

"""simple docstring"""






import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
 import torch


if is_vision_available():
 from PIL import Image

 from transformers import MgpstrProcessor, ViTImageProcessor
@require_torch
@require_vision
class        _lowercase					(     unittest.TestCase     ):
     _lowerCamelCase     =       ViTImageProcessor if is_vision_available() else None







     @property
     def 	lowerCAmelCase__    (      self       ):
      return self.image_processor_tester.prepare_image_processor_dict()







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      (3, 32, 128)
      __magic_name__     =      tempfile.mkdtemp()

      # fmt: off
      __magic_name__     =      ['''[GO]''', '''[s]''', '''0''', '''1''', '''2''', '''3''', '''4''', '''5''', '''6''', '''7''', '''8''', '''9''', '''a''', '''b''', '''c''', '''d''', '''e''', '''f''', '''g''', '''h''', '''i''', '''j''', '''k''', '''l''', '''m''', '''n''', '''o''', '''p''', '''q''', '''r''', '''s''', '''t''', '''u''', '''v''', '''w''', '''x''', '''y''', '''z''']
      # fmt: on
      __magic_name__     =      dict(zip(UpperCamelCase_ ,						range(len(UpperCamelCase_       )       )       )       )

      __magic_name__     =      os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['''vocab_file''']       )
      with open(self.vocab_file ,						'''w''' ,						encoding='''utf-8'''       ) as fp:
       fp.write(json.dumps(UpperCamelCase_       ) + '''\n'''       )

      __magic_name__     =      {
          '''do_normalize''': False,
          '''do_resize''': True,
          '''image_processor_type''': '''ViTImageProcessor''',
          '''resample''': 3,
          '''size''': {'''height''': 32, '''width''': 128},
      }
      __magic_name__     =      os.path.join(self.tmpdirname ,						UpperCamelCase_       )
      with open(self.image_processor_file ,						'''w''' ,						encoding='''utf-8'''       ) as fp:
       json.dump(UpperCamelCase_ ,						UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self ,						**UpperCamelCase_       ):
      return MgpstrTokenizer.from_pretrained(self.tmpdirname ,						**UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self ,						**UpperCamelCase_       ):
      return ViTImageProcessor.from_pretrained(self.tmpdirname ,						**UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self       ):
      shutil.rmtree(self.tmpdirname       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      np.random.randint(255 ,						size=(3, 30, 400) ,						dtype=np.uinta       )

      __magic_name__     =      Image.fromarray(np.moveaxis(UpperCamelCase_ ,						0 ,						-1       )       )

      return image_input







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_tokenizer()
      __magic_name__     =      self.get_image_processor()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )
      processor.save_pretrained(self.tmpdirname       )
      __magic_name__     =      MgpstrProcessor.from_pretrained(self.tmpdirname ,						use_fast=UpperCamelCase_       )

      self.assertEqual(processor.char_tokenizer.get_vocab() ,						tokenizer.get_vocab()       )
      self.assertIsInstance(processor.char_tokenizer ,						UpperCamelCase_       )

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_tokenizer()
      __magic_name__     =      self.get_image_processor()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )
      processor.save_pretrained(self.tmpdirname       )

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

      __magic_name__     =      MgpstrProcessor.from_pretrained(
          self.tmpdirname ,						bos_token='''(BOS)''' ,						eos_token='''(EOS)''' ,						do_normalize=UpperCamelCase_ ,						padding_value=1.0       )

      self.assertEqual(processor.char_tokenizer.get_vocab() ,						tokenizer_add_kwargs.get_vocab()       )
      self.assertIsInstance(processor.char_tokenizer ,						UpperCamelCase_       )

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      self.prepare_image_inputs()

      __magic_name__     =      image_processor(UpperCamelCase_ ,						return_tensors='''np'''       )
      __magic_name__     =      processor(images=UpperCamelCase_ ,						return_tensors='''np'''       )

      for key in input_image_proc.keys():
       self.assertAlmostEqual(input_image_proc[key].sum() ,						input_processor[key].sum() ,						delta=1E-2       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      '''test'''

      __magic_name__     =      processor(text=UpperCamelCase_       )

      __magic_name__     =      tokenizer(UpperCamelCase_       )
      for key in encoded_tok.keys():
       self.assertListEqual(encoded_tok[key] ,						encoded_processor[key]       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      '''test'''
      __magic_name__     =      self.prepare_image_inputs()

      __magic_name__     =      processor(text=UpperCamelCase_ ,						images=UpperCamelCase_       )

      self.assertListEqual(list(inputs.keys()       ) ,						['''pixel_values''', '''labels''']       )

      # test if it raises when no input is passed
      with pytest.raises(UpperCamelCase_       ):
       processor()







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

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

      __magic_name__     =      processor.char_decode(UpperCamelCase_       )
      __magic_name__     =      tokenizer.batch_decode(UpperCamelCase_       )
      __magic_name__     =      [seq.replace(''' ''' ,						''''''       ) for seq in decoded_tok]

      self.assertListEqual(UpperCamelCase_ ,						UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      None
      __magic_name__     =      self.prepare_image_inputs()

      __magic_name__     =      processor(text=UpperCamelCase_ ,						images=UpperCamelCase_       )

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







     def 	lowerCAmelCase__    (      self       ):
      __magic_name__     =      self.get_image_processor()
      __magic_name__     =      self.get_tokenizer()

      __magic_name__     =      MgpstrProcessor(tokenizer=UpperCamelCase_ ,						image_processor=UpperCamelCase_       )

      __magic_name__     =      torch.randn(1 ,						27 ,						38       )
      __magic_name__     =      torch.randn(1 ,						27 ,						5_0257       )
      __magic_name__     =      torch.randn(1 ,						27 ,						3_0522       )

      __magic_name__     =      processor.batch_decode([char_input, bpe_input, wp_input]       )

      self.assertListEqual(list(results.keys()       ) ,						['''generated_text''', '''scores''', '''char_preds''', '''bpe_preds''', '''wp_preds''']       )





"""simple docstring"""






class        _lowercase					:







     def __init__(      self ,						UpperCamelCase_       ):
      __magic_name__     =      size
      __magic_name__     =      [0] * size
      __magic_name__     =      [0] * size







     @staticmethod
     def 	lowerCAmelCase__    (      UpperCamelCase_       ):
      return index | (index + 1)







     @staticmethod
     def 	lowerCAmelCase__    (      UpperCamelCase_       ):
      return (index & (index + 1)) - 1







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_ ,						UpperCamelCase_       ):
      __magic_name__     =      value
      while index < self.size:
       __magic_name__     =      self.get_prev(UpperCamelCase_       ) + 1
       if current_left_border == index:
        __magic_name__     =      value
       else:
        __magic_name__     =      max(UpperCamelCase_ ,						UpperCamelCase_ ,						UpperCamelCase_       )
       __magic_name__     =      self.get_next(UpperCamelCase_       )







     def 	lowerCAmelCase__    (      self ,						UpperCamelCase_ ,						UpperCamelCase_       ):
      right -= 1  # Because of right is exclusive
      __magic_name__     =      0
      while left <= right:
       __magic_name__     =      self.get_prev(UpperCamelCase_       )
       if left <= current_left:
        __magic_name__     =      max(UpperCamelCase_ ,						self.tree[right]       )
        __magic_name__     =      current_left
       else:
        __magic_name__     =      max(UpperCamelCase_ ,						self.arr[right]       )
        right -= 1
      return result


if __name__ == "__main__":
 import doctest

 doctest.testmod()

