





'''simple docstring'''


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       UpperCamelCase__  (		unittest.TestCase     ):







	def 						__a   (				self			:   Dict		):




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

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

				a__     = {
				    "do_resize": True,
				    "size": 2_0,
				    "do_center_crop": True,
				    "crop_size": 1_8,
				    "do_normalize": True,
				    "image_mean": [0.48145466, 0.4578275, 0.40821073],
				    "image_std": [0.26862954, 0.26130258, 0.27577711],
				}
				a__     = os.path.join(self.tmpdirname , lowerCamelCase		)
				with open(self.image_processor_file , "w" , encoding="utf-8"		) as fp:
							json.dump(lowerCamelCase , lowerCamelCase		)







	def 						__a   (				self			:   Optional[int] , **lowerCamelCase			:   int		):




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







	def 						__a   (				self			:   List[Any] , **lowerCamelCase			:   List[Any]		):




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







	def 						__a   (				self			:   Optional[int] , **lowerCamelCase			:   Optional[int]		):




				'''simple docstring'''
				return EfficientNetImageProcessor.from_pretrained(self.tmpdirname , **lowerCamelCase		)







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




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







	def 						__a   (				self			:   List[Any]		):




				'''simple docstring'''
				a__     = [np.random.randint(2_5_5 , size=(3, 3_0, 4_0_0) , dtype=np.uinta		)]
				a__     = [Image.fromarray(np.moveaxis(lowerCamelCase , 0 , -1		)		) for x in image_inputs]
				return image_inputs







	def 						__a   (				self			:   Any		):




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

				a__     = AlignProcessor(tokenizer=lowerCamelCase , image_processor=lowerCamelCase		)
				processor_slow.save_pretrained(self.tmpdirname		)
				a__     = AlignProcessor.from_pretrained(self.tmpdirname , use_fast=lowerCamelCase		)

				a__     = AlignProcessor(tokenizer=lowerCamelCase , image_processor=lowerCamelCase		)
				processor_fast.save_pretrained(self.tmpdirname		)
				a__     = 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 						__a   (				self			:   Any		):




				'''simple docstring'''
				a__     = AlignProcessor(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 , padding_value=1.0		)

				a__     = 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 						__a   (				self			:   Union[str, Any]		):




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

				a__     = AlignProcessor(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 						__a   (				self			:   Any		):




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

				a__     = AlignProcessor(tokenizer=lowerCamelCase , image_processor=lowerCamelCase		)

				a__     = "lower newer"

				a__     = processor(text=lowerCamelCase		)

				a__     = tokenizer(lowerCamelCase , padding="max_length" , max_length=6_4		)

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







	def 						__a   (				self			:   Optional[Any]		):




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

				a__     = AlignProcessor(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", "token_type_ids", "attention_mask", "pixel_values"]		)

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







	def 						__a   (				self			:   Optional[Any]		):




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

				a__     = AlignProcessor(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		)







	def 						__a   (				self			:   Optional[int]		):




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

				a__     = AlignProcessor(tokenizer=lowerCamelCase , image_processor=lowerCamelCase		)

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

				a__     = processor(text=lowerCamelCase , images=lowerCamelCase		)

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










'''simple docstring'''


import argparse
import os
import re

import packaging.version


lowerCAmelCase_   :   Optional[int]       =					"examples/"
lowerCAmelCase_   :   Optional[int]       =					{
    "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"),
}
lowerCAmelCase_   :   Optional[int]       =					{
    "init": "src/transformers/__init__.py",
    "setup": "setup.py",
}
lowerCAmelCase_   :   List[Any]       =					"README.md"







def    _lowerCamelCase  (__lowerCamelCase  :     Dict					,  __lowerCamelCase  :     List[Any]					,  __lowerCamelCase  :     Optional[Any]     )   ->    str:
			with open(__lowerCamelCase					,  "r"					,  encoding="utf-8"					,  newline="\n"     ) as f:
						a__     = f.read()
			a__   ,				a__     = REPLACE_PATTERNS[pattern]
			a__     = replace.replace("VERSION"					,  __lowerCamelCase     )
			a__     = re_pattern.sub(__lowerCamelCase					,  __lowerCamelCase     )
			with open(__lowerCamelCase					,  "w"					,  encoding="utf-8"					,  newline="\n"     ) as f:
						f.write(__lowerCamelCase     )







def    _lowerCamelCase  (__lowerCamelCase  :     Union[str, Any]     )   ->    Dict:
			for folder, directories, fnames in os.walk(__lowerCamelCase     ):
						# 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(__lowerCamelCase					,  __lowerCamelCase     )					,  __lowerCamelCase					,  pattern="examples"     )







def    _lowerCamelCase  (__lowerCamelCase  :     int					,  __lowerCamelCase  :     Any=False     )   ->    Optional[Any]:
			for pattern, fname in REPLACE_FILES.items():
						update_version_in_file(__lowerCamelCase					,  __lowerCamelCase					,  __lowerCamelCase     )
			if not patch:
						update_version_in_examples(__lowerCamelCase     )







def    _lowerCamelCase  ()   ->    Tuple:
			a__     = "🤗 Transformers currently provides the following architectures"
			a__     = "1. Want to contribute a new model?"
			with open(__lowerCamelCase					,  "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/transformers/main/model_doc"					,  "https://huggingface.co/docs/transformers/model_doc"					,  )
						index += 1

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







def    _lowerCamelCase  ()   ->    Tuple:
			with open(REPLACE_FILES["init"]					,  "r"     ) as f:
						a__     = f.read()
			a__     = REPLACE_PATTERNS["init"][0].search(__lowerCamelCase     ).groups()[0]
			return packaging.version.parse(__lowerCamelCase     )







def    _lowerCamelCase  (__lowerCamelCase  :     Any=False     )   ->    int:
			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(__lowerCamelCase     ) == 0:
						a__     = default_version

			print(f'''Updating version to {version}.'''     )
			global_version_update(__lowerCamelCase					,  patch=__lowerCamelCase     )
			if not patch:
						print("Cleaning main README, don't forget to run `make fix-copies`."     )
						clean_main_ref_in_model_list()







def    _lowerCamelCase  ()   ->    Tuple:
			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(__lowerCamelCase     ) == 0:
						a__     = dev_version

			print(f'''Updating version to {version}.'''     )
			global_version_update(__lowerCamelCase     )
			print("Cleaning main README, don't forget to run `make fix-copies`."     )
			clean_main_ref_in_model_list()


if __name__ == "__main__":
		lowerCAmelCase_   :   List[str]       =					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.")
		lowerCAmelCase_   :   int       =					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()



