





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       ):






			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			tempfile.mkdtemp()

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

										UpperCamelCase__				     =			{
										    """do_resize""": True,
										    """size""": 20,
										    """do_center_crop""": True,
										    """crop_size""": 18,
										    """do_normalize""": True,
										    """image_mean""": [0.4814_5466, 0.457_8275, 0.4082_1073],
										    """image_std""": [0.2686_2954, 0.2613_0258, 0.2757_7711],
										}
										UpperCamelCase__				     =			os.path.join(self.tmpdirname  , __lowerCAmelCase  )
										with open(self.image_processor_file  , """w"""  , encoding="""utf-8"""  ) as fp:
																	json.dump(__lowerCAmelCase  , __lowerCAmelCase  )






			def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
										return BertTokenizer.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






			def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
										return BertTokenizerFast.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






			def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
										return EfficientNetImageProcessor.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






			def 				_lowerCamelCase		(						self  ):
										shutil.rmtree(self.tmpdirname  )






			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			[np.random.randint(255  , size=(3, 30, 400)  , dtype=np.uinta  )]
										UpperCamelCase__				     =			[Image.fromarray(np.moveaxis(__lowerCAmelCase  , 0  , -1  )  ) for x in image_inputs]
										return image_inputs






			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			self.get_tokenizer()
										UpperCamelCase__				     =			self.get_rust_tokenizer()
										UpperCamelCase__				     =			self.get_image_processor()

										UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )
										processor_slow.save_pretrained(self.tmpdirname  )
										UpperCamelCase__				     =			AlignProcessor.from_pretrained(self.tmpdirname  , use_fast=__lowerCAmelCase  )

										UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )
										processor_fast.save_pretrained(self.tmpdirname  )
										UpperCamelCase__				     =			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  , __lowerCAmelCase  )
										self.assertIsInstance(processor_fast.tokenizer  , __lowerCAmelCase  )

										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  , __lowerCAmelCase  )
										self.assertIsInstance(processor_fast.image_processor  , __lowerCAmelCase  )






			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			AlignProcessor(tokenizer=self.get_tokenizer()  , image_processor=self.get_image_processor()  )
										processor.save_pretrained(self.tmpdirname  )

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

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

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

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






			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			self.get_image_processor()
										UpperCamelCase__				     =			self.get_tokenizer()

										UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

										UpperCamelCase__				     =			self.prepare_image_inputs()

										UpperCamelCase__				     =			image_processor(__lowerCAmelCase  , return_tensors="""np"""  )
										UpperCamelCase__				     =			processor(images=__lowerCAmelCase  , 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  ):
										UpperCamelCase__				     =			self.get_image_processor()
										UpperCamelCase__				     =			self.get_tokenizer()

										UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

										UpperCamelCase__				     =			"""lower newer"""

										UpperCamelCase__				     =			processor(text=__lowerCAmelCase  )

										UpperCamelCase__				     =			tokenizer(__lowerCAmelCase  , padding="""max_length"""  , max_length=64  )

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






			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			self.get_image_processor()
										UpperCamelCase__				     =			self.get_tokenizer()

										UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

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

										UpperCamelCase__				     =			processor(text=__lowerCAmelCase  , images=__lowerCAmelCase  )

										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(__lowerCAmelCase  ):
																	processor()






			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			self.get_image_processor()
										UpperCamelCase__				     =			self.get_tokenizer()

										UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

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

										UpperCamelCase__				     =			processor.batch_decode(__lowerCAmelCase  )
										UpperCamelCase__				     =			tokenizer.batch_decode(__lowerCAmelCase  )

										self.assertListEqual(__lowerCAmelCase  , __lowerCAmelCase  )







			def 				_lowerCamelCase		(						self  ):
										UpperCamelCase__				     =			self.get_image_processor()
										UpperCamelCase__				     =			self.get_tokenizer()

										UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

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

										UpperCamelCase__				     =			processor(text=__lowerCAmelCase  , images=__lowerCAmelCase  )

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











from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase__											= logging.get_logger(__name__)

UpperCamelCase__											= {
    "studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
    "studio-ousia/luke-large": "https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json",
}

class        __SCREAMING_SNAKE_CASE					(     _a       ):
							snake_case     :      Optional[int]						     =       """luke"""






							def __init__(						self  , __lowerCAmelCase=50267  , __lowerCAmelCase=500000  , __lowerCAmelCase=768  , __lowerCAmelCase=256  , __lowerCAmelCase=12  , __lowerCAmelCase=12  , __lowerCAmelCase=3072  , __lowerCAmelCase="gelu"  , __lowerCAmelCase=0.1  , __lowerCAmelCase=0.1  , __lowerCAmelCase=512  , __lowerCAmelCase=2  , __lowerCAmelCase=0.02  , __lowerCAmelCase=1E-12  , __lowerCAmelCase=True  , __lowerCAmelCase=None  , __lowerCAmelCase=1  , __lowerCAmelCase=0  , __lowerCAmelCase=2  , **__lowerCAmelCase  , ):
														super().__init__(pad_token_id=__lowerCAmelCase  , bos_token_id=__lowerCAmelCase  , eos_token_id=__lowerCAmelCase  , **__lowerCAmelCase  )

														UpperCamelCase__				     =			vocab_size
														UpperCamelCase__				     =			entity_vocab_size
														UpperCamelCase__				     =			hidden_size
														UpperCamelCase__				     =			entity_emb_size
														UpperCamelCase__				     =			num_hidden_layers
														UpperCamelCase__				     =			num_attention_heads
														UpperCamelCase__				     =			hidden_act
														UpperCamelCase__				     =			intermediate_size
														UpperCamelCase__				     =			hidden_dropout_prob
														UpperCamelCase__				     =			attention_probs_dropout_prob
														UpperCamelCase__				     =			max_position_embeddings
														UpperCamelCase__				     =			type_vocab_size
														UpperCamelCase__				     =			initializer_range
														UpperCamelCase__				     =			layer_norm_eps
														UpperCamelCase__				     =			use_entity_aware_attention
														UpperCamelCase__				     =			classifier_dropout




