




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 	lowerCamelCase_							(				unittest.TestCase ):


 '''simple docstring'''







 lowercase_       =   ViTImageProcessor if is_vision_available() else None



 @property
 def 				lowerCAmelCase_  (							self  :		List[Any]						):
       return self.image_processor_tester.prepare_image_processor_dict()



 def 				lowerCAmelCase_  (							self  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      (3, 32, 128)
       SCREAMING_SNAKE_CASE_     						=      tempfile.mkdtemp()

       # fmt: off
       SCREAMING_SNAKE_CASE_     						=      ['[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
       SCREAMING_SNAKE_CASE_     						=      dict(zip(_lowerCAmelCase    ,    range(len(_lowerCAmelCase						)						)						)						)

       SCREAMING_SNAKE_CASE_     						=      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(_lowerCAmelCase						) + '\n'						)

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



 def 				lowerCAmelCase_  (							self  :		Tuple    ,    **_lowerCAmelCase  :		Union[str, Any]						):
       return MgpstrTokenizer.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[Any]    ,    **_lowerCAmelCase  :		Tuple						):
       return ViTImageProcessor.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       shutil.rmtree(self.tmpdirname						)



 def 				lowerCAmelCase_  (							self  :		Tuple						):
       SCREAMING_SNAKE_CASE_     						=      np.random.randint(255    ,    size=(3, 30, 400)    ,    dtype=np.uinta						)

       SCREAMING_SNAKE_CASE_     						=      Image.fromarray(np.moveaxis(_lowerCAmelCase    ,    0    ,    -1						)						)

       return image_input



 def 				lowerCAmelCase_  (							self  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)
       processor.save_pretrained(self.tmpdirname						)
       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor.from_pretrained(self.tmpdirname    ,    use_fast=_lowerCAmelCase						)

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

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



 def 				lowerCAmelCase_  (							self  :		List[Any]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)
       processor.save_pretrained(self.tmpdirname						)

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

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

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

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



 def 				lowerCAmelCase_  (							self  :		str						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE_     						=      image_processor(_lowerCAmelCase    ,    return_tensors='np'						)
       SCREAMING_SNAKE_CASE_     						=      processor(images=_lowerCAmelCase    ,    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  :		Optional[int]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      'test'

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase						)

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



 def 				lowerCAmelCase_  (							self  :		int						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

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

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase    ,    images=_lowerCAmelCase						)

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

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



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

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

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

       self.assertListEqual(_lowerCAmelCase    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      None
       SCREAMING_SNAKE_CASE_     						=      self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase    ,    images=_lowerCAmelCase						)

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




 def 				lowerCAmelCase_  (							self  :		List[str]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      MgpstrProcessor(tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      torch.randn(1    ,    27    ,    38						)
       SCREAMING_SNAKE_CASE_     						=      torch.randn(1    ,    27    ,    50_257						)
       SCREAMING_SNAKE_CASE_     						=      torch.randn(1    ,    27    ,    30_522						)

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

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





def  UpperCAmelCase_							(				__UpperCAmelCase						:     str							) ->			list:
      return [
          txt[:a] + txt[a].upper() + txt[a + 1 :]
          for a in range(len(__UpperCAmelCase							)							)
          if txt[a].isalpha()
      ]


if __name__ == "__main__":
   __import__('doctest').testmod()