"""simple docstring"""







import json
import os
import random
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 FlavaImageProcessor, FlavaProcessor
						from transformers.models.flava.image_processing_flava import (
						    FLAVA_CODEBOOK_MEAN,
						    FLAVA_CODEBOOK_STD,
						    FLAVA_IMAGE_MEAN,
						    FLAVA_IMAGE_STD,
						)


@require_vision
class 			_lowercase		(   unittest.TestCase  ):

				def        A (     self       :    str     ):


										'''simple docstring'''
										UpperCAmelCase__						=		tempfile.mkdtemp()

										# fmt: off
										UpperCAmelCase__						=		["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing""", """,""", """low""", """lowest"""]
										# fmt: on
										UpperCAmelCase__						=		os.path.join(self.tmpdirname       ,    VOCAB_FILES_NAMES["""vocab_file"""]     )

										with open(self.vocab_file       ,    """w"""       ,    encoding="""utf-8"""     ) as fp:
																fp.write("""""".join([x + """\n""" for x in vocab_tokens]     )     )

										UpperCAmelCase__						=		{
										    """image_mean""": FLAVA_IMAGE_MEAN,
										    """image_std""": FLAVA_IMAGE_STD,
										    """do_normalize""": True,
										    """do_resize""": True,
										    """size""": 2_2_4,
										    """do_center_crop""": True,
										    """crop_size""": 2_2_4,
										    """input_size_patches""": 1_4,
										    """total_mask_patches""": 7_5,
										    """mask_group_max_patches""": None,
										    """mask_group_min_patches""": 1_6,
										    """mask_group_min_aspect_ratio""": 0.3,
										    """mask_group_max_aspect_ratio""": None,
										    """codebook_do_resize""": True,
										    """codebook_size""": 1_1_2,
										    """codebook_do_center_crop""": True,
										    """codebook_crop_size""": 1_1_2,
										    """codebook_do_map_pixels""": True,
										    """codebook_do_normalize""": True,
										    """codebook_image_mean""": FLAVA_CODEBOOK_MEAN,
										    """codebook_image_std""": FLAVA_CODEBOOK_STD,
										}

										UpperCAmelCase__						=		os.path.join(self.tmpdirname       ,    _lowercase     )
										with open(self.image_processor_file       ,    """w"""       ,    encoding="""utf-8"""     ) as fp:
																json.dump(_lowercase       ,    _lowercase     )

				def        A (     self       :    Any       ,    **_lowercase       :    Union[str, Any]     ):


										'''simple docstring'''
										return BertTokenizer.from_pretrained(self.tmpdirname       ,    **_lowercase     )

				def        A (     self       :    Dict       ,    **_lowercase       :    Optional[Any]     ):


										'''simple docstring'''
										return BertTokenizerFast.from_pretrained(self.tmpdirname       ,    **_lowercase     )

				def        A (     self       :    Tuple       ,    **_lowercase       :    str     ):


										'''simple docstring'''
										return FlavaImageProcessor.from_pretrained(self.tmpdirname       ,    **_lowercase     )

				def        A (     self       :    Dict     ):


										'''simple docstring'''
										shutil.rmtree(self.tmpdirname     )

				def        A (     self       :    List[str]     ):


										'''simple docstring'''
										UpperCAmelCase__						=		[np.random.randint(2_5_5       ,    size=(3, 3_0, 4_0_0)       ,    dtype=np.uinta     )]

										UpperCAmelCase__						=		[Image.fromarray(np.moveaxis(_lowercase       ,    0       ,    -1     )     ) for x in image_inputs]

										return image_inputs

				def        A (     self       :    int     ):


										'''simple docstring'''
										UpperCAmelCase__						=		self.get_tokenizer()
										UpperCAmelCase__						=		self.get_rust_tokenizer()
										UpperCAmelCase__						=		self.get_image_processor()

										UpperCAmelCase__						=		FlavaProcessor(tokenizer=_lowercase       ,    image_processor=_lowercase     )
										processor_slow.save_pretrained(self.tmpdirname     )
										UpperCAmelCase__						=		FlavaProcessor.from_pretrained(self.tmpdirname       ,    use_fast=_lowercase     )

										UpperCAmelCase__						=		FlavaProcessor(tokenizer=_lowercase       ,    image_processor=_lowercase     )
										processor_fast.save_pretrained(self.tmpdirname     )
										UpperCAmelCase__						=		FlavaProcessor.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        A (     self       :    List[Any]     ):


										'''simple docstring'''
										UpperCAmelCase__						=		FlavaProcessor(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=_lowercase       ,    padding_value=1.0     )

										UpperCAmelCase__						=		FlavaProcessor.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        A (     self       :    List[Any]     ):


										'''simple docstring'''
										UpperCAmelCase__						=		self.get_image_processor()
										UpperCAmelCase__						=		self.get_tokenizer()

										UpperCAmelCase__						=		FlavaProcessor(tokenizer=_lowercase       ,    image_processor=_lowercase     )

										UpperCAmelCase__						=		self.prepare_image_inputs()

										UpperCAmelCase__						=		image_processor(_lowercase       ,    return_tensors="""np"""     )
										UpperCAmelCase__						=		processor(images=_lowercase       ,    return_tensors="""np"""     )

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

										# With rest of the args
										random.seed(1_2_3_4     )
										UpperCAmelCase__						=		image_processor(
										    _lowercase       ,    return_image_mask=_lowercase       ,    return_codebook_pixels=_lowercase       ,    return_tensors="""np"""     )
										random.seed(1_2_3_4     )
										UpperCAmelCase__						=		processor(
										    images=_lowercase       ,    return_image_mask=_lowercase       ,    return_codebook_pixels=_lowercase       ,    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        A (     self       :    str     ):


										'''simple docstring'''
										UpperCAmelCase__						=		self.get_image_processor()
										UpperCAmelCase__						=		self.get_tokenizer()

										UpperCAmelCase__						=		FlavaProcessor(tokenizer=_lowercase       ,    image_processor=_lowercase     )

										UpperCAmelCase__						=		"""lower newer"""

										UpperCAmelCase__						=		processor(text=_lowercase     )

										UpperCAmelCase__						=		tokenizer(_lowercase     )

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

				def        A (     self       :    Tuple     ):


										'''simple docstring'''
										UpperCAmelCase__						=		self.get_image_processor()
										UpperCAmelCase__						=		self.get_tokenizer()

										UpperCAmelCase__						=		FlavaProcessor(tokenizer=_lowercase       ,    image_processor=_lowercase     )

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

										UpperCAmelCase__						=		processor(text=_lowercase       ,    images=_lowercase     )

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

										# add extra args
										UpperCAmelCase__						=		processor(text=_lowercase       ,    images=_lowercase       ,    return_codebook_pixels=_lowercase       ,    return_image_mask=_lowercase     )

										self.assertListEqual(
										    list(inputs.keys()     )       ,    [
										        """input_ids""",
										        """token_type_ids""",
										        """attention_mask""",
										        """pixel_values""",
										        """codebook_pixel_values""",
										        """bool_masked_pos""",
										    ]       ,    )

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

				def        A (     self       :    List[str]     ):


										'''simple docstring'''
										UpperCAmelCase__						=		self.get_image_processor()
										UpperCAmelCase__						=		self.get_tokenizer()

										UpperCAmelCase__						=		FlavaProcessor(tokenizer=_lowercase       ,    image_processor=_lowercase     )

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

										UpperCAmelCase__						=		processor.batch_decode(_lowercase     )
										UpperCAmelCase__						=		tokenizer.batch_decode(_lowercase     )

										self.assertListEqual(_lowercase       ,    _lowercase     )

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


										'''simple docstring'''
										UpperCAmelCase__						=		self.get_image_processor()
										UpperCAmelCase__						=		self.get_tokenizer()

										UpperCAmelCase__						=		FlavaProcessor(tokenizer=_lowercase       ,    image_processor=_lowercase     )

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

										UpperCAmelCase__						=		processor(text=_lowercase       ,    images=_lowercase     )

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


"""simple docstring"""







def   a__      (		UpperCAmelCase__       :			list[int]			)->	int:
						UpperCAmelCase__						=		len(UpperCAmelCase__			)
						if n in (0, 1):
												return 0
						return sum(query * (n - i - 1) for i, query in enumerate(sorted(UpperCAmelCase__			)			)			)


if __name__ == "__main__":
						import doctest

						doctest.testmod()

