


"""simple docstring"""


import argparse
import os
import re

import packaging.version


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


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




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


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			for folder, directories, fnames in os.walk(_UpperCamelCase      ):
						# 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(_UpperCamelCase    , _UpperCamelCase      )    , _UpperCamelCase    , pattern="examples"      )


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase=False      ):

			'''simple docstring'''




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


def _lowerCamelCase	(		):

			'''simple docstring'''




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

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

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

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


def _lowerCamelCase	(		):

			'''simple docstring'''




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


def _lowerCamelCase	(		_UpperCamelCase=False      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			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:
						__lowerCAmelCase				    =			default_version.base_version
			elif patch:
						__lowerCAmelCase				    =			f"{default_version.major}.{default_version.minor}.{default_version.micro + 1}"
			else:
						__lowerCAmelCase				    =			f"{default_version.major}.{default_version.minor + 1}.0"

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

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


def _lowerCamelCase	(		):

			'''simple docstring'''




			__lowerCAmelCase				    =			get_version()
			__lowerCAmelCase				    =			f"{current_version.major}.{current_version.minor + 1}.0.dev0"
			__lowerCAmelCase				    =			current_version.base_version

			# Check with the user we got that right.
			__lowerCAmelCase				    =			input(f"Which version are we developing now? [{dev_version}]"      )
			if len(_UpperCamelCase      ) == 0:
						__lowerCAmelCase				    =			dev_version

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


if __name__ == "__main__":
	A     :   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.")
	A     :   Dict			    =			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()








"""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 FEATURE_EXTRACTOR_NAME, is_vision_available


if is_vision_available():
	from PIL import Image

	from transformers import ChineseCLIPImageProcessor, ChineseCLIPProcessor
@require_vision
class   _UpperCamelCase  (   unittest.TestCase		):
							'''simple docstring'''







							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			tempfile.mkdtemp()

										__lowerCAmelCase				    =			[
										    "[UNK]",
										    "[CLS]",
										    "[SEP]",
										    "[PAD]",
										    "[MASK]",
										    "的",
										    "价",
										    "格",
										    "是",
										    "15",
										    "便",
										    "alex",
										    "##andra",
										    "，",
										    "。",
										    "-",
										    "t",
										    "shirt",
										]
										__lowerCAmelCase				    =			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]	)	)

										__lowerCAmelCase				    =			{
										    "do_resize": True,
										    "size": {"height": 2_24, "width": 2_24},
										    "do_center_crop": True,
										    "crop_size": {"height": 18, "width": 18},
										    "do_normalize": True,
										    "image_mean": [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
										    "image_std": [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
										    "do_convert_rgb": True,
										}
										__lowerCAmelCase				    =			os.path.join(self.tmpdirname    ,   __a	)
										with open(self.image_processor_file    ,   "w"    ,   encoding="utf-8"	) as fp:
													json.dump(__a    ,   __a	)

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

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

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

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

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

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

										return image_inputs

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_tokenizer()
										__lowerCAmelCase				    =			self.get_rust_tokenizer()
										__lowerCAmelCase				    =			self.get_image_processor()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)
										processor_slow.save_pretrained(self.tmpdirname	)
										__lowerCAmelCase				    =			ChineseCLIPProcessor.from_pretrained(self.tmpdirname    ,   use_fast=__a	)

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)
										processor_fast.save_pretrained(self.tmpdirname	)
										__lowerCAmelCase				    =			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    ,   __a	)
										self.assertIsInstance(processor_fast.tokenizer    ,   __a	)

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

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

										__lowerCAmelCase				    =			self.get_tokenizer(cls_token="(CLS)"    ,   sep_token="(SEP)"	)
										__lowerCAmelCase				    =			self.get_image_processor(do_normalize=__a	)

										__lowerCAmelCase				    =			ChineseCLIPProcessor.from_pretrained(
										    self.tmpdirname    ,   cls_token="(CLS)"    ,   sep_token="(SEP)"    ,   do_normalize=__a	)

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

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			self.prepare_image_inputs()

										__lowerCAmelCase				    =			image_processor(__a    ,   return_tensors="np"	)
										__lowerCAmelCase				    =			processor(images=__a    ,   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 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			"Alexandra，T-shirt的价格是15便士。"

										__lowerCAmelCase				    =			processor(text=__a	)

										__lowerCAmelCase				    =			tokenizer(__a	)

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

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			"Alexandra，T-shirt的价格是15便士。"
										__lowerCAmelCase				    =			self.prepare_image_inputs()

										__lowerCAmelCase				    =			processor(text=__a    ,   images=__a	)

										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(__a	):
													processor()

							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

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

										__lowerCAmelCase				    =			processor.batch_decode(__a	)
										__lowerCAmelCase				    =			tokenizer.batch_decode(__a	)

										self.assertListEqual(__a    ,   __a	)



							def 			snake_case				(     self	):
										__lowerCAmelCase				    =			self.get_image_processor()
										__lowerCAmelCase				    =			self.get_tokenizer()

										__lowerCAmelCase				    =			ChineseCLIPProcessor(tokenizer=__a    ,   image_processor=__a	)

										__lowerCAmelCase				    =			"Alexandra，T-shirt的价格是15便士。"
										__lowerCAmelCase				    =			self.prepare_image_inputs()

										__lowerCAmelCase				    =			processor(text=__a    ,   images=__a	)

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




