


'''simple docstring'''
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
		from PIL import Image

		from transformers import AutoProcessor, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast
@require_vision
class        lowercase     (							unittest.TestCase ):

		"""simple docstring"""

		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :str							 =			tempfile.mkdtemp()

							UpperCamelCase__       :Union[str, Any]							 =			BlipImageProcessor()
							UpperCamelCase__       :List[Any]							 =			GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''							)

							UpperCamelCase__       :int							 =			BlipaProcessor(UpperCamelCase_   ,       UpperCamelCase_							)

							processor.save_pretrained(self.tmpdirname							)




		def    lowerCAmelCase__    (		self   ,       **UpperCamelCase_							):

							'''simple docstring'''


							return AutoProcessor.from_pretrained(self.tmpdirname   ,       **UpperCamelCase_							).tokenizer




		def    lowerCAmelCase__    (		self   ,       **UpperCamelCase_							):

							'''simple docstring'''


							return AutoProcessor.from_pretrained(self.tmpdirname   ,       **UpperCamelCase_							).image_processor




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							shutil.rmtree(self.tmpdirname							)




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Optional[int]							 =			[np.random.randint(255   ,       size=(3, 30, 400)   ,       dtype=np.uinta							)]

							UpperCamelCase__       :Any							 =			[Image.fromarray(np.moveaxis(UpperCamelCase_   ,       0   ,       -1							)							) for x in image_inputs]

							return image_inputs




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Optional[int]							 =			BlipaProcessor(tokenizer=self.get_tokenizer()   ,       image_processor=self.get_image_processor()							)
							processor.save_pretrained(self.tmpdirname							)

							UpperCamelCase__       :List[str]							 =			self.get_tokenizer(bos_token='''(BOS)'''   ,       eos_token='''(EOS)'''							)
							UpperCamelCase__       :str							 =			self.get_image_processor(do_normalize=UpperCamelCase_   ,       padding_value=1.0							)

							UpperCamelCase__       :List[Any]							 =			BlipaProcessor.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							):

							'''simple docstring'''


							UpperCamelCase__       :Dict							 =			self.get_image_processor()
							UpperCamelCase__       :Any							 =			self.get_tokenizer()

							UpperCamelCase__       :str							 =			BlipaProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :Tuple							 =			self.prepare_image_inputs()

							UpperCamelCase__       :Dict							 =			image_processor(UpperCamelCase_   ,       return_tensors='''np'''							)
							UpperCamelCase__       :Optional[Any]							 =			processor(images=UpperCamelCase_   ,       return_tensors='''np'''							)

							for key in input_feat_extract.keys():
												self.assertAlmostEqual(input_feat_extract[key].sum()   ,       input_processor[key].sum()   ,       delta=1e-2							)




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Any							 =			self.get_image_processor()
							UpperCamelCase__       :Union[str, Any]							 =			self.get_tokenizer()

							UpperCamelCase__       :Dict							 =			BlipaProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :str							 =			'''lower newer'''

							UpperCamelCase__       :Dict							 =			processor(text=UpperCamelCase_							)

							UpperCamelCase__       :Union[str, Any]							 =			tokenizer(UpperCamelCase_   ,       return_token_type_ids=UpperCamelCase_							)

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




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :List[str]							 =			self.get_image_processor()
							UpperCamelCase__       :Optional[Any]							 =			self.get_tokenizer()

							UpperCamelCase__       :Optional[int]							 =			BlipaProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :str							 =			'''lower newer'''
							UpperCamelCase__       :Optional[Any]							 =			self.prepare_image_inputs()

							UpperCamelCase__       :Any							 =			processor(text=UpperCamelCase_   ,       images=UpperCamelCase_							)

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

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




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :Union[str, Any]							 =			self.get_image_processor()
							UpperCamelCase__       :str							 =			self.get_tokenizer()

							UpperCamelCase__       :Dict							 =			BlipaProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :Dict							 =			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							UpperCamelCase__       :Tuple							 =			processor.batch_decode(UpperCamelCase_							)
							UpperCamelCase__       :List[Any]							 =			tokenizer.batch_decode(UpperCamelCase_							)

							self.assertListEqual(UpperCamelCase_   ,       UpperCamelCase_							)




		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							UpperCamelCase__       :List[Any]							 =			self.get_image_processor()
							UpperCamelCase__       :List[Any]							 =			self.get_tokenizer()

							UpperCamelCase__       :List[str]							 =			BlipaProcessor(tokenizer=UpperCamelCase_   ,       image_processor=UpperCamelCase_							)

							UpperCamelCase__       :str							 =			'''lower newer'''
							UpperCamelCase__       :Optional[Any]							 =			self.prepare_image_inputs()

							UpperCamelCase__       :List[Any]							 =			processor(text=UpperCamelCase_   ,       images=UpperCamelCase_							)

							# For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
							self.assertListEqual(list(inputs.keys()							)   ,       ['''pixel_values''', '''input_ids''', '''attention_mask''']							)



'''simple docstring'''
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__snake_case											=					logging.get_logger(__name__)

__snake_case											=					{
    '''distilbert-base-uncased''': '''https://huggingface.co/distilbert-base-uncased/resolve/main/config.json''',
    '''distilbert-base-uncased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-cased''': '''https://huggingface.co/distilbert-base-cased/resolve/main/config.json''',
    '''distilbert-base-cased-distilled-squad''': (
        '''https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json'''
    ),
    '''distilbert-base-german-cased''': '''https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json''',
    '''distilbert-base-multilingual-cased''': (
        '''https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json'''
    ),
    '''distilbert-base-uncased-finetuned-sst-2-english''': (
        '''https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json'''
    ),
}
class        lowercase     (							A__ ):

		"""simple docstring"""

		_a   			=    'distilbert'
		_a   			=    {
		    'hidden_size': 'dim',
		    'num_attention_heads': 'n_heads',
		    'num_hidden_layers': 'n_layers',
		}




		def __init__(		self   ,       UpperCamelCase_=30522   ,       UpperCamelCase_=512   ,       UpperCamelCase_=False   ,       UpperCamelCase_=6   ,       UpperCamelCase_=12   ,       UpperCamelCase_=768   ,       UpperCamelCase_=4 * 768   ,       UpperCamelCase_=0.1   ,       UpperCamelCase_=0.1   ,       UpperCamelCase_="gelu"   ,       UpperCamelCase_=0.02   ,       UpperCamelCase_=0.1   ,       UpperCamelCase_=0.2   ,       UpperCamelCase_=0   ,       **UpperCamelCase_   ,       ):

							'''simple docstring'''


							UpperCamelCase__       :List[Any]							 =			vocab_size
							UpperCamelCase__       :Dict							 =			max_position_embeddings
							UpperCamelCase__       :str							 =			sinusoidal_pos_embds
							UpperCamelCase__       :Any							 =			n_layers
							UpperCamelCase__       :str							 =			n_heads
							UpperCamelCase__       :Tuple							 =			dim
							UpperCamelCase__       :str							 =			hidden_dim
							UpperCamelCase__       :Dict							 =			dropout
							UpperCamelCase__       :int							 =			attention_dropout
							UpperCamelCase__       :Optional[Any]							 =			activation
							UpperCamelCase__       :Optional[int]							 =			initializer_range
							UpperCamelCase__       :Union[str, Any]							 =			qa_dropout
							UpperCamelCase__       :Dict							 =			seq_classif_dropout
							super().__init__(**UpperCamelCase_   ,       pad_token_id=UpperCamelCase_							)



class        lowercase     (							A__ ):

		"""simple docstring"""

		@property
		def    lowerCAmelCase__    (		self							):

							'''simple docstring'''


							if self.task == "multiple-choice":
												UpperCamelCase__       :str							 =			{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
							else:
												UpperCamelCase__       :str							 =			{0: '''batch''', 1: '''sequence'''}
							return OrderedDict(
							    [
							        ('''input_ids''', dynamic_axis),
							        ('''attention_mask''', dynamic_axis),
							    ]							)