


'''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   UpperCAmelCase_    (unittest.TestCase    ):





    """simple docstring"""






    def  lowercase_							(				self      )							->	List[Any]:
         __lowerCamelCase  :      Any														=						tempfile.mkdtemp()

         __lowerCamelCase  :      Dict														=						BlipImageProcessor()
         __lowerCamelCase  :      Tuple														=						GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model'      )
         __lowerCamelCase  :      List[Any]														=						BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert'      )

         __lowerCamelCase  :      Any														=						InstructBlipProcessor(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )

         processor.save_pretrained(self.tmpdirname      )







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







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Tuple:
         return AutoProcessor.from_pretrained(self.tmpdirname     ,	**SCREAMING_SNAKE_CASE_      ).image_processor







    def  lowercase_							(				self     ,	**SCREAMING_SNAKE_CASE_      )							->	Dict:
         return AutoProcessor.from_pretrained(self.tmpdirname     ,	**SCREAMING_SNAKE_CASE_      ).qformer_tokenizer







    def  lowercase_							(				self      )							->	List[Any]:
         shutil.rmtree(self.tmpdirname      )







    def  lowercase_							(				self      )							->	Union[str, Any]:
         __lowerCamelCase  :      Optional[Any]														=						[np.random.randint(2_55     ,	size=(3, 30, 4_00)     ,	dtype=np.uinta      )]

         __lowerCamelCase  :      Union[str, Any]														=						[Image.fromarray(np.moveaxis(SCREAMING_SNAKE_CASE_     ,	0     ,	-1      )      ) for x in image_inputs]

         return image_inputs







    def  lowercase_							(				self      )							->	str:
         __lowerCamelCase  :      int														=						InstructBlipProcessor(
             tokenizer=self.get_tokenizer()     ,	image_processor=self.get_image_processor()     ,	qformer_tokenizer=self.get_qformer_tokenizer()     ,	)
         processor.save_pretrained(self.tmpdirname      )

         __lowerCamelCase  :      Optional[int]														=						self.get_tokenizer(bos_token='(BOS)'     ,	eos_token='(EOS)'      )
         __lowerCamelCase  :      Optional[Any]														=						self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_     ,	padding_value=1.0      )

         __lowerCamelCase  :      Any														=						InstructBlipProcessor.from_pretrained(
             self.tmpdirname     ,	bos_token='(BOS)'     ,	eos_token='(EOS)'     ,	do_normalize=SCREAMING_SNAKE_CASE_     ,	padding_value=1.0      )

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

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







    def  lowercase_							(				self      )							->	Union[str, Any]:
         __lowerCamelCase  :      int														=						self.get_image_processor()
         __lowerCamelCase  :      Optional[int]														=						self.get_tokenizer()
         __lowerCamelCase  :      Any														=						self.get_qformer_tokenizer()

         __lowerCamelCase  :      Optional[int]														=						InstructBlipProcessor(
             tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_     ,	qformer_tokenizer=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Dict														=						self.prepare_image_inputs()

         __lowerCamelCase  :      Optional[int]														=						image_processor(SCREAMING_SNAKE_CASE_     ,	return_tensors='np'      )
         __lowerCamelCase  :      Optional[Any]														=						processor(images=SCREAMING_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      )							->	int:
         __lowerCamelCase  :      List[str]														=						self.get_image_processor()
         __lowerCamelCase  :      Optional[Any]														=						self.get_tokenizer()
         __lowerCamelCase  :      List[Any]														=						self.get_qformer_tokenizer()

         __lowerCamelCase  :      Union[str, Any]														=						InstructBlipProcessor(
             tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_     ,	qformer_tokenizer=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[str]														=						'lower newer'

         __lowerCamelCase  :      str														=						processor(text=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Any														=						tokenizer(SCREAMING_SNAKE_CASE_     ,	return_token_type_ids=SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						qformer_tokenizer(SCREAMING_SNAKE_CASE_     ,	return_token_type_ids=SCREAMING_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  lowercase_							(				self      )							->	List[str]:
         __lowerCamelCase  :      Dict														=						self.get_image_processor()
         __lowerCamelCase  :      Optional[Any]														=						self.get_tokenizer()
         __lowerCamelCase  :      int														=						self.get_qformer_tokenizer()

         __lowerCamelCase  :      Optional[int]														=						InstructBlipProcessor(
             tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_     ,	qformer_tokenizer=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      Any														=						'lower newer'
         __lowerCamelCase  :      Dict														=						self.prepare_image_inputs()

         __lowerCamelCase  :      List[Any]														=						processor(text=SCREAMING_SNAKE_CASE_     ,	images=SCREAMING_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(SCREAMING_SNAKE_CASE_      ):
              processor()







    def  lowercase_							(				self      )							->	Optional[Any]:
         __lowerCamelCase  :      Tuple														=						self.get_image_processor()
         __lowerCamelCase  :      int														=						self.get_tokenizer()
         __lowerCamelCase  :      List[str]														=						self.get_qformer_tokenizer()

         __lowerCamelCase  :      str														=						InstructBlipProcessor(
             tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_     ,	qformer_tokenizer=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[str]														=						[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         __lowerCamelCase  :      Any														=						processor.batch_decode(SCREAMING_SNAKE_CASE_      )
         __lowerCamelCase  :      Union[str, Any]														=						tokenizer.batch_decode(SCREAMING_SNAKE_CASE_      )

         self.assertListEqual(SCREAMING_SNAKE_CASE_     ,	SCREAMING_SNAKE_CASE_      )







    def  lowercase_							(				self      )							->	str:
         __lowerCamelCase  :      Union[str, Any]														=						self.get_image_processor()
         __lowerCamelCase  :      str														=						self.get_tokenizer()
         __lowerCamelCase  :      int														=						self.get_qformer_tokenizer()

         __lowerCamelCase  :      Union[str, Any]														=						InstructBlipProcessor(
             tokenizer=SCREAMING_SNAKE_CASE_     ,	image_processor=SCREAMING_SNAKE_CASE_     ,	qformer_tokenizer=SCREAMING_SNAKE_CASE_      )

         __lowerCamelCase  :      List[Any]														=						'lower newer'
         __lowerCamelCase  :      Optional[int]														=						self.prepare_image_inputs()

         __lowerCamelCase  :      str														=						processor(text=SCREAMING_SNAKE_CASE_     ,	images=SCREAMING_SNAKE_CASE_      )

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










'''simple docstring'''



# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# this script dumps information about the environment

import os
import platform
import sys


A__						:   List[str]				=    """3"""

print("""Python version:""", sys.version)

print("""OS platform:""", platform.platform())
print("""OS architecture:""", platform.machine())

try:
      import torch

      print("""Torch version:""", torch.__version__)
      print("""Cuda available:""", torch.cuda.is_available())
      print("""Cuda version:""", torch.version.cuda)
      print("""CuDNN version:""", torch.backends.cudnn.version())
      print("""Number of GPUs available:""", torch.cuda.device_count())
except ImportError:
      print("""Torch version:""", None)

try:
      import transformers

      print("""transformers version:""", transformers.__version__)
except ImportError:
      print("""transformers version:""", None)






