





'''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        UpperCAmelCase     (	unittest.TestCase    ):
 def 					UpperCAmelCase_							(    self				:Optional[Any]							)->							List[str]:
     A__    =      tempfile.mkdtemp()

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

     A__    =      {
         "do_resize": True,
         "size": 20,
         "do_center_crop": True,
         "crop_size": 18,
         "do_normalize": True,
         "image_mean": [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
         "image_std": [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
     }
     A__    =      os.path.join(self.tmpdirname						,	lowercase_							)
     with open(self.image_processor_file						,	"w"						,	encoding="utf-8"							) as fp:
         json.dump(lowercase_						,	lowercase_							)
 def 					UpperCAmelCase_							(    self				:Optional[int]						,	**lowercase_				:Tuple							)->							Optional[Any]:
     return BertTokenizer.from_pretrained(self.tmpdirname						,	**lowercase_							)
 def 					UpperCAmelCase_							(    self				:int						,	**lowercase_				:Tuple							)->							Union[str, Any]:
     return BertTokenizerFast.from_pretrained(self.tmpdirname						,	**lowercase_							)
 def 					UpperCAmelCase_							(    self				:Any						,	**lowercase_				:Union[str, Any]							)->							List[Any]:
     return EfficientNetImageProcessor.from_pretrained(self.tmpdirname						,	**lowercase_							)
 def 					UpperCAmelCase_							(    self				:Optional[int]							)->							List[str]:
     shutil.rmtree(self.tmpdirname							)
 def 					UpperCAmelCase_							(    self				:Dict							)->							Dict:
     A__    =      [np.random.randint(2_55						,	size=(3, 30, 4_00)						,	dtype=np.uinta							)]
     A__    =      [Image.fromarray(np.moveaxis(lowercase_						,	0						,	-1							)							) for x in image_inputs]
     return image_inputs
 def 					UpperCAmelCase_							(    self				:Union[str, Any]							)->							str:
     A__    =      self.get_tokenizer()
     A__    =      self.get_rust_tokenizer()
     A__    =      self.get_image_processor()

     A__    =      AlignProcessor(tokenizer=lowercase_						,	image_processor=lowercase_							)
     processor_slow.save_pretrained(self.tmpdirname							)
     A__    =      AlignProcessor.from_pretrained(self.tmpdirname						,	use_fast=lowercase_							)

     A__    =      AlignProcessor(tokenizer=lowercase_						,	image_processor=lowercase_							)
     processor_fast.save_pretrained(self.tmpdirname							)
     A__    =      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						,	lowercase_							)
     self.assertIsInstance(processor_fast.tokenizer						,	lowercase_							)

     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						,	lowercase_							)
     self.assertIsInstance(processor_fast.image_processor						,	lowercase_							)
 def 					UpperCAmelCase_							(    self				:Any							)->							int:
     A__    =      AlignProcessor(tokenizer=self.get_tokenizer()						,	image_processor=self.get_image_processor()							)
     processor.save_pretrained(self.tmpdirname							)

     A__    =      self.get_tokenizer(bos_token="(BOS)"						,	eos_token="(EOS)"							)
     A__    =      self.get_image_processor(do_normalize=lowercase_						,	padding_value=1.0							)

     A__    =      AlignProcessor.from_pretrained(
         self.tmpdirname						,	bos_token="(BOS)"						,	eos_token="(EOS)"						,	do_normalize=lowercase_						,	padding_value=1.0							)

     self.assertEqual(processor.tokenizer.get_vocab()						,	tokenizer_add_kwargs.get_vocab()							)
     self.assertIsInstance(processor.tokenizer						,	lowercase_							)

     self.assertEqual(processor.image_processor.to_json_string()						,	image_processor_add_kwargs.to_json_string()							)
     self.assertIsInstance(processor.image_processor						,	lowercase_							)
 def 					UpperCAmelCase_							(    self				:Union[str, Any]							)->							Optional[int]:
     A__    =      self.get_image_processor()
     A__    =      self.get_tokenizer()

     A__    =      AlignProcessor(tokenizer=lowercase_						,	image_processor=lowercase_							)

     A__    =      self.prepare_image_inputs()

     A__    =      image_processor(lowercase_						,	return_tensors="np"							)
     A__    =      processor(images=lowercase_						,	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				:Any							)->							Optional[int]:
     A__    =      self.get_image_processor()
     A__    =      self.get_tokenizer()

     A__    =      AlignProcessor(tokenizer=lowercase_						,	image_processor=lowercase_							)

     A__    =      "lower newer"

     A__    =      processor(text=lowercase_							)

     A__    =      tokenizer(lowercase_						,	padding="max_length"						,	max_length=64							)

     for key in encoded_tok.keys():
         self.assertListEqual(encoded_tok[key]						,	encoded_processor[key]							)
 def 					UpperCAmelCase_							(    self				:Tuple							)->							List[Any]:
     A__    =      self.get_image_processor()
     A__    =      self.get_tokenizer()

     A__    =      AlignProcessor(tokenizer=lowercase_						,	image_processor=lowercase_							)

     A__    =      "lower newer"
     A__    =      self.prepare_image_inputs()

     A__    =      processor(text=lowercase_						,	images=lowercase_							)

     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(lowercase_							):
         processor()
 def 					UpperCAmelCase_							(    self				:int							)->							Tuple:
     A__    =      self.get_image_processor()
     A__    =      self.get_tokenizer()

     A__    =      AlignProcessor(tokenizer=lowercase_						,	image_processor=lowercase_							)

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

     A__    =      processor.batch_decode(lowercase_							)
     A__    =      tokenizer.batch_decode(lowercase_							)

     self.assertListEqual(lowercase_						,	lowercase_							)



 def 					UpperCAmelCase_							(    self				:Any							)->							List[Any]:
     A__    =      self.get_image_processor()
     A__    =      self.get_tokenizer()

     A__    =      AlignProcessor(tokenizer=lowercase_						,	image_processor=lowercase_							)

     A__    =      "lower newer"
     A__    =      self.prepare_image_inputs()

     A__    =      processor(text=lowercase_						,	images=lowercase_							)

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










'''simple docstring'''

def 						UpperCamelCase    (							_lowerCamelCase : int	):

    if not isinstance(_lowerCamelCase						,	_lowerCamelCase	):
        A__    =      F"Input value of [number={number}] must be an integer"
        raise TypeError(_lowerCamelCase	)

    if number < 1:
        A__    =      F"Input value of [number={number}] must be > 0"
        raise ValueError(_lowerCamelCase	)

    A__    =      1

    for i in range(1						,	_lowerCamelCase	):
        current_number *= 4 * i - 2
        current_number //= i + 1

    return current_number


if __name__ == "__main__":
  import doctest

  doctest.testmod()



