
"""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        _SCREAMING_SNAKE_CASE  (  unittest.TestCase							):






				'''simple docstring'''



				def 				__lowerCamelCase	(					self	:			Tuple  )		->  Union[str, Any]:







											"""simple docstring"""




											_lowerCAmelCase  	=			tempfile.mkdtemp()

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

											_lowerCAmelCase  	=			{
											    'do_resize': True,
											    'size': 20,
											    'do_center_crop': True,
											    'crop_size': 18,
											    'do_normalize': True,
											    'image_mean': [0.48145466, 0.4578275, 0.40821073],
											    'image_std': [0.26862954, 0.26130258, 0.27577711],
											}
											_lowerCAmelCase  	=			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	:			Any				,     **UpperCAmelCase_	:			str  )		->  str:







											"""simple docstring"""




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


				def 				__lowerCamelCase	(					self	:			List[str]				,     **UpperCAmelCase_	:			int  )		->  Any:







											"""simple docstring"""




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


				def 				__lowerCamelCase	(					self	:			Union[str, Any]				,     **UpperCAmelCase_	:			Optional[Any]  )		->  Union[str, Any]:







											"""simple docstring"""




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


				def 				__lowerCamelCase	(					self	:			Optional[int]  )		->  List[str]:







											"""simple docstring"""




											shutil.rmtree(self.tmpdirname  )


				def 				__lowerCamelCase	(					self	:			Any  )		->  int:







											"""simple docstring"""




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


				def 				__lowerCamelCase	(					self	:			Dict  )		->  Tuple:







											"""simple docstring"""




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

											_lowerCAmelCase  	=			AlignProcessor(tokenizer=UpperCAmelCase_				,     image_processor=UpperCAmelCase_  )
											processor_slow.save_pretrained(self.tmpdirname  )
											_lowerCAmelCase  	=			AlignProcessor.from_pretrained(self.tmpdirname				,     use_fast=UpperCAmelCase_  )

											_lowerCAmelCase  	=			AlignProcessor(tokenizer=UpperCAmelCase_				,     image_processor=UpperCAmelCase_  )
											processor_fast.save_pretrained(self.tmpdirname  )
											_lowerCAmelCase  	=			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 				__lowerCamelCase	(					self	:			Union[str, Any]  )		->  List[Any]:







											"""simple docstring"""




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

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

											_lowerCAmelCase  	=			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 				__lowerCamelCase	(					self	:			List[Any]  )		->  Any:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_image_processor()
											_lowerCAmelCase  	=			self.get_tokenizer()

											_lowerCAmelCase  	=			AlignProcessor(tokenizer=UpperCAmelCase_				,     image_processor=UpperCAmelCase_  )

											_lowerCAmelCase  	=			self.prepare_image_inputs()

											_lowerCAmelCase  	=			image_processor(UpperCAmelCase_				,     return_tensors='np'  )
											_lowerCAmelCase  	=			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	:			Optional[Any]  )		->  Optional[int]:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_image_processor()
											_lowerCAmelCase  	=			self.get_tokenizer()

											_lowerCAmelCase  	=			AlignProcessor(tokenizer=UpperCAmelCase_				,     image_processor=UpperCAmelCase_  )

											_lowerCAmelCase  	=			'lower newer'

											_lowerCAmelCase  	=			processor(text=UpperCAmelCase_  )

											_lowerCAmelCase  	=			tokenizer(UpperCAmelCase_				,     padding='max_length'				,     max_length=64  )

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


				def 				__lowerCamelCase	(					self	:			int  )		->  Union[str, Any]:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_image_processor()
											_lowerCAmelCase  	=			self.get_tokenizer()

											_lowerCAmelCase  	=			AlignProcessor(tokenizer=UpperCAmelCase_				,     image_processor=UpperCAmelCase_  )

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

											_lowerCAmelCase  	=			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 				__lowerCamelCase	(					self	:			List[str]  )		->  List[Any]:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_image_processor()
											_lowerCAmelCase  	=			self.get_tokenizer()

											_lowerCAmelCase  	=			AlignProcessor(tokenizer=UpperCAmelCase_				,     image_processor=UpperCAmelCase_  )

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

											_lowerCAmelCase  	=			processor.batch_decode(UpperCAmelCase_  )
											_lowerCAmelCase  	=			tokenizer.batch_decode(UpperCAmelCase_  )

											self.assertListEqual(UpperCAmelCase_				,     UpperCAmelCase_  )







				def 				__lowerCamelCase	(					self	:			Any  )		->  List[Any]:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_image_processor()
											_lowerCAmelCase  	=			self.get_tokenizer()

											_lowerCAmelCase  	=			AlignProcessor(tokenizer=UpperCAmelCase_				,     image_processor=UpperCAmelCase_  )

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

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

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








"""simple docstring"""



import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase							)
class        _SCREAMING_SNAKE_CASE  (  UpperCAmelCase							):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE_:							str							=					field(default="image-classification"      ,				metadata={"include_in_asdict_even_if_is_default": True}							)
				SCREAMING_SNAKE_CASE_:							ClassVar[Features]							=					Features({"image": Image()}							)
				SCREAMING_SNAKE_CASE_:							ClassVar[Features]							=					Features({"labels": ClassLabel}							)
				SCREAMING_SNAKE_CASE_:							str							=					"image"
				SCREAMING_SNAKE_CASE_:							str							=					"labels"


				def 				__lowerCamelCase	(					self	:			str				,     UpperCAmelCase_	:			Optional[Any]  )		->  Dict:







											"""simple docstring"""




											if self.label_column not in features:
																		raise ValueError(F"""Column {self.label_column} is not present in features."""  )
											if not isinstance(features[self.label_column]				,     UpperCAmelCase_  ):
																		raise ValueError(F"""Column {self.label_column} is not a ClassLabel."""  )
											_lowerCAmelCase  	=			copy.deepcopy(self  )
											_lowerCAmelCase  	=			self.label_schema.copy()
											_lowerCAmelCase  	=			features[self.label_column]
											_lowerCAmelCase  	=			label_schema
											return task_template







				@property
				def 				__lowerCamelCase	(					self	:			Union[str, Any]  )		->  Dict[str, str]:







											"""simple docstring"""




											return {
											    self.image_column: "image",
											    self.label_column: "labels",
											}






