
"""simple docstring"""

import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
      from PIL import Image

      from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor

@require_tokenizers
@require_vision
class __lowerCAmelCase	(   unittest.TestCase    ):





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= tempfile.mkdtemp()

      # fmt: off
      __UpperCamelCase       						= ['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing', ',', 'low', 'lowest']
      # fmt: on
      __UpperCamelCase       						= os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES['vocab_file']   )
      with open(self.vocab_file			,  'w'			,  encoding='utf-8'   ) as vocab_writer:
       vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]   )   )

      __UpperCamelCase       						= {
          'do_resize': True,
          'size': {'height': 18, 'width': 18},
          'do_normalize': True,
          'image_mean': [0.5, 0.5, 0.5],
          'image_std': [0.5, 0.5, 0.5],
      }
      __UpperCamelCase       						= os.path.join(self.tmpdirname			,  __UpperCAmelCase   )
      with open(self.image_processor_file			,  'w'			,  encoding='utf-8'   ) as fp:
       json.dump(__UpperCAmelCase			,  __UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  **__UpperCAmelCase   ):

      '''simple docstring'''




      return BertTokenizer.from_pretrained(self.tmpdirname			,  **__UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  **__UpperCAmelCase   ):

      '''simple docstring'''




      return ViTImageProcessor.from_pretrained(self.tmpdirname			,  **__UpperCAmelCase   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      shutil.rmtree(self.tmpdirname   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= [np.random.randint(255			,  size=(3, 30, 400)			,  dtype=np.uinta   )]

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

      return image_inputs





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.get_tokenizer()
      __UpperCamelCase       						= self.get_image_processor()

      __UpperCamelCase       						= VisionTextDualEncoderProcessor(tokenizer=__UpperCAmelCase			,  image_processor=__UpperCAmelCase   )

      processor.save_pretrained(self.tmpdirname   )
      __UpperCamelCase       						= VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname   )

      self.assertEqual(processor.tokenizer.get_vocab()			,  tokenizer.get_vocab()   )
      self.assertIsInstance(processor.tokenizer			,  (BertTokenizer, BertTokenizerFast)   )

      self.assertEqual(processor.image_processor.to_json_string()			,  image_processor.to_json_string()   )
      self.assertIsInstance(processor.image_processor			,  __UpperCAmelCase   )





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= VisionTextDualEncoderProcessor(
          tokenizer=self.get_tokenizer()			,  image_processor=self.get_image_processor()   )
      processor.save_pretrained(self.tmpdirname   )

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

      __UpperCamelCase       						= VisionTextDualEncoderProcessor.from_pretrained(
          self.tmpdirname			,  bos_token='(BOS)'			,  eos_token='(EOS)'			,  do_normalize=__UpperCAmelCase			,  padding_value=1.0   )

      self.assertEqual(processor.tokenizer.get_vocab()			,  tokenizer_add_kwargs.get_vocab()   )
      self.assertIsInstance(processor.tokenizer			,  (BertTokenizer, BertTokenizerFast)   )

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





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.get_image_processor()
      __UpperCamelCase       						= self.get_tokenizer()

      __UpperCamelCase       						= VisionTextDualEncoderProcessor(tokenizer=__UpperCAmelCase			,  image_processor=__UpperCAmelCase   )

      __UpperCamelCase       						= self.prepare_image_inputs()

      __UpperCamelCase       						= image_processor(__UpperCAmelCase			,  return_tensors='np'   )
      __UpperCamelCase       						= processor(images=__UpperCAmelCase			,  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 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.get_image_processor()
      __UpperCamelCase       						= self.get_tokenizer()

      __UpperCamelCase       						= VisionTextDualEncoderProcessor(tokenizer=__UpperCAmelCase			,  image_processor=__UpperCAmelCase   )

      __UpperCamelCase       						= 'lower newer'

      __UpperCamelCase       						= processor(text=__UpperCAmelCase   )

      __UpperCamelCase       						= tokenizer(__UpperCAmelCase   )

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





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.get_image_processor()
      __UpperCamelCase       						= self.get_tokenizer()

      __UpperCamelCase       						= VisionTextDualEncoderProcessor(tokenizer=__UpperCAmelCase			,  image_processor=__UpperCAmelCase   )

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

      __UpperCamelCase       						= processor(text=__UpperCAmelCase			,  images=__UpperCAmelCase   )

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

      # test if it raises when no input is passed
      with self.assertRaises(__UpperCAmelCase   ):
       processor()





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.get_image_processor()
      __UpperCamelCase       						= self.get_tokenizer()

      __UpperCamelCase       						= VisionTextDualEncoderProcessor(tokenizer=__UpperCAmelCase			,  image_processor=__UpperCAmelCase   )

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

      __UpperCamelCase       						= processor.batch_decode(__UpperCAmelCase   )
      __UpperCamelCase       						= tokenizer.batch_decode(__UpperCAmelCase   )

      self.assertListEqual(__UpperCAmelCase			,  __UpperCAmelCase   )







     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.get_image_processor()
      __UpperCamelCase       						= self.get_tokenizer()

      __UpperCamelCase       						= VisionTextDualEncoderProcessor(tokenizer=__UpperCAmelCase			,  image_processor=__UpperCAmelCase   )

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

      __UpperCamelCase       						= processor(text=__UpperCAmelCase			,  images=__UpperCAmelCase   )

      self.assertListEqual(list(inputs.keys()   )			,  processor.model_input_names   )





"""simple docstring"""

from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase			:       List[str]									=				{
    "configuration_autoformer": [
        "AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "AutoformerConfig",
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      UpperCamelCase			:       Dict									=				[
          "AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "AutoformerForPrediction",
          "AutoformerModel",
          "AutoformerPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_autoformer import (
          AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
          AutoformerConfig,
      )

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_autoformer import (
                AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                AutoformerForPrediction,
                AutoformerModel,
                AutoformerPreTrainedModel,
            )

else:
      import sys

      UpperCamelCase			:       int									=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



