
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 FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor







@require_vision
class        A_   (			unittest.TestCase   ):




	'''simple docstring'''


	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    tempfile.mkdtemp()

		lowercase       =    [
		    '[UNK]',
		    '[CLS]',
		    '[SEP]',
		    '[PAD]',
		    '[MASK]',
		    '的',
		    '价',
		    '格',
		    '是',
		    '15',
		    '便',
		    'alex',
		    '##andra',
		    '，',
		    '。',
		    '-',
		    't',
		    'shirt',
		]
		lowercase       =    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]       )       )

		lowercase       =    {
		    'do_resize': True,
		    'size': {'height': 224, 'width': 224},
		    'do_center_crop': True,
		    'crop_size': {'height': 18, 'width': 18},
		    'do_normalize': True,
		    'image_mean': [0.48_145_466, 0.4_578_275, 0.40_821_073],
		    'image_std': [0.26_862_954, 0.26_130_258, 0.27_577_711],
		    'do_convert_rgb': True,
		}
		lowercase       =    os.path.join(self.tmpdirname		,    snake_case       )
		with open(self.image_processor_file		,    'w'		,    encoding='utf-8'       ) as fp:
			json.dump(snake_case		,    snake_case       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    **snake_case       ):
		return BertTokenizer.from_pretrained(self.tmpdirname		,    **snake_case       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    **snake_case       ):
		return BertTokenizerFast.from_pretrained(self.tmpdirname		,    **snake_case       )





	def 	SCREAMING_SNAKE_CASE__						(       self		,    **snake_case       ):
		return ChineseCLIPImageProcessor.from_pretrained(self.tmpdirname		,    **snake_case       )





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





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    [np.random.randint(255		,    size=(3, 30, 400)		,    dtype=np.uinta       )]

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

		return image_inputs





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_tokenizer()
		lowercase       =    self.get_rust_tokenizer()
		lowercase       =    self.get_image_processor()

		lowercase       =    ChineseCLIPProcessor(tokenizer=snake_case		,    image_processor=snake_case       )
		processor_slow.save_pretrained(self.tmpdirname       )
		lowercase       =    ChineseCLIPProcessor.from_pretrained(self.tmpdirname		,    use_fast=snake_case       )

		lowercase       =    ChineseCLIPProcessor(tokenizer=snake_case		,    image_processor=snake_case       )
		processor_fast.save_pretrained(self.tmpdirname       )
		lowercase       =    ChineseCLIPProcessor.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		,    snake_case       )
		self.assertIsInstance(processor_fast.tokenizer		,    snake_case       )

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





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    ChineseCLIPProcessor(tokenizer=self.get_tokenizer()		,    image_processor=self.get_image_processor()       )
		processor.save_pretrained(self.tmpdirname       )

		lowercase       =    self.get_tokenizer(cls_token='(CLS)'		,    sep_token='(SEP)'       )
		lowercase       =    self.get_image_processor(do_normalize=snake_case       )

		lowercase       =    ChineseCLIPProcessor.from_pretrained(
		    self.tmpdirname		,    cls_token='(CLS)'		,    sep_token='(SEP)'		,    do_normalize=snake_case       )

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

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





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

		lowercase       =    ChineseCLIPProcessor(tokenizer=snake_case		,    image_processor=snake_case       )

		lowercase       =    self.prepare_image_inputs()

		lowercase       =    image_processor(snake_case		,    return_tensors='np'       )
		lowercase       =    processor(images=snake_case		,    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 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

		lowercase       =    ChineseCLIPProcessor(tokenizer=snake_case		,    image_processor=snake_case       )

		lowercase       =    'Alexandra，T-shirt的价格是15便士。'

		lowercase       =    processor(text=snake_case       )

		lowercase       =    tokenizer(snake_case       )

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





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

		lowercase       =    ChineseCLIPProcessor(tokenizer=snake_case		,    image_processor=snake_case       )

		lowercase       =    'Alexandra，T-shirt的价格是15便士。'
		lowercase       =    self.prepare_image_inputs()

		lowercase       =    processor(text=snake_case		,    images=snake_case       )

		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(snake_case       ):
			processor()





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

		lowercase       =    ChineseCLIPProcessor(tokenizer=snake_case		,    image_processor=snake_case       )

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

		lowercase       =    processor.batch_decode(snake_case       )
		lowercase       =    tokenizer.batch_decode(snake_case       )

		self.assertListEqual(snake_case		,    snake_case       )





	def 	SCREAMING_SNAKE_CASE__						(       self       ):
		lowercase       =    self.get_image_processor()
		lowercase       =    self.get_tokenizer()

		lowercase       =    ChineseCLIPProcessor(tokenizer=snake_case		,    image_processor=snake_case       )

		lowercase       =    'Alexandra，T-shirt的价格是15便士。'
		lowercase       =    self.prepare_image_inputs()

		lowercase       =    processor(text=snake_case		,    images=snake_case       )

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



import argparse
import os
from io import BytesIO
from pathlib import Path

import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE ,							__SCREAMING_SNAKE_CASE							):
	lowercase       =    1.5
	lowercase       =    int(factor * num_class_images							)
	lowercase       =    ClipClient(
	    url='https://knn.laion.ai/knn-service' ,							indice_name='laion_400m' ,							num_images=__SCREAMING_SNAKE_CASE ,							aesthetic_weight=0.1							)

	os.makedirs(F'''{class_data_dir}/images''' ,							exist_ok=__SCREAMING_SNAKE_CASE							)
	if len(list(Path(F'''{class_data_dir}/images'''							).iterdir()							)							) >= num_class_images:
		return

	while True:
		lowercase       =    client.query(text=__SCREAMING_SNAKE_CASE							)
		if len(__SCREAMING_SNAKE_CASE							) >= factor * num_class_images or num_images > 1e4:
			break
		else:
			lowercase       =    int(factor * num_images							)
			lowercase       =    ClipClient(
			    url='https://knn.laion.ai/knn-service' ,							indice_name='laion_400m' ,							num_images=__SCREAMING_SNAKE_CASE ,							aesthetic_weight=0.1 ,							)

	lowercase       =    0
	lowercase       =    0
	lowercase       =    tqdm(desc='downloading real regularization images' ,							total=__SCREAMING_SNAKE_CASE							)

	with open(F'''{class_data_dir}/caption.txt''' ,							'w'							) as fa, open(F'''{class_data_dir}/urls.txt''' ,							'w'							) as fa, open(
	    F'''{class_data_dir}/images.txt''' ,							'w'							) as fa:
		while total < num_class_images:
			lowercase       =    class_images[count]
			count += 1
			try:
				lowercase       =    requests.get(images['url']							)
				if img.status_code == 200:
					lowercase       =    Image.open(BytesIO(img.content							)							)
					with open(F'''{class_data_dir}/images/{total}.jpg''' ,							'wb'							) as f:
						f.write(img.content							)
					fa.write(images['caption'] + '\n'							)
					fa.write(images['url'] + '\n'							)
					fa.write(F'''{class_data_dir}/images/{total}.jpg''' + '\n'							)
					total += 1
					pbar.update(1							)
				else:
					continue
			except Exception:
				continue
	return






def 							UpperCAmelCase_		(							):
	lowercase       =    argparse.ArgumentParser('' ,							add_help=__SCREAMING_SNAKE_CASE							)
	parser.add_argument('--class_prompt' ,							help='text prompt to retrieve images' ,							required=__SCREAMING_SNAKE_CASE ,							type=__SCREAMING_SNAKE_CASE							)
	parser.add_argument('--class_data_dir' ,							help='path to save images' ,							required=__SCREAMING_SNAKE_CASE ,							type=__SCREAMING_SNAKE_CASE							)
	parser.add_argument('--num_class_images' ,							help='number of images to download' ,							default=200 ,							type=__SCREAMING_SNAKE_CASE							)
	return parser.parse_args()


if __name__ == "__main__":
	UpperCAmelCase	      = parse_args()
	retrieve(args.class_prompt, args.class_data_dir, args.num_class_images)

