

'''simple docstring'''


import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip 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 OwlViTImageProcessor, OwlViTProcessor



@require_vision
class 					lowercase						(  unittest.TestCase ):


							def 						_snake_case							(			self)							->				Any:
								UpperCAmelCase_		:      List[str]       	=					tempfile.mkdtemp()

								# fmt: off
								UpperCAmelCase_		:      List[Any]       	=					['', 'l', 'o', 'w', 'e', 'r', 's', 't', 'i', 'd', 'n', 'lo', 'l</w>', 'w</w>', 'r</w>', 't</w>', 'low</w>', 'er</w>', 'lowest</w>', 'newer</w>', 'wider', '<unk>', '<|startoftext|>', '<|endoftext|>']
								# fmt: on
								UpperCAmelCase_		:      List[str]       	=					dict(zip(_snake_case    ,			range(len(_snake_case))))
								UpperCAmelCase_		:      Tuple       	=					['#version: 0.2', 'l o', 'lo w</w>', 'e r</w>', '']
								UpperCAmelCase_		:      int       	=					{'unk_token': '<unk>'}

								UpperCAmelCase_		:      Any       	=					os.path.join(self.tmpdirname    ,			VOCAB_FILES_NAMES['vocab_file'])
								UpperCAmelCase_		:      List[Any]       	=					os.path.join(self.tmpdirname    ,			VOCAB_FILES_NAMES['merges_file'])
								with open(self.vocab_file    ,			'w'    ,			encoding='utf-8') as fp:
									fp.write(json.dumps(_snake_case) + '\n')
								with open(self.merges_file    ,			'w'    ,			encoding='utf-8') as fp:
									fp.write('\n'.join(_snake_case))

								UpperCAmelCase_		:      Optional[int]       	=					{
								    'do_resize': True,
								    'size': 20,
								    'do_center_crop': True,
								    'crop_size': 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],
								}
								UpperCAmelCase_		:      Tuple       	=					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 						_snake_case							(			self    ,			**_snake_case)							->				Dict:
								return CLIPTokenizer.from_pretrained(self.tmpdirname    ,			pad_token='!'    ,			**_snake_case)


							def 						_snake_case							(			self    ,			**_snake_case)							->				int:
								return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,			pad_token='!'    ,			**_snake_case)


							def 						_snake_case							(			self    ,			**_snake_case)							->				Optional[Any]:
								return OwlViTImageProcessor.from_pretrained(self.tmpdirname    ,			**_snake_case)


							def 						_snake_case							(			self)							->				List[Any]:
								shutil.rmtree(self.tmpdirname)


							def 						_snake_case							(			self)							->				str:
								UpperCAmelCase_		:      List[str]       	=					[np.random.randint(255    ,			size=(3, 30, 400)    ,			dtype=np.uinta)]

								UpperCAmelCase_		:      List[str]       	=					[Image.fromarray(np.moveaxis(_snake_case    ,			0    ,			-1)) for x in image_inputs]

								return image_inputs


							def 						_snake_case							(			self)							->				List[Any]:
								UpperCAmelCase_		:      Union[str, Any]       	=					self.get_tokenizer()
								UpperCAmelCase_		:      Dict       	=					self.get_rust_tokenizer()
								UpperCAmelCase_		:      List[Any]       	=					self.get_image_processor()

								UpperCAmelCase_		:      Optional[int]       	=					OwlViTProcessor(tokenizer=_snake_case    ,			image_processor=_snake_case)
								processor_slow.save_pretrained(self.tmpdirname)
								UpperCAmelCase_		:      Optional[Any]       	=					OwlViTProcessor.from_pretrained(self.tmpdirname    ,			use_fast=_snake_case)

								UpperCAmelCase_		:      Union[str, Any]       	=					OwlViTProcessor(tokenizer=_snake_case    ,			image_processor=_snake_case)
								processor_fast.save_pretrained(self.tmpdirname)
								UpperCAmelCase_		:      int       	=					OwlViTProcessor.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 						_snake_case							(			self)							->				List[Any]:
								UpperCAmelCase_		:      Union[str, Any]       	=					OwlViTProcessor(tokenizer=self.get_tokenizer()    ,			image_processor=self.get_image_processor())
								processor.save_pretrained(self.tmpdirname)

								UpperCAmelCase_		:      Optional[int]       	=					self.get_tokenizer(bos_token='(BOS)'    ,			eos_token='(EOS)')
								UpperCAmelCase_		:      Any       	=					self.get_image_processor(do_normalize=_snake_case)

								UpperCAmelCase_		:      int       	=					OwlViTProcessor.from_pretrained(
								    self.tmpdirname    ,			bos_token='(BOS)'    ,			eos_token='(EOS)'    ,			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 						_snake_case							(			self)							->				int:
								UpperCAmelCase_		:      Union[str, Any]       	=					self.get_image_processor()
								UpperCAmelCase_		:      Optional[Any]       	=					self.get_tokenizer()

								UpperCAmelCase_		:      List[Any]       	=					OwlViTProcessor(tokenizer=_snake_case    ,			image_processor=_snake_case)

								UpperCAmelCase_		:      List[str]       	=					self.prepare_image_inputs()

								UpperCAmelCase_		:      str       	=					image_processor(_snake_case    ,			return_tensors='np')
								UpperCAmelCase_		:      Union[str, Any]       	=					processor(images=_snake_case    ,			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 						_snake_case							(			self)							->				Union[str, Any]:
								UpperCAmelCase_		:      Any       	=					self.get_image_processor()
								UpperCAmelCase_		:      List[str]       	=					self.get_tokenizer()

								UpperCAmelCase_		:      str       	=					OwlViTProcessor(tokenizer=_snake_case    ,			image_processor=_snake_case)

								UpperCAmelCase_		:      Union[str, Any]       	=					'lower newer'

								UpperCAmelCase_		:      Union[str, Any]       	=					processor(text=_snake_case    ,			return_tensors='np')

								UpperCAmelCase_		:      Dict       	=					tokenizer(_snake_case    ,			return_tensors='np')

								for key in encoded_tok.keys():
									self.assertListEqual(encoded_tok[key][0].tolist()    ,			encoded_processor[key][0].tolist())


							def 						_snake_case							(			self)							->				str:
								UpperCAmelCase_		:      List[str]       	=					self.get_image_processor()
								UpperCAmelCase_		:      Optional[int]       	=					self.get_tokenizer()

								UpperCAmelCase_		:      List[Any]       	=					OwlViTProcessor(tokenizer=_snake_case    ,			image_processor=_snake_case)

								UpperCAmelCase_		:      Tuple       	=					'lower newer'
								UpperCAmelCase_		:      Union[str, Any]       	=					self.prepare_image_inputs()

								UpperCAmelCase_		:      str       	=					processor(text=_snake_case    ,			images=_snake_case)

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

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


							def 						_snake_case							(			self)							->				int:
								UpperCAmelCase_		:      str       	=					'google/owlvit-base-patch32'
								UpperCAmelCase_		:      Any       	=					OwlViTProcessor.from_pretrained(_snake_case)

								UpperCAmelCase_		:      List[Any]       	=					['cat', 'nasa badge']
								UpperCAmelCase_		:      Any       	=					processor(text=_snake_case)

								UpperCAmelCase_		:      int       	=					16
								self.assertListEqual(list(inputs.keys())    ,			['input_ids', 'attention_mask'])
								self.assertEqual(inputs['input_ids'].shape    ,			(2, seq_length))

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


							def 						_snake_case							(			self)							->				int:
								UpperCAmelCase_		:      str       	=					'google/owlvit-base-patch32'
								UpperCAmelCase_		:      List[str]       	=					OwlViTProcessor.from_pretrained(_snake_case)

								UpperCAmelCase_		:      str       	=					[['cat', 'nasa badge'], ['person']]
								UpperCAmelCase_		:      List[Any]       	=					processor(text=_snake_case)

								UpperCAmelCase_		:      List[str]       	=					16
								UpperCAmelCase_		:      Optional[int]       	=					len(_snake_case)
								UpperCAmelCase_		:      List[Any]       	=					max([len(_snake_case) for texts in input_texts])

								self.assertListEqual(list(inputs.keys())    ,			['input_ids', 'attention_mask'])
								self.assertEqual(inputs['input_ids'].shape    ,			(batch_size * num_max_text_queries, seq_length))

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


							def 						_snake_case							(			self)							->				Dict:
								UpperCAmelCase_		:      Union[str, Any]       	=					'google/owlvit-base-patch32'
								UpperCAmelCase_		:      List[Any]       	=					OwlViTProcessor.from_pretrained(_snake_case)

								UpperCAmelCase_		:      str       	=					['cat', 'nasa badge']
								UpperCAmelCase_		:      str       	=					processor(text=_snake_case)

								UpperCAmelCase_		:      Dict       	=					16
								UpperCAmelCase_		:      int       	=					inputs['input_ids']
								UpperCAmelCase_		:      Optional[int]       	=					[
								    [4_9406, 2368, 4_9407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
								    [4_9406, 6841, 1_1301, 4_9407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
								]

								self.assertListEqual(list(inputs.keys())    ,			['input_ids', 'attention_mask'])
								self.assertEqual(inputs['input_ids'].shape    ,			(2, seq_length))
								self.assertListEqual(list(input_ids[0])    ,			predicted_ids[0])
								self.assertListEqual(list(input_ids[1])    ,			predicted_ids[1])


							def 						_snake_case							(			self)							->				Any:
								UpperCAmelCase_		:      Tuple       	=					self.get_image_processor()
								UpperCAmelCase_		:      List[Any]       	=					self.get_tokenizer()

								UpperCAmelCase_		:      int       	=					OwlViTProcessor(tokenizer=_snake_case    ,			image_processor=_snake_case)

								UpperCAmelCase_		:      Optional[Any]       	=					self.prepare_image_inputs()
								UpperCAmelCase_		:      Optional[int]       	=					self.prepare_image_inputs()

								UpperCAmelCase_		:      str       	=					processor(images=_snake_case    ,			query_images=_snake_case)

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

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





							def 						_snake_case							(			self)							->				List[str]:
								UpperCAmelCase_		:      Union[str, Any]       	=					self.get_image_processor()
								UpperCAmelCase_		:      Tuple       	=					self.get_tokenizer()

								UpperCAmelCase_		:      str       	=					OwlViTProcessor(tokenizer=_snake_case    ,			image_processor=_snake_case)

								UpperCAmelCase_		:      int       	=					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

								UpperCAmelCase_		:      Union[str, Any]       	=					processor.batch_decode(_snake_case)
								UpperCAmelCase_		:      Union[str, Any]       	=					tokenizer.batch_decode(_snake_case)

								self.assertListEqual(_snake_case    ,			_snake_case)





'''simple docstring'''


from __future__ import annotations

import requests

lowerCAmelCase__										= set(
    "approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories created_utc downs\nedited gilded gildings hidden hide_score is_created_from_ads_ui is_meta\nis_original_content is_reddit_media_domain is_video link_flair_css_class\nlink_flair_richtext link_flair_text link_flair_text_color media_embed mod_reason_title\nname permalink pwls quarantine saved score secure_media secure_media_embed selftext\nsubreddit subreddit_name_prefixed subreddit_type thumbnail title top_awarded_type\ntotal_awards_received ups upvote_ratio url user_reports".split()
)







def 						SCREAMING_SNAKE_CASE(  UpperCamelCase   ,UpperCamelCase = 1   ,UpperCamelCase = "new"   ,UpperCamelCase = None  )    ->    dict:
	UpperCAmelCase_		:      Dict       	=					wanted_data or []
	if invalid_search_terms := ", ".join(sorted(set(UpperCamelCase  ) - valid_terms  )  ):
		UpperCAmelCase_		:      str       	=					f"""Invalid search term: {invalid_search_terms}"""
		raise ValueError(UpperCamelCase  )
	UpperCAmelCase_		:      Dict       	=					requests.get(
	    f"""https://reddit.com/r/{subreddit}/{age}.json?limit={limit}"""   ,headers={'User-agent': 'A random string'}   ,)
	if response.status_code == 4_2_9:
		raise requests.HTTPError

	UpperCAmelCase_		:      int       	=					response.json()
	if not wanted_data:
		return {id_: data["data"]["children"][id_] for id_ in range(UpperCamelCase  )}

	UpperCAmelCase_		:      List[str]       	=					{}
	for id_ in range(UpperCamelCase  ):
		UpperCAmelCase_		:      Tuple       	=					{
		    item: data['data']['children'][id_]['data'][item] for item in wanted_data
		}
	return data_dict


if __name__ == "__main__":
						# If you get Error 429, that means you are rate limited.Try after some time
						print(get_subreddit_data("learnpython", wanted_data=["title", "url", "selftext"]))






