





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 				A_				(      unittest.TestCase	):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_      : Optional[Any]      =  ViTImageProcessor if is_vision_available() else None







       @property
       def    __UpperCAmelCase (    self	:	List[str]  )						->					Optional[Any]:
         return self.image_processor_tester.prepare_image_processor_dict()







       def    __UpperCAmelCase (    self	:	Tuple  )						->					Tuple:
         _lowercase							= (3, 32, 128)
         _lowercase							= tempfile.mkdtemp()

         # fmt: off
         _lowercase							= ['[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
         _lowercase							= dict(zip(__A						,range(len(__A  )  )  )  )

         _lowercase							= 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(__A  ) + '\n'  )

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







       def    __UpperCAmelCase (    self	:	Optional[int]						,**__A	:	Dict  )						->					List[Any]:
         return MgpstrTokenizer.from_pretrained(self.tmpdirname						,**__A  )







       def    __UpperCAmelCase (    self	:	List[str]						,**__A	:	List[Any]  )						->					int:
         return ViTImageProcessor.from_pretrained(self.tmpdirname						,**__A  )







       def    __UpperCAmelCase (    self	:	Any  )						->					Union[str, Any]:
         shutil.rmtree(self.tmpdirname  )







       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					int:
         _lowercase							= np.random.randint(255						,size=(3, 30, 400)						,dtype=np.uinta  )

         _lowercase							= Image.fromarray(np.moveaxis(__A						,0						,-1  )  )

         return image_input







       def    __UpperCAmelCase (    self	:	List[Any]  )						->					Dict:
         _lowercase							= self.get_tokenizer()
         _lowercase							= self.get_image_processor()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )
         processor.save_pretrained(self.tmpdirname  )
         _lowercase							= MgpstrProcessor.from_pretrained(self.tmpdirname						,use_fast=__A  )

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

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







       def    __UpperCAmelCase (    self	:	int  )						->					Optional[Any]:
         _lowercase							= self.get_tokenizer()
         _lowercase							= self.get_image_processor()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )
         processor.save_pretrained(self.tmpdirname  )

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

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

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

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







       def    __UpperCAmelCase (    self	:	int  )						->					str:
         _lowercase							= self.get_image_processor()
         _lowercase							= self.get_tokenizer()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )

         _lowercase							= self.prepare_image_inputs()

         _lowercase							= image_processor(__A						,return_tensors='np'  )
         _lowercase							= processor(images=__A						,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    __UpperCAmelCase (    self	:	List[str]  )						->					Tuple:
         _lowercase							= self.get_image_processor()
         _lowercase							= self.get_tokenizer()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )

         _lowercase							= 'test'

         _lowercase							= processor(text=__A  )

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







       def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					str:
         _lowercase							= self.get_image_processor()
         _lowercase							= self.get_tokenizer()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )

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

         _lowercase							= processor(text=__A						,images=__A  )

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

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







       def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					Union[str, Any]:
         _lowercase							= self.get_image_processor()
         _lowercase							= self.get_tokenizer()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )

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

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

         self.assertListEqual(__A						,__A  )







       def    __UpperCAmelCase (    self	:	Any  )						->					Optional[Any]:
         _lowercase							= self.get_image_processor()
         _lowercase							= self.get_tokenizer()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )

         _lowercase							= None
         _lowercase							= self.prepare_image_inputs()

         _lowercase							= processor(text=__A						,images=__A  )

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







       def    __UpperCAmelCase (    self	:	Tuple  )						->					List[str]:
         _lowercase							= self.get_image_processor()
         _lowercase							= self.get_tokenizer()

         _lowercase							= MgpstrProcessor(tokenizer=__A						,image_processor=__A  )

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

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

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






def 							SCREAMING_SNAKE_CASE__       (  snake_case__  :str			,							snake_case__  :int     )      ->						list[str]:
  return [sentence[i : i + ngram_size] for i in range(len(snake_case__     ) - ngram_size + 1     )]


if __name__ == "__main__":
      from doctest import testmod

      testmod()