase												=							processor.batch_decode(__snake_case  )
            _lowerCAmelCase												=							tokenizer.batch_decode(__snake_case  )

            self.assertListEqual(__snake_case      ,      __snake_case  )






