





import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin



class    _a     (				lowercase__					,							unittest.TestCase							):






							"""simple docstring"""

							snake_case_							 =						BioGptTokenizer
							snake_case_							 =						False

							def      A_  (      self				:     int    )	->Any:
													super().setUp()

													# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
													SCREAMING_SNAKE_CASE__     :				List[str]   =					[
													    "l",
													    "o",
													    "w",
													    "e",
													    "r",
													    "s",
													    "t",
													    "i",
													    "d",
													    "n",
													    "w</w>",
													    "r</w>",
													    "t</w>",
													    "lo",
													    "low",
													    "er</w>",
													    "low</w>",
													    "lowest</w>",
													    "newer</w>",
													    "wider</w>",
													    "<unk>",
													]
													SCREAMING_SNAKE_CASE__     :				Dict   =					dict(zip(a							,	range(len(a    )    )    )    )
													SCREAMING_SNAKE_CASE__     :				List[str]   =					["l o 123", "lo w 1456", "e r</w> 1789", ""]

													SCREAMING_SNAKE_CASE__     :				Any   =					os.path.join(self.tmpdirname							,	VOCAB_FILES_NAMES["vocab_file"]    )
													SCREAMING_SNAKE_CASE__     :				Tuple   =					os.path.join(self.tmpdirname							,	VOCAB_FILES_NAMES["merges_file"]    )
													with open(self.vocab_file							,	"w"    ) as fp:
																			fp.write(json.dumps(a    )    )
													with open(self.merges_file							,	"w"    ) as fp:
																			fp.write("\n".join(a    )    )

							def      A_  (      self				:     List[str]							,	a				:     Optional[int]    )	->Tuple:
													SCREAMING_SNAKE_CASE__     :				Optional[int]   =					"lower newer"
													SCREAMING_SNAKE_CASE__     :				str   =					"lower newer"
													return input_text, output_text

							def      A_  (      self				:     Optional[int]    )	->Tuple:
													SCREAMING_SNAKE_CASE__     :				Optional[int]   =					BioGptTokenizer(self.vocab_file							,	self.merges_file    )

													SCREAMING_SNAKE_CASE__     :				Optional[int]   =					"lower"
													SCREAMING_SNAKE_CASE__     :				Tuple   =					["low", "er</w>"]
													SCREAMING_SNAKE_CASE__     :				Any   =					tokenizer.tokenize(a    )
													self.assertListEqual(a							,	a    )

													SCREAMING_SNAKE_CASE__     :				Dict   =					tokens + ["<unk>"]
													SCREAMING_SNAKE_CASE__     :				Any   =					[14, 15, 20]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(a    )							,	a    )






							@slow
							def      A_  (      self				:     Dict    )	->Optional[Any]:
													SCREAMING_SNAKE_CASE__     :				str   =					BioGptTokenizer.from_pretrained("microsoft/biogpt"    )

													SCREAMING_SNAKE_CASE__     :				List[str]   =					tokenizer.encode("sequence builders"							,	add_special_tokens=a    )
													SCREAMING_SNAKE_CASE__     :				Dict   =					tokenizer.encode("multi-sequence build"							,	add_special_tokens=a    )

													SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					tokenizer.build_inputs_with_special_tokens(a    )
													SCREAMING_SNAKE_CASE__     :				Optional[Any]   =					tokenizer.build_inputs_with_special_tokens(a							,	a    )

													self.assertTrue(encoded_sentence == [2] + text    )
													self.assertTrue(encoded_pair == [2] + text + [2] + text_a    )






import sys

from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

__lowercase       :List[Any]       =  "python tqdm regex requests packaging filelock numpy tokenizers".split()
if sys.version_info < (3, 7):
				pkgs_to_check_at_runtime.append("dataclasses")
if sys.version_info < (3, 8):
				pkgs_to_check_at_runtime.append("importlib_metadata")

for pkg in pkgs_to_check_at_runtime:
				if pkg in deps:
								if pkg == "tokenizers":
												# must be loaded here, or else tqdm check may fail
												from .utils import is_tokenizers_available

												if not is_tokenizers_available():
																continue  # not required, check version only if installed

								require_version_core(deps[pkg])
				else:
								raise ValueError(f"can't find {pkg} in {deps.keys()}, check dependency_versions_table.py")







def       UpperCAmelCase							(     _lowerCamelCase      :  Optional[Any]			,   _lowerCamelCase      :  Optional[Any]=None     ):





						'''simple docstring'''


						require_version(deps[pkg]			,   _lowerCamelCase     )