

"""simple docstring"""




import copy

from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging


__A	:       Dict        =						logging.get_logger(__name__)





class      __UpperCamelCase					(  _A		):
		SCREAMING_SNAKE_CASE														=       "hybrid-clip"
		SCREAMING_SNAKE_CASE														=       True


		def __init__(self					:						str	,	__SCREAMING_SNAKE_CASE					:						str=5_1_2	,	**__SCREAMING_SNAKE_CASE					:						str):
							super().__init__(**__SCREAMING_SNAKE_CASE)

							if "text_config" not in kwargs:
												raise ValueError("`text_config` can not be `None`.")

							if "vision_config" not in kwargs:
												raise ValueError("`vision_config` can not be `None`.")

							A     =   kwargs.pop("text_config")
							A     =   kwargs.pop("vision_config")

							A     =   text_config.pop("model_type")
							A     =   vision_config.pop("model_type")

							from transformers import AutoConfig

							A     =   AutoConfig.for_model(__SCREAMING_SNAKE_CASE	,	**__SCREAMING_SNAKE_CASE)

							if vision_model_type == "clip":
												A     =   AutoConfig.for_model(__SCREAMING_SNAKE_CASE	,	**__SCREAMING_SNAKE_CASE).vision_config
							elif vision_model_type == "clip_vision_model":
												from transformers import CLIPVisionConfig

												A     =   CLIPVisionConfig(**__SCREAMING_SNAKE_CASE)
							else:
												A     =   AutoConfig.for_model(__SCREAMING_SNAKE_CASE	,	**__SCREAMING_SNAKE_CASE)

							A     =   projection_dim
							A     =   1.0


		@classmethod
		def    SCREAMING_SNAKE_CASE__  (cls					:						List[Any]	,	__SCREAMING_SNAKE_CASE					:						PretrainedConfig	,	__SCREAMING_SNAKE_CASE					:						PretrainedConfig	,	**__SCREAMING_SNAKE_CASE					:						Union[str, Any]):
							return cls(text_config=text_config.to_dict()	,	vision_config=vision_config.to_dict()	,	**__SCREAMING_SNAKE_CASE)


		def    SCREAMING_SNAKE_CASE__  (self					:						Optional[Any]):
							A     =   copy.deepcopy(self.__dict__)
							A     =   self.text_config.to_dict()
							A     =   self.vision_config.to_dict()
							A     =   self.__class__.model_type
							return output








"""simple docstring"""




import os
import tempfile
import unittest
from typing import List

from transformers.models.esm.tokenization_esm import VOCAB_FILES_NAMES, EsmTokenizer
from transformers.testing_utils import require_tokenizers
from transformers.tokenization_utils import PreTrainedTokenizer
from transformers.tokenization_utils_base import PreTrainedTokenizerBase





@require_tokenizers
class      __UpperCamelCase					(  unittest.TestCase		):
		SCREAMING_SNAKE_CASE														=       EsmTokenizer


		def    SCREAMING_SNAKE_CASE__  (self					:						Tuple):
							super().setUp()
							A     =   tempfile.mkdtemp()
							# fmt: off
							A     =   ["<cls>", "<pad>", "<eos>", "<unk>", "L", "A", "G", "V", "S", "E", "R", "T", "I", "D", "P", "K", "Q", "N", "F", "Y", "M", "H", "W", "C", "X", "B", "U", "Z", "O", ".", "-", "<null_1>", "<mask>"]  # noqa: E501
							# fmt: on
							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]))


		def    SCREAMING_SNAKE_CASE__  (self					:						Any	,	**__SCREAMING_SNAKE_CASE					:						str):
							return [self.get_tokenizer(**__SCREAMING_SNAKE_CASE)]


		def    SCREAMING_SNAKE_CASE__  (self					:						Union[str, Any]	,	**__SCREAMING_SNAKE_CASE					:						Optional[Any]):
							return self.tokenizer_class.from_pretrained(self.tmpdirname	,	**__SCREAMING_SNAKE_CASE)


		def    SCREAMING_SNAKE_CASE__  (self					:						List[Any]):
							A     =   self.tokenizer_class(self.vocab_file)

							A     =   tokenizer.tokenize("LAGVS")
							self.assertListEqual(__SCREAMING_SNAKE_CASE	,	["L", "A", "G", "V", "S"])
							self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE)	,	[4, 5, 6, 7, 8])


		def    SCREAMING_SNAKE_CASE__  (self					:						List[Any]):
							A     =   self.tokenizer_class(self.vocab_file)

							A     =   "LAGVS"
							self.assertListEqual(tokenizer.encode(__SCREAMING_SNAKE_CASE)	,	[0, 4, 5, 6, 7, 8, 2])


		def    SCREAMING_SNAKE_CASE__  (self					:						List[str]):
							A     =   self.tokenizer_class(self.vocab_file)

							A     =   ["LAGVS", "WCB"]
							A     =   tokenizer(__SCREAMING_SNAKE_CASE	,	padding=__SCREAMING_SNAKE_CASE)["input_ids"]

							self.assertListEqual(__SCREAMING_SNAKE_CASE	,	[[0, 4, 5, 6, 7, 8, 2], [0, 2_2, 2_3, 2_5, 2]])


		def    SCREAMING_SNAKE_CASE__  (self					:						str):
							A     =   self.tokenizer_class(self.vocab_file)

							A     =   ["LAGVS", "WCB"]
							A     =   tokenizer(__SCREAMING_SNAKE_CASE	,	padding=__SCREAMING_SNAKE_CASE)["input_ids"]

							self.assertListEqual(__SCREAMING_SNAKE_CASE	,	[[0, 4, 5, 6, 7, 8, 2], [0, 2_2, 2_3, 2_5, 2, 1, 1]])


		def    SCREAMING_SNAKE_CASE__  (self					:						Tuple):
							A     =   self.get_tokenizers(fast=__SCREAMING_SNAKE_CASE)
							for tokenizer in tokenizers:
												with self.subTest(F"""{tokenizer.__class__.__name__}"""):
																	A     =   "<unk>"
																	A     =   "<mask>"

																	A     =   tokenizer.tokenize(__SCREAMING_SNAKE_CASE)
																	A     =   tokenizer.tokenize(__SCREAMING_SNAKE_CASE)

																	self.assertEqual(len(__SCREAMING_SNAKE_CASE)	,	1)
																	self.assertEqual(len(__SCREAMING_SNAKE_CASE)	,	1)
																	self.assertEqual(token_a[0]	,	__SCREAMING_SNAKE_CASE)
																	self.assertEqual(token_a[0]	,	__SCREAMING_SNAKE_CASE)





