


'''simple docstring'''

import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

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


if is_vision_available():
 from PIL import Image

 from transformers import AlignProcessor, EfficientNetImageProcessor
@require_vision
class   __lowerCAmelCase						(unittest.TestCase     ):





      '''simple docstring'''






      def       UpperCamelCase__		(self    :    List[Any] ):

             '''simple docstring'''







             lowercase__      			= tempfile.mkdtemp()

             lowercase__      			= [
                 '''[UNK]''',
                 '''[CLS]''',
                 '''[SEP]''',
                 '''[PAD]''',
                 '''[MASK]''',
                 '''want''',
                 '''##want''',
                 '''##ed''',
                 '''wa''',
                 '''un''',
                 '''runn''',
                 '''##ing''',
                 ''',''',
                 '''low''',
                 '''lowest''',
             ]
             lowercase__      			= 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] ) )

             lowercase__      			= {
                 '''do_resize''': True,
                 '''size''': 20,
                 '''do_center_crop''': True,
                 '''crop_size''': 18,
                 '''do_normalize''': True,
                 '''image_mean''': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
                 '''image_std''': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
             }
             lowercase__      			= 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    :    Tuple   ,						**UpperCamelCase    :    Optional[int] ):

             '''simple docstring'''







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



      def       UpperCamelCase__		(self    :    Tuple   ,						**UpperCamelCase    :    List[str] ):

             '''simple docstring'''







             return BertTokenizerFast.from_pretrained(self.tmpdirname   ,						**UpperCamelCase )



      def       UpperCamelCase__		(self    :    List[Any]   ,						**UpperCamelCase    :    Optional[int] ):

             '''simple docstring'''







             return EfficientNetImageProcessor.from_pretrained(self.tmpdirname   ,						**UpperCamelCase )



      def       UpperCamelCase__		(self    :    str ):

             '''simple docstring'''







             shutil.rmtree(self.tmpdirname )



      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             lowercase__      			= [np.random.randint(255   ,						size=(3, 30, 400)   ,						dtype=np.uinta )]
             lowercase__      			= [Image.fromarray(np.moveaxis(UpperCamelCase   ,						0   ,						-1 ) ) for x in image_inputs]
             return image_inputs



      def       UpperCamelCase__		(self    :    Union[str, Any] ):

             '''simple docstring'''







             lowercase__      			= self.get_tokenizer()
             lowercase__      			= self.get_rust_tokenizer()
             lowercase__      			= self.get_image_processor()

             lowercase__      			= AlignProcessor(tokenizer=UpperCamelCase   ,						image_processor=UpperCamelCase )
             processor_slow.save_pretrained(self.tmpdirname )
             lowercase__      			= AlignProcessor.from_pretrained(self.tmpdirname   ,						use_fast=UpperCamelCase )

             lowercase__      			= AlignProcessor(tokenizer=UpperCamelCase   ,						image_processor=UpperCamelCase )
             processor_fast.save_pretrained(self.tmpdirname )
             lowercase__      			= AlignProcessor.from_pretrained(self.tmpdirname )

             self.assertEqual(processor_slow.tokenizer.get_vocab()   ,						tokenizer_slow.get_vocab() )
             self.assertEqual(processor_fast.tokenizer.get_vocab()   ,						tokenizer_fast.get_vocab() )
             self.assertEqual(tokenizer_slow.get_vocab()   ,						tokenizer_fast.get_vocab() )
             self.assertIsInstance(processor_slow.tokenizer   ,						UpperCamelCase )
             self.assertIsInstance(processor_fast.tokenizer   ,						UpperCamelCase )

             self.assertEqual(processor_slow.image_processor.to_json_string()   ,						image_processor.to_json_string() )
             self.assertEqual(processor_fast.image_processor.to_json_string()   ,						image_processor.to_json_string() )
             self.assertIsInstance(processor_slow.image_processor   ,						UpperCamelCase )
             self.assertIsInstance(processor_fast.image_processor   ,						UpperCamelCase )



      def       UpperCamelCase__		(self    :    int ):

             '''simple docstring'''







             lowercase__      			= AlignProcessor(tokenizer=self.get_tokenizer()   ,						image_processor=self.get_image_processor() )
             processor.save_pretrained(self.tmpdirname )

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

             lowercase__      			= AlignProcessor.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   ,						UpperCamelCase )

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



      def       UpperCamelCase__		(self    :    List[str] ):

             '''simple docstring'''







             lowercase__      			= self.get_image_processor()
             lowercase__      			= self.get_tokenizer()

             lowercase__      			= AlignProcessor(tokenizer=UpperCamelCase   ,						image_processor=UpperCamelCase )

             lowercase__      			= self.prepare_image_inputs()

             lowercase__      			= image_processor(UpperCamelCase   ,						return_tensors='''np''' )
             lowercase__      			= 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       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







             lowercase__      			= self.get_image_processor()
             lowercase__      			= self.get_tokenizer()

             lowercase__      			= AlignProcessor(tokenizer=UpperCamelCase   ,						image_processor=UpperCamelCase )

             lowercase__      			= '''lower newer'''

             lowercase__      			= processor(text=UpperCamelCase )

             lowercase__      			= tokenizer(UpperCamelCase   ,						padding='''max_length'''   ,						max_length=64 )

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



      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







             lowercase__      			= self.get_image_processor()
             lowercase__      			= self.get_tokenizer()

             lowercase__      			= AlignProcessor(tokenizer=UpperCamelCase   ,						image_processor=UpperCamelCase )

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

             lowercase__      			= 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 pytest.raises(UpperCamelCase ):
                    processor()



      def       UpperCamelCase__		(self    :    Tuple ):

             '''simple docstring'''







             lowercase__      			= self.get_image_processor()
             lowercase__      			= self.get_tokenizer()

             lowercase__      			= AlignProcessor(tokenizer=UpperCamelCase   ,						image_processor=UpperCamelCase )

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

             lowercase__      			= processor.batch_decode(UpperCamelCase )
             lowercase__      			= tokenizer.batch_decode(UpperCamelCase )

             self.assertListEqual(UpperCamelCase   ,						UpperCamelCase )






      def       UpperCamelCase__		(self    :    Optional[Any] ):

             '''simple docstring'''







             lowercase__      			= self.get_image_processor()
             lowercase__      			= self.get_tokenizer()

             lowercase__      			= AlignProcessor(tokenizer=UpperCamelCase   ,						image_processor=UpperCamelCase )

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

             lowercase__      			= processor(text=UpperCamelCase   ,						images=UpperCamelCase )

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








'''simple docstring'''

# Lint as: python3
import itertools
import os
import re


lowerCamelCase							:   Any  						=	re.compile(R'([A-Z]+)([A-Z][a-z])')
lowerCamelCase							:   str  						=	re.compile(R'([a-z\d])([A-Z])')

lowerCamelCase							:   Optional[int]  						=	re.compile(R'(?<!_)_(?!_)')
lowerCamelCase							:   List[Any]  						=	re.compile(R'(_{2,})')

lowerCamelCase							:   str  						=	R'^\w+(\.\w+)*$'

lowerCamelCase							:   Dict  						=	R'<>:/\|?*'

def _SCREAMING_SNAKE_CASE      (A       )       ->       Any:






       """simple docstring"""







       lowercase__      			= _uppercase_uppercase_re.sub(R'''\1_\2'''  , A       )
       lowercase__      			= _lowercase_uppercase_re.sub(R'''\1_\2'''  , A       )
       return name.lower()

def _SCREAMING_SNAKE_CASE      (A       )       ->       Tuple:






       """simple docstring"""







       lowercase__      			= _single_underscore_re.split(A       )
       lowercase__      			= [_multiple_underscores_re.split(A       ) for n in name]
       return "".join(n.capitalize() for n in itertools.chain.from_iterable(A       ) if n != ''''''       )

def _SCREAMING_SNAKE_CASE      (A       )       ->       Tuple:






       """simple docstring"""







       if os.path.basename(A       ) != name:
              raise ValueError(f"Should be a dataset name, not a path: {name}"       )
       return camelcase_to_snakecase(A       )

def _SCREAMING_SNAKE_CASE      (A  , A       )       ->       Optional[Any]:






       """simple docstring"""







       if os.path.basename(A       ) != name:
              raise ValueError(f"Should be a dataset name, not a path: {name}"       )
       if not re.match(_split_re  , A       ):
              raise ValueError(f"Split name should match '{_split_re}'' but got '{split}'."       )
       return f"{filename_prefix_for_name(A       )}-{split}"

def _SCREAMING_SNAKE_CASE      (A  , A  , A  , A=None       )       ->       List[str]:






       """simple docstring"""







       lowercase__      			= filename_prefix_for_split(A  , A       )
       if filetype_suffix:
              prefix += f".{filetype_suffix}"
       lowercase__      			= os.path.join(A  , A       )
       return f"{filepath}*"

def _SCREAMING_SNAKE_CASE      (A  , A  , A  , A=None  , A=None       )       ->       Optional[Any]:






       """simple docstring"""







       lowercase__      			= filename_prefix_for_split(A  , A       )
       lowercase__      			= os.path.join(A  , A       )

       if shard_lengths:
              lowercase__      			= len(A       )
              lowercase__      			= [f"{prefix}-{shard_id:05d}-of-{num_shards:05d}" for shard_id in range(A       )]
              if filetype_suffix:
                     lowercase__      			= [filename + f".{filetype_suffix}" for filename in filenames]
              return filenames
       else:
              lowercase__      			= prefix
              if filetype_suffix:
                     filename += f".{filetype_suffix}"
              return [filename]




