




import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
 from PIL import Image

 from transformers import (
     AutoProcessor,
     BertTokenizerFast,
     BlipImageProcessor,
     GPTaTokenizer,
     InstructBlipProcessor,
     PreTrainedTokenizerFast,
 )



@require_vision
class       a					(       unittest.TestCase      ):

     '''simple docstring'''





     def   lowerCamelCase_       (     self       :      Optional[int]    ):
         UpperCAmelCase_										=					tempfile.mkdtemp()

         UpperCAmelCase_										=					BlipImageProcessor()
         UpperCAmelCase_										=					GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''    )
         UpperCAmelCase_										=					BertTokenizerFast.from_pretrained('''hf-internal-testing/tiny-random-bert'''    )

         UpperCAmelCase_										=					InstructBlipProcessor(__snake_case ,   __snake_case ,   __snake_case    )

         processor.save_pretrained(self.tmpdirname    )
     def   lowerCamelCase_       (     self       :      Union[str, Any] ,   **__snake_case       :      Optional[Any]    ):
         return AutoProcessor.from_pretrained(self.tmpdirname ,   **__snake_case    ).tokenizer
     def   lowerCamelCase_       (     self       :      Optional[int] ,   **__snake_case       :      Optional[int]    ):
         return AutoProcessor.from_pretrained(self.tmpdirname ,   **__snake_case    ).image_processor
     def   lowerCamelCase_       (     self       :      Dict ,   **__snake_case       :      Any    ):
         return AutoProcessor.from_pretrained(self.tmpdirname ,   **__snake_case    ).qformer_tokenizer
     def   lowerCamelCase_       (     self       :      List[str]    ):
         shutil.rmtree(self.tmpdirname    )
     def   lowerCamelCase_       (     self       :      Optional[int]    ):
         UpperCAmelCase_										=					[np.random.randint(2_55 ,   size=(3, 30, 4_00) ,   dtype=np.uinta    )]

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

         return image_inputs
     def   lowerCamelCase_       (     self       :      Any    ):
         UpperCAmelCase_										=					InstructBlipProcessor(
             tokenizer=self.get_tokenizer() ,   image_processor=self.get_image_processor() ,   qformer_tokenizer=self.get_qformer_tokenizer() ,   )
         processor.save_pretrained(self.tmpdirname    )

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

         UpperCAmelCase_										=					InstructBlipProcessor.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    )
         self.assertIsInstance(processor.qformer_tokenizer ,   __snake_case    )
     def   lowerCamelCase_       (     self       :      Union[str, Any]    ):
         UpperCAmelCase_										=					self.get_image_processor()
         UpperCAmelCase_										=					self.get_tokenizer()
         UpperCAmelCase_										=					self.get_qformer_tokenizer()

         UpperCAmelCase_										=					InstructBlipProcessor(
             tokenizer=__snake_case ,   image_processor=__snake_case ,   qformer_tokenizer=__snake_case    )

         UpperCAmelCase_										=					self.prepare_image_inputs()

         UpperCAmelCase_										=					image_processor(__snake_case ,   return_tensors='''np'''    )
         UpperCAmelCase_										=					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   lowerCamelCase_       (     self       :      Dict    ):
         UpperCAmelCase_										=					self.get_image_processor()
         UpperCAmelCase_										=					self.get_tokenizer()
         UpperCAmelCase_										=					self.get_qformer_tokenizer()

         UpperCAmelCase_										=					InstructBlipProcessor(
             tokenizer=__snake_case ,   image_processor=__snake_case ,   qformer_tokenizer=__snake_case    )

         UpperCAmelCase_										=					'''lower newer'''

         UpperCAmelCase_										=					processor(text=__snake_case    )

         UpperCAmelCase_										=					tokenizer(__snake_case ,   return_token_type_ids=__snake_case    )
         UpperCAmelCase_										=					qformer_tokenizer(__snake_case ,   return_token_type_ids=__snake_case    )

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

         for key in encoded_tokens_qformer.keys():
             self.assertListEqual(encoded_tokens_qformer[key] ,   encoded_processor['''qformer_''' + key]    )
     def   lowerCamelCase_       (     self       :      Optional[Any]    ):
         UpperCAmelCase_										=					self.get_image_processor()
         UpperCAmelCase_										=					self.get_tokenizer()
         UpperCAmelCase_										=					self.get_qformer_tokenizer()

         UpperCAmelCase_										=					InstructBlipProcessor(
             tokenizer=__snake_case ,   image_processor=__snake_case ,   qformer_tokenizer=__snake_case    )

         UpperCAmelCase_										=					'''lower newer'''
         UpperCAmelCase_										=					self.prepare_image_inputs()

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

         self.assertListEqual(
             list(inputs.keys()    ) ,   ['''input_ids''', '''attention_mask''', '''qformer_input_ids''', '''qformer_attention_mask''', '''pixel_values'''] ,   )

         # test if it raises when no input is passed
         with pytest.raises(__snake_case    ):
             processor()
     def   lowerCamelCase_       (     self       :      Optional[int]    ):
         UpperCAmelCase_										=					self.get_image_processor()
         UpperCAmelCase_										=					self.get_tokenizer()
         UpperCAmelCase_										=					self.get_qformer_tokenizer()

         UpperCAmelCase_										=					InstructBlipProcessor(
             tokenizer=__snake_case ,   image_processor=__snake_case ,   qformer_tokenizer=__snake_case    )

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

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

         self.assertListEqual(__snake_case ,   __snake_case    )




     def   lowerCamelCase_       (     self       :      Tuple    ):
         UpperCAmelCase_										=					self.get_image_processor()
         UpperCAmelCase_										=					self.get_tokenizer()
         UpperCAmelCase_										=					self.get_qformer_tokenizer()

         UpperCAmelCase_										=					InstructBlipProcessor(
             tokenizer=__snake_case ,   image_processor=__snake_case ,   qformer_tokenizer=__snake_case    )

         UpperCAmelCase_										=					'''lower newer'''
         UpperCAmelCase_										=					self.prepare_image_inputs()

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

         self.assertListEqual(
             list(inputs.keys()    ) ,   ['''input_ids''', '''attention_mask''', '''qformer_input_ids''', '''qformer_attention_mask''', '''pixel_values'''] ,   )











import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate



@dataclass(frozen=_A      )
class       a					(       _A      ):

     '''simple docstring'''





     lowerCAmelCase    :	str       		=  field(default='audio-classification'     ,       metadata={'include_in_asdict_even_if_is_default': True}      )
     lowerCAmelCase    :	ClassVar[Features]       		=  Features({'audio': Audio()}      )
     lowerCAmelCase    :	ClassVar[Features]       		=  Features({'labels': ClassLabel}      )
     lowerCAmelCase    :	str       		=  "audio"
     lowerCAmelCase    :	str       		=  "labels"
     def   lowerCamelCase_       (     self       :      Optional[Any] ,   __snake_case       :      List[Any]    ):
         if self.label_column not in features:
             raise ValueError(F'Column {self.label_column} is not present in features.'    )
         if not isinstance(features[self.label_column] ,   __snake_case    ):
             raise ValueError(F'Column {self.label_column} is not a ClassLabel.'    )
         UpperCAmelCase_										=					copy.deepcopy(self    )
         UpperCAmelCase_										=					self.label_schema.copy()
         UpperCAmelCase_										=					features[self.label_column]
         UpperCAmelCase_										=					label_schema
         return task_template




     @property
     def   lowerCamelCase_       (     self       :      Tuple    ):
         return {
             self.audio_column: "audio",
             self.label_column: "labels",
         }





