






'''simple docstring'''
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      __SCREAMING_SNAKE_CASE      (			unittest.TestCase				):




 def      __magic_name__	(      self	:							str      )	->						Optional[Any]:
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=tempfile.mkdtemp()

       SCREAMING_SNAKE_CASE__     :				List[str]									=BlipImageProcessor()
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''      )
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=BertTokenizerFast.from_pretrained('''hf-internal-testing/tiny-random-bert'''      )

       SCREAMING_SNAKE_CASE__     :				List[Any]									=InstructBlipProcessor(__lowercase					,      __lowercase					,      __lowercase      )

       processor.save_pretrained(self.tmpdirname      )




 def      __magic_name__	(      self	:							Any					,      **__lowercase	:							Union[str, Any]      )	->						Optional[Any]:
       return AutoProcessor.from_pretrained(self.tmpdirname					,      **__lowercase      ).tokenizer




 def      __magic_name__	(      self	:							Tuple					,      **__lowercase	:							Optional[int]      )	->						List[Any]:
       return AutoProcessor.from_pretrained(self.tmpdirname					,      **__lowercase      ).image_processor




 def      __magic_name__	(      self	:							Dict					,      **__lowercase	:							Optional[int]      )	->						int:
       return AutoProcessor.from_pretrained(self.tmpdirname					,      **__lowercase      ).qformer_tokenizer




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




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

       SCREAMING_SNAKE_CASE__     :				Any									=[Image.fromarray(np.moveaxis(__lowercase					,      0					,      -1      )      ) for x in image_inputs]

       return image_inputs




 def      __magic_name__	(      self	:							Optional[Any]      )	->						Any:
       SCREAMING_SNAKE_CASE__     :				Tuple									=InstructBlipProcessor(
           tokenizer=self.get_tokenizer()					,      image_processor=self.get_image_processor()					,      qformer_tokenizer=self.get_qformer_tokenizer()					,      )
       processor.save_pretrained(self.tmpdirname      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=self.get_tokenizer(bos_token='''(BOS)'''					,      eos_token='''(EOS)'''      )
       SCREAMING_SNAKE_CASE__     :				int									=self.get_image_processor(do_normalize=__lowercase					,      padding_value=1.0      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=InstructBlipProcessor.from_pretrained(
           self.tmpdirname					,      bos_token='''(BOS)'''					,      eos_token='''(EOS)'''					,      do_normalize=__lowercase					,      padding_value=1.0      )

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

       self.assertEqual(processor.image_processor.to_json_string()					,      image_processor_add_kwargs.to_json_string()      )
       self.assertIsInstance(processor.image_processor					,      __lowercase      )
       self.assertIsInstance(processor.qformer_tokenizer					,      __lowercase      )




 def      __magic_name__	(      self	:							int      )	->						int:
       SCREAMING_SNAKE_CASE__     :				List[str]									=self.get_image_processor()
       SCREAMING_SNAKE_CASE__     :				str									=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__     :				Dict									=self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE__     :				Optional[int]									=InstructBlipProcessor(
           tokenizer=__lowercase					,      image_processor=__lowercase					,      qformer_tokenizer=__lowercase      )

       SCREAMING_SNAKE_CASE__     :				List[Any]									=self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE__     :				Any									=image_processor(__lowercase					,      return_tensors='''np'''      )
       SCREAMING_SNAKE_CASE__     :				int									=processor(images=__lowercase					,      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      __magic_name__	(      self	:							Dict      )	->						str:
       SCREAMING_SNAKE_CASE__     :				Dict									=self.get_image_processor()
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE__     :				List[Any]									=InstructBlipProcessor(
           tokenizer=__lowercase					,      image_processor=__lowercase					,      qformer_tokenizer=__lowercase      )

       SCREAMING_SNAKE_CASE__     :				Optional[int]									='''lower newer'''

       SCREAMING_SNAKE_CASE__     :				Dict									=processor(text=__lowercase      )

       SCREAMING_SNAKE_CASE__     :				str									=tokenizer(__lowercase					,      return_token_type_ids=__lowercase      )
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=qformer_tokenizer(__lowercase					,      return_token_type_ids=__lowercase      )

       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      __magic_name__	(      self	:							Tuple      )	->						Union[str, Any]:
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=self.get_image_processor()
       SCREAMING_SNAKE_CASE__     :				Dict									=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__     :				Tuple									=self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE__     :				str									=InstructBlipProcessor(
           tokenizer=__lowercase					,      image_processor=__lowercase					,      qformer_tokenizer=__lowercase      )

       SCREAMING_SNAKE_CASE__     :				List[str]									='''lower newer'''
       SCREAMING_SNAKE_CASE__     :				Any									=self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE__     :				str									=processor(text=__lowercase					,      images=__lowercase      )

       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(__lowercase      ):
             processor()




 def      __magic_name__	(      self	:							Any      )	->						Optional[int]:
       SCREAMING_SNAKE_CASE__     :				List[Any]									=self.get_image_processor()
       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__     :				Tuple									=self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE__     :				int									=InstructBlipProcessor(
           tokenizer=__lowercase					,      image_processor=__lowercase					,      qformer_tokenizer=__lowercase      )

       SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       SCREAMING_SNAKE_CASE__     :				Any									=processor.batch_decode(__lowercase      )
       SCREAMING_SNAKE_CASE__     :				Tuple									=tokenizer.batch_decode(__lowercase      )

       self.assertListEqual(__lowercase					,      __lowercase      )




 def      __magic_name__	(      self	:							List[Any]      )	->						List[Any]:
       SCREAMING_SNAKE_CASE__     :				Tuple									=self.get_image_processor()
       SCREAMING_SNAKE_CASE__     :				str									=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__     :				List[Any]									=self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=InstructBlipProcessor(
           tokenizer=__lowercase					,      image_processor=__lowercase					,      qformer_tokenizer=__lowercase      )

       SCREAMING_SNAKE_CASE__     :				Optional[int]									='''lower newer'''
       SCREAMING_SNAKE_CASE__     :				Dict									=self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE__     :				Any									=processor(text=__lowercase					,      images=__lowercase      )

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







'''simple docstring'''
import inspect
import os
import sys
import unittest

import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu






class      __SCREAMING_SNAKE_CASE      (			unittest.TestCase				):




 def      __magic_name__	(      self	:							int      )	->						Tuple:
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=inspect.getfile(accelerate.test_utils      )
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=os.path.sep.join(mod_file.split(os.path.sep      )[:-1] + ['''scripts''', '''test_script.py''']      )
       SCREAMING_SNAKE_CASE__     :				Dict									=os.path.sep.join(inspect.getfile(self.__class__      ).split(os.path.sep      )[:-1]      )




 @require_tpu
 def      __magic_name__	(      self	:							int      )	->						Tuple:
       SCREAMING_SNAKE_CASE__     :				Any									=F"\n            {self.test_dir}/xla_spawn.py\n            --num_cores 8\n            {self.test_file_path}\n        ".split()
       SCREAMING_SNAKE_CASE__     :				List[str]									=[sys.executable] + distributed_args
       execute_subprocess_async(__lowercase					,      env=os.environ.copy()      )