
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 							UpperCAmelCase				(  unittest.TestCase  ):




	'''simple docstring'''





	def     UpperCamelCase_  (	self :			Union[str, Any]			):
					__A             =			tempfile.mkdtemp()

					# fmt: off
					__A             =			["", "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
					__A             =			dict(zip(_lowerCamelCase							,range(len(_lowerCamelCase			)			)			)			)
					__A             =			["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
					__A             =			{"unk_token": "<unk>"}

					__A             =			os.path.join(self.tmpdirname							,VOCAB_FILES_NAMES["vocab_file"]			)
					__A             =			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(_lowerCamelCase			) + "\n"			)
					with open(self.merges_file							,"w"							,encoding="utf-8"			) as fp:
									fp.write("\n".join(_lowerCamelCase			)			)

					__A             =			{
					    "do_resize": True,
					    "size": 20,
					    "do_center_crop": True,
					    "crop_size": 18,
					    "do_normalize": True,
					    "image_mean": [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
					    "image_std": [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
					}
					__A             =			os.path.join(self.tmpdirname							,_lowerCamelCase			)
					with open(self.image_processor_file							,"w"							,encoding="utf-8"			) as fp:
									json.dump(_lowerCamelCase							,_lowerCamelCase			)






	def     UpperCamelCase_  (	self :			Optional[Any]							,**A :			List[str]			):
					return CLIPTokenizer.from_pretrained(self.tmpdirname							,pad_token="!"							,**_lowerCamelCase			)






	def     UpperCamelCase_  (	self :			Any							,**A :			List[str]			):
					return CLIPTokenizerFast.from_pretrained(self.tmpdirname							,pad_token="!"							,**_lowerCamelCase			)






	def     UpperCamelCase_  (	self :			str							,**A :			Any			):
					return OwlViTImageProcessor.from_pretrained(self.tmpdirname							,**_lowerCamelCase			)






	def     UpperCamelCase_  (	self :			Tuple			):
					shutil.rmtree(self.tmpdirname			)






	def     UpperCamelCase_  (	self :			Dict			):
					__A             =			[np.random.randint(2_55							,size=(3, 30, 4_00)							,dtype=np.uinta			)]

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

					return image_inputs






	def     UpperCamelCase_  (	self :			List[Any]			):
					__A             =			self.get_tokenizer()
					__A             =			self.get_rust_tokenizer()
					__A             =			self.get_image_processor()

					__A             =			OwlViTProcessor(tokenizer=_lowerCamelCase							,image_processor=_lowerCamelCase			)
					processor_slow.save_pretrained(self.tmpdirname			)
					__A             =			OwlViTProcessor.from_pretrained(self.tmpdirname							,use_fast=_lowerCamelCase			)

					__A             =			OwlViTProcessor(tokenizer=_lowerCamelCase							,image_processor=_lowerCamelCase			)
					processor_fast.save_pretrained(self.tmpdirname			)
					__A             =			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							,_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     UpperCamelCase_  (	self :			Optional[int]			):
					__A             =			OwlViTProcessor(tokenizer=self.get_tokenizer()							,image_processor=self.get_image_processor()			)
					processor.save_pretrained(self.tmpdirname			)

					__A             =			self.get_tokenizer(bos_token="(BOS)"							,eos_token="(EOS)"			)
					__A             =			self.get_image_processor(do_normalize=_lowerCamelCase			)

					__A             =			OwlViTProcessor.from_pretrained(
					    self.tmpdirname							,bos_token="(BOS)"							,eos_token="(EOS)"							,do_normalize=_lowerCamelCase			)

					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     UpperCamelCase_  (	self :			Dict			):
					__A             =			self.get_image_processor()
					__A             =			self.get_tokenizer()

					__A             =			OwlViTProcessor(tokenizer=_lowerCamelCase							,image_processor=_lowerCamelCase			)

					__A             =			self.prepare_image_inputs()

					__A             =			image_processor(_lowerCamelCase							,return_tensors="np"			)
					__A             =			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     UpperCamelCase_  (	self :			Optional[Any]			):
					__A             =			self.get_image_processor()
					__A             =			self.get_tokenizer()

					__A             =			OwlViTProcessor(tokenizer=_lowerCamelCase							,image_processor=_lowerCamelCase			)

					__A             =			"lower newer"

					__A             =			processor(text=_lowerCamelCase							,return_tensors="np"			)

					__A             =			tokenizer(_lowerCamelCase							,return_tensors="np"			)

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






	def     UpperCamelCase_  (	self :			Optional[Any]			):
					__A             =			self.get_image_processor()
					__A             =			self.get_tokenizer()

					__A             =			OwlViTProcessor(tokenizer=_lowerCamelCase							,image_processor=_lowerCamelCase			)

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

					__A             =			processor(text=_lowerCamelCase							,images=_lowerCamelCase			)

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

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






	def     UpperCamelCase_  (	self :			Optional[int]			):
					__A             =			"google/owlvit-base-patch32"
					__A             =			OwlViTProcessor.from_pretrained(_lowerCamelCase			)

					__A             =			["cat", "nasa badge"]
					__A             =			processor(text=_lowerCamelCase			)

					__A             =			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(_lowerCamelCase			):
									processor()






	def     UpperCamelCase_  (	self :			Optional[int]			):
					__A             =			"google/owlvit-base-patch32"
					__A             =			OwlViTProcessor.from_pretrained(_lowerCamelCase			)

					__A             =			[["cat", "nasa badge"], ["person"]]
					__A             =			processor(text=_lowerCamelCase			)

					__A             =			16
					__A             =			len(_lowerCamelCase			)
					__A             =			max([len(_lowerCamelCase			) 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(_lowerCamelCase			):
									processor()






	def     UpperCamelCase_  (	self :			Union[str, Any]			):
					__A             =			"google/owlvit-base-patch32"
					__A             =			OwlViTProcessor.from_pretrained(_lowerCamelCase			)

					__A             =			["cat", "nasa badge"]
					__A             =			processor(text=_lowerCamelCase			)

					__A             =			16
					__A             =			inputs["input_ids"]
					__A             =			[
					    [4_94_06, 23_68, 4_94_07, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
					    [4_94_06, 68_41, 1_13_01, 4_94_07, 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     UpperCamelCase_  (	self :			List[str]			):
					__A             =			self.get_image_processor()
					__A             =			self.get_tokenizer()

					__A             =			OwlViTProcessor(tokenizer=_lowerCamelCase							,image_processor=_lowerCamelCase			)

					__A             =			self.prepare_image_inputs()
					__A             =			self.prepare_image_inputs()

					__A             =			processor(images=_lowerCamelCase							,query_images=_lowerCamelCase			)

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

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







	def     UpperCamelCase_  (	self :			str			):
					__A             =			self.get_image_processor()
					__A             =			self.get_tokenizer()

					__A             =			OwlViTProcessor(tokenizer=_lowerCamelCase							,image_processor=_lowerCamelCase			)

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

					__A             =			processor.batch_decode(_lowerCamelCase			)
					__A             =			tokenizer.batch_decode(_lowerCamelCase			)

					self.assertListEqual(_lowerCamelCase							,_lowerCamelCase			)


import argparse
import os
import re

import packaging.version


SCREAMING_SNAKE_CASE							:int										=    'examples/'
SCREAMING_SNAKE_CASE							:str										=    {
    'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
    'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__version__ = "VERSION"\n'),
    'setup': (re.compile(R'^(\s*)version\s*=\s*"[^"]+",', re.MULTILINE), R'\1version="VERSION",'),
    'doc': (re.compile(R'^(\s*)release\s*=\s*"[^"]+"$', re.MULTILINE), 'release = "VERSION"\n'),
}
SCREAMING_SNAKE_CASE							:int										=    {
    'init': 'src/diffusers/__init__.py',
    'setup': 'setup.py',
}
SCREAMING_SNAKE_CASE							:List[str]										=    'README.md'


def 						UpperCAmelCase      (     a_		,       a_		,       a_						)		->     Tuple:







				"""simple docstring"""



				with open(a_		,       "r"		,       encoding="utf-8"		,       newline="\n"						) as f:
								__A             =			f.read()
				__A      ,							__A             =			REPLACE_PATTERNS[pattern]
				__A             =			replace.replace("VERSION"		,       a_						)
				__A             =			re_pattern.sub(a_		,       a_						)
				with open(a_		,       "w"		,       encoding="utf-8"		,       newline="\n"						) as f:
								f.write(a_						)


def 						UpperCAmelCase      (     a_						)		->     Optional[Any]:







				"""simple docstring"""



				for folder, directories, fnames in os.walk(a_						):
								# Removing some of the folders with non-actively maintained examples from the walk
								if "research_projects" in directories:
												directories.remove("research_projects"						)
								if "legacy" in directories:
												directories.remove("legacy"						)
								for fname in fnames:
												if fname.endswith(".py"						):
																update_version_in_file(os.path.join(a_		,       a_						)		,       a_		,       pattern="examples"						)


def 						UpperCAmelCase      (     a_		,       a_=False						)		->     str:







				"""simple docstring"""



				for pattern, fname in REPLACE_FILES.items():
								update_version_in_file(a_		,       a_		,       a_						)
				if not patch:
								update_version_in_examples(a_						)


def 						UpperCAmelCase      (     )		->     Optional[int]:







				"""simple docstring"""



				__A             =			"🤗 Transformers currently provides the following architectures"
				__A             =			"1. Want to contribute a new model?"
				with open(a_		,       "r"		,       encoding="utf-8"		,       newline="\n"						) as f:
								__A             =			f.readlines()

				# Find the start of the list.
				__A             =			0
				while not lines[start_index].startswith(_start_prompt						):
								start_index += 1
				start_index += 1

				__A             =			start_index
				# Update the lines in the model list.
				while not lines[index].startswith(_end_prompt						):
								if lines[index].startswith("1."						):
												__A             =			lines[index].replace(
												    "https://huggingface.co/docs/diffusers/main/model_doc"		,       "https://huggingface.co/docs/diffusers/model_doc"		,       )
								index += 1

				with open(a_		,       "w"		,       encoding="utf-8"		,       newline="\n"						) as f:
								f.writelines(a_						)


def 						UpperCAmelCase      (     )		->     Dict:







				"""simple docstring"""



				with open(REPLACE_FILES["init"]		,       "r"						) as f:
								__A             =			f.read()
				__A             =			REPLACE_PATTERNS["init"][0].search(a_						).groups()[0]
				return packaging.version.parse(a_						)


def 						UpperCAmelCase      (     a_=False						)		->     str:







				"""simple docstring"""



				__A             =			get_version()
				if patch and default_version.is_devrelease:
								raise ValueError("Can't create a patch version from the dev branch, checkout a released version!"						)
				if default_version.is_devrelease:
								__A             =			default_version.base_version
				elif patch:
								__A             =			F'''{default_version.major}.{default_version.minor}.{default_version.micro + 1}'''
				else:
								__A             =			F'''{default_version.major}.{default_version.minor + 1}.0'''

				# Now let's ask nicely if that's the right one.
				__A             =			input(F'''Which version are you releasing? [{default_version}]'''						)
				if len(a_						) == 0:
								__A             =			default_version

				print(F'''Updating version to {version}.'''						)
				global_version_update(a_		,       patch=a_						)


def 						UpperCAmelCase      (     )		->     Optional[int]:







				"""simple docstring"""



				__A             =			get_version()
				__A             =			F'''{current_version.major}.{current_version.minor + 1}.0.dev0'''
				__A             =			current_version.base_version

				# Check with the user we got that right.
				__A             =			input(F'''Which version are we developing now? [{dev_version}]'''						)
				if len(a_						) == 0:
								__A             =			dev_version

				print(F'''Updating version to {version}.'''						)
				global_version_update(a_						)


#    print("Cleaning main README, don't forget to run `make fix-copies`.")
#    clean_main_ref_in_model_list()


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE							:Union[str, Any]										=    argparse.ArgumentParser()
					parser.add_argument('--post_release', action='store_true', help='Whether this is pre or post release.')
					parser.add_argument('--patch', action='store_true', help='Whether or not this is a patch release.')
					SCREAMING_SNAKE_CASE							:List[str]										=    parser.parse_args()
					if not args.post_release:
										pre_release_work(patch=args.patch)
					elif args.patch:
										print('Nothing to do after a patch :-)')
					else:
										post_release_work()
