




import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
       UpperCAmelCase_									=	'pt'
elif is_tf_available():
       UpperCAmelCase_									=	'tf'
else:
       UpperCAmelCase_									=	'jax'





class     lowerCamelCase__(					__lowercase ,     unittest.TestCase):
      UpperCAmelCase__      :	Optional[Any]    		=   PerceiverTokenizer
      UpperCAmelCase__      :	List[str]    		=   False
      def 			lowerCAmelCase__						(				self: Any   ):
             super().setUp()
             __lowerCamelCase   =						PerceiverTokenizer()
             tokenizer.save_pretrained(self.tmpdirname   )
      @cached_property
      def 			lowerCAmelCase__						(				self: Union[str, Any]   ):
             return PerceiverTokenizer.from_pretrained("""deepmind/language-perceiver"""   )
      def 			lowerCAmelCase__						(				self: List[Any]    ,       **UpperCamelCase_: Union[str, Any]   ):
             return self.tokenizer_class.from_pretrained(self.tmpdirname    ,       **UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: List[str]    ,       UpperCamelCase_: Any    ,       UpperCamelCase_: Union[str, Any]=False    ,       UpperCamelCase_: Optional[Any]=20    ,       UpperCamelCase_: List[Any]=5   ):
             # XXX The default common tokenizer tests assume that every ID is decodable on its own.
             # This assumption is invalid for Perceiver because single bytes might not be
             # valid utf-8 (byte 128 for instance).
             # Here we're overriding the smallest possible method to provide
             # a clean sequence without making the same assumption.

             __lowerCamelCase   =						[]
             for i in range(len(UpperCamelCase_   )   ):
                    try:
                           __lowerCamelCase   =						tokenizer.decode([i]    ,       clean_up_tokenization_spaces=UpperCamelCase_   )
                    except UnicodeDecodeError:
                           pass
                    toks.append((i, tok)   )

             __lowerCamelCase   =						list(filter(lambda UpperCamelCase_   : re.match(r"""^[ a-zA-Z]+$"""    ,       t[1]   )    ,       UpperCamelCase_   )   )
             __lowerCamelCase   =						list(filter(lambda UpperCamelCase_   : [t[0]] == tokenizer.encode(t[1]    ,       add_special_tokens=UpperCamelCase_   )    ,       UpperCamelCase_   )   )
             if max_length is not None and len(UpperCamelCase_   ) > max_length:
                    __lowerCamelCase   =						toks[:max_length]
             if min_length is not None and len(UpperCamelCase_   ) < min_length and len(UpperCamelCase_   ) > 0:
                    while len(UpperCamelCase_   ) < min_length:
                           __lowerCamelCase   =						toks + toks
        # toks_str = [t[1] for t in toks]
             __lowerCamelCase   =						[t[0] for t in toks]

             # Ensure consistency
             __lowerCamelCase   =						tokenizer.decode(UpperCamelCase_    ,       clean_up_tokenization_spaces=UpperCamelCase_   )
             if " " not in output_txt and len(UpperCamelCase_   ) > 1:
                    __lowerCamelCase   =						(
                        tokenizer.decode([toks_ids[0]]    ,       clean_up_tokenization_spaces=UpperCamelCase_   )
                        + " "
                        + tokenizer.decode(toks_ids[1:]    ,       clean_up_tokenization_spaces=UpperCamelCase_   )
                    )
             if with_prefix_space:
                    __lowerCamelCase   =						" " + output_txt
             __lowerCamelCase   =						tokenizer.encode(UpperCamelCase_    ,       add_special_tokens=UpperCamelCase_   )
             return output_txt, output_ids
      def 			lowerCAmelCase__						(				self: str   ):
             __lowerCamelCase   =						self.perceiver_tokenizer
             __lowerCamelCase   =						"Unicode €."
             __lowerCamelCase   =						tokenizer(UpperCamelCase_   )
             __lowerCamelCase   =						[4, 91, 1_16, 1_11, 1_05, 1_17, 1_06, 1_07, 38, 2_32, 1_36, 1_78, 52, 5]
             self.assertEqual(encoded["""input_ids"""]    ,       UpperCamelCase_   )

             # decoding
             __lowerCamelCase   =						tokenizer.decode(UpperCamelCase_   )
             self.assertEqual(UpperCamelCase_    ,       """[CLS]Unicode €.[SEP]"""   )

             __lowerCamelCase   =						tokenizer("""e è é ê ë"""   )
             __lowerCamelCase   =						[4, 1_07, 38, 2_01, 1_74, 38, 2_01, 1_75, 38, 2_01, 1_76, 38, 2_01, 1_77, 5]
             self.assertEqual(encoded["""input_ids"""]    ,       UpperCamelCase_   )
             # decoding
             __lowerCamelCase   =						tokenizer.decode(UpperCamelCase_   )
             self.assertEqual(UpperCamelCase_    ,       """[CLS]e è é ê ë[SEP]"""   )

             # encode/decode, but with `encode` instead of `__call__`
             self.assertEqual(tokenizer.decode(tokenizer.encode("""e è é ê ë"""   )   )    ,       """[CLS]e è é ê ë[SEP]"""   )
      def 			lowerCAmelCase__						(				self: Tuple   ):
             __lowerCamelCase   =						self.perceiver_tokenizer
             __lowerCamelCase   =						["A long paragraph for summarization.", "Another paragraph for summarization."]
             # fmt: off
             __lowerCamelCase   =						[4, 71, 38, 1_14, 1_17, 1_16, 1_09, 38, 1_18, 1_03, 1_20, 1_03, 1_09, 1_20, 1_03, 1_18, 1_10, 38, 1_08, 1_17, 1_20, 38, 1_21, 1_23, 1_15, 1_15, 1_03, 1_20, 1_11, 1_28, 1_03, 1_22, 1_11, 1_17, 1_16, 52, 5, 0]
             # fmt: on
             __lowerCamelCase   =						tokenizer(UpperCamelCase_    ,       padding=UpperCamelCase_    ,       return_tensors=UpperCamelCase_   )
             self.assertIsInstance(UpperCamelCase_    ,       UpperCamelCase_   )

             if FRAMEWORK != "jax":
                    __lowerCamelCase   =						list(batch.input_ids.numpy()[0]   )
             else:
                    __lowerCamelCase   =						list(batch.input_ids.tolist()[0]   )

             self.assertListEqual(UpperCamelCase_    ,       UpperCamelCase_   )

             self.assertEqual((2, 38)    ,       batch.input_ids.shape   )
             self.assertEqual((2, 38)    ,       batch.attention_mask.shape   )
      def 			lowerCAmelCase__						(				self: Optional[int]   ):
             __lowerCamelCase   =						self.perceiver_tokenizer
             __lowerCamelCase   =						["A long paragraph for summarization.", "Another paragraph for summarization."]
             __lowerCamelCase   =						tokenizer(UpperCamelCase_    ,       padding=UpperCamelCase_    ,       return_tensors=UpperCamelCase_   )
             # check if input_ids are returned and no decoder_input_ids
             self.assertIn("""input_ids"""    ,       UpperCamelCase_   )
             self.assertIn("""attention_mask"""    ,       UpperCamelCase_   )
             self.assertNotIn("""decoder_input_ids"""    ,       UpperCamelCase_   )
             self.assertNotIn("""decoder_attention_mask"""    ,       UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: List[str]   ):
             __lowerCamelCase   =						self.perceiver_tokenizer
             __lowerCamelCase   =						[
                 "Summary of the text.",
                 "Another summary.",
             ]
             __lowerCamelCase   =						tokenizer(
                 text_target=UpperCamelCase_    ,       max_length=32    ,       padding="""max_length"""    ,       truncation=UpperCamelCase_    ,       return_tensors=UpperCamelCase_   )
             self.assertEqual(32    ,       targets["""input_ids"""].shape[1]   )
      def 			lowerCAmelCase__						(				self: Optional[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(UpperCamelCase_    ,       add_special_tokens=UpperCamelCase_   )
                           tokenizer.save_pretrained(UpperCamelCase_   )

                           __lowerCamelCase   =						tokenizer.__class__.from_pretrained(UpperCamelCase_   )
                           __lowerCamelCase   =						after_tokenizer.encode(UpperCamelCase_    ,       add_special_tokens=UpperCamelCase_   )
                           self.assertListEqual(UpperCamelCase_    ,       UpperCamelCase_   )

                           shutil.rmtree(UpperCamelCase_   )

             __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"
                           tokenizer.add_tokens(["""bim""", """bambam"""]   )
                           __lowerCamelCase   =						tokenizer.additional_special_tokens
                           additional_special_tokens.append("""new_additional_special_token"""   )
                           tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}   )
                           __lowerCamelCase   =						tokenizer.encode(UpperCamelCase_    ,       add_special_tokens=UpperCamelCase_   )
                           tokenizer.save_pretrained(UpperCamelCase_   )

                           __lowerCamelCase   =						tokenizer.__class__.from_pretrained(UpperCamelCase_   )
                           __lowerCamelCase   =						after_tokenizer.encode(UpperCamelCase_    ,       add_special_tokens=UpperCamelCase_   )
                           self.assertListEqual(UpperCamelCase_    ,       UpperCamelCase_   )
                           self.assertIn("""new_additional_special_token"""    ,       after_tokenizer.additional_special_tokens   )
                           self.assertEqual(after_tokenizer.model_max_length    ,       42   )

                           __lowerCamelCase   =						tokenizer.__class__.from_pretrained(UpperCamelCase_    ,       model_max_length=43   )
                           self.assertEqual(tokenizer.model_max_length    ,       43   )

                           shutil.rmtree(UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: int   ):
             __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(UpperCamelCase_   )

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

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

                           __lowerCamelCase   =						[F'<extra_id_{i}>' for i in range(1_25   )]

                           __lowerCamelCase   =						added_tokens_extra_ids + [
                               "an_additional_special_token"
                           ]
                           __lowerCamelCase   =						added_tokens_extra_ids + [
                               "an_additional_special_token"
                           ]

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

                           # 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(
                               UpperCamelCase_    ,       )
                           self.assertIn(
                               """an_additional_special_token"""    ,       tokenizer_without_change_in_init.additional_special_tokens   )
                           self.assertEqual(
                               ["""an_additional_special_token"""]    ,       tokenizer_without_change_in_init.convert_ids_to_tokens(
                                   tokenizer_without_change_in_init.convert_tokens_to_ids(["""an_additional_special_token"""]   )   )    ,       )

                           # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                           __lowerCamelCase   =						added_tokens_extra_ids + [AddedToken("""a_new_additional_special_token"""    ,       lstrip=UpperCamelCase_   )]
                           __lowerCamelCase   =						tokenizer_class.from_pretrained(
                               UpperCamelCase_    ,       additional_special_tokens=UpperCamelCase_    ,       )

                           self.assertIn("""a_new_additional_special_token"""    ,       tokenizer.additional_special_tokens   )
                           self.assertEqual(
                               ["""a_new_additional_special_token"""]    ,       tokenizer.convert_ids_to_tokens(
                                   tokenizer.convert_tokens_to_ids(["""a_new_additional_special_token"""]   )   )    ,       )
      def 			lowerCAmelCase__						(				self: Tuple   ):
             __lowerCamelCase   =						self.perceiver_tokenizer
             self.assertEqual(tokenizer.decode([1_78]   )    ,       """�"""   )
      def 			lowerCAmelCase__						(				self: int   ):
             pass
      def 			lowerCAmelCase__						(				self: Dict   ):
             pass
      def 			lowerCAmelCase__						(				self: List[str]   ):
             pass
      def 			lowerCAmelCase__						(				self: List[Any]   ):
             pass




      def 			lowerCAmelCase__						(				self: Any   ):
             # The default common tokenizer tests uses invalid tokens for Perceiver that can only accept one-character
             # strings and special added tokens as tokens
             __lowerCamelCase   =						self.get_tokenizers(fast=UpperCamelCase_    ,       do_lower_case=UpperCamelCase_   )
             for tokenizer in tokenizers:
                    with self.subTest(F'{tokenizer.__class__.__name__}'   ):
                           __lowerCamelCase   =						["[CLS]", "t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "s", "t", "[SEP]"]
                           __lowerCamelCase   =						tokenizer.convert_tokens_to_string(UpperCamelCase_   )

                           self.assertIsInstance(UpperCamelCase_    ,       UpperCamelCase_   )



import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
		lowercase  :					int													=       {
		    'linear': PIL.Image.Resampling.BILINEAR,
		    'bilinear': PIL.Image.Resampling.BILINEAR,
		    'bicubic': PIL.Image.Resampling.BICUBIC,
		    'lanczos': PIL.Image.Resampling.LANCZOS,
		    'nearest': PIL.Image.Resampling.NEAREST,
		}
else:
		lowercase  :					Any													=       {
		    'linear': PIL.Image.LINEAR,
		    'bilinear': PIL.Image.BILINEAR,
		    'bicubic': PIL.Image.BICUBIC,
		    'lanczos': PIL.Image.LANCZOS,
		    'nearest': PIL.Image.NEAREST,
		}




def 	_SCREAMING_SNAKE_CASE					(		_lowerCamelCase :			int)					->    Any:






							'''simple docstring'''





							__UpperCamelCase	:   Union[str, Any]			   =					(images / 2 + 0.5).clamp(0						,  1)
							__UpperCamelCase	:   int			   =					images.cpu().permute(0						,  2						,  3						,  1).float().numpy()
							__UpperCamelCase	:   Dict			   =					numpy_to_pil(_lowerCamelCase)
							return images




def 	_SCREAMING_SNAKE_CASE					(		_lowerCamelCase :			Optional[Any])					->    Optional[Any]:






							'''simple docstring'''





							if images.ndim == 3:
														__UpperCamelCase	:   Optional[int]			   =					images[None, ...]
							__UpperCamelCase	:   Dict			   =					(images * 255).round().astype("uint8")
							if images.shape[-1] == 1:
														# special case for grayscale (single channel) images
														__UpperCamelCase	:   int			   =					[Image.fromarray(image.squeeze()						,  mode="L") for image in images]
							else:
														__UpperCamelCase	:   Union[str, Any]			   =					[Image.fromarray(_lowerCamelCase) for image in images]

							return pil_images