


"""simple docstring"""


import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class snake_case   (	_UpperCamelCase  ,					unittest.TestCase):
		__UpperCamelCase							     =      HerbertTokenizer
		__UpperCamelCase							     =      HerbertTokenizerFast
		__UpperCamelCase							     =      True







		def 			a_			(       self   :							Optional[int]		)							->    str:





						'''simple docstring'''







						super().setUp()

						# Use a simpler test file without japanese/chinese characters
						with open(F"""{get_tests_dir()}/fixtures/sample_text_no_unicode.txt"""     , encoding="utf-8"		) as f_data:
										_A       	=      f_data.read().replace("\n\n"     , "\n"		).strip()

						_A       	=      [
						    "<s>",
						    "</s>",
						    "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>",
						    ",</w>",
						    "<unk>",
						]
						_A       	=      dict(zip(a__     , range(len(a__		)		)		)		)
						_A       	=      ["l o 123", "lo w 1456", "e r</w> 1789", ""]

						_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"		) as fp:
										fp.write(json.dumps(a__		)		)
						with open(self.merges_file     , "w"		) as fp:
										fp.write("\n".join(a__		)		)







		def 			a_			(       self   :							Optional[int]     , a__   :							int		)							->    List[Any]:





						'''simple docstring'''







						_A       	=      "lower newer"
						_A       	=      "lower newer"
						return input_text, output_text







		def 			a_			(       self   :							Optional[int]		)							->    Union[str, Any]:





						'''simple docstring'''







						_A       	=      self.tokenizer_class(vocab_file=self.vocab_file     , merges_file=self.merges_file		)

						_A       	=      "lower"
						_A       	=      ["low", "er</w>"]
						_A       	=      tokenizer.tokenize(a__		)
						self.assertListEqual(a__     , a__		)

						_A       	=      tokens + ["<unk>"]
						_A       	=      [16, 17, 23]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(a__		)     , a__		)







		def 			a_			(       self   :							Optional[Any]		)							->    List[str]:





						'''simple docstring'''







						if not self.test_rust_tokenizer:
										return

						_A       	=      self.get_tokenizer()
						_A       	=      self.get_rust_tokenizer()

						_A       	=      "lower,newer"

						_A       	=      tokenizer.tokenize(a__		)
						_A       	=      rust_tokenizer.tokenize(a__		)
						self.assertListEqual(a__     , a__		)

						_A       	=      tokenizer.encode(a__     , add_special_tokens=a__		)
						_A       	=      rust_tokenizer.encode(a__     , add_special_tokens=a__		)
						self.assertListEqual(a__     , a__		)

						_A       	=      self.get_rust_tokenizer()
						_A       	=      tokenizer.encode(a__		)
						_A       	=      rust_tokenizer.encode(a__		)
						self.assertListEqual(a__     , a__		)







		@slow
		def 			a_			(       self   :							List[Any]		)							->    Optional[int]:





						'''simple docstring'''







						_A       	=      self.tokenizer_class.from_pretrained("allegro/herbert-base-cased"		)

						_A       	=      tokenizer.encode("konstruowanie sekwencji"     , add_special_tokens=a__		)
						_A       	=      tokenizer.encode("konstruowanie wielu sekwencji"     , add_special_tokens=a__		)

						_A       	=      tokenizer.build_inputs_with_special_tokens(a__		)
						_A       	=      tokenizer.build_inputs_with_special_tokens(a__     , a__		)

						assert encoded_sentence == [0] + text + [2]
						assert encoded_pair == [0] + text + [2] + text_a + [2]



"""simple docstring"""


import os

from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline

from .logging import get_logger


a_											=     2 << 20  # 2mb
a_											=     get_logger(__name__)
class snake_case   (	_UpperCamelCase):







		def 			a_			(       self   :							Tuple		)							->    Optional[int]:





						'''simple docstring'''







						_A       	=      self._options.get_all_options().get("runner"		)
						return runner in [None, "DirectRunner", "PortableRunner"]






def   a__			(					__lowercase  ,      __lowercase  ,      __lowercase=False )						->						Any:
				_A       	=      FileSystems
				if fs.exists(__lowercase ):
								if force_upload:
												logger.info(f"""Remote path already exist: {remote_file_path}. Overwriting it as force_upload=True.""" )
								else:
												logger.info(f"""Remote path already exist: {remote_file_path}. Skipping it as force_upload=False.""" )
												return
				with fs.create(__lowercase ) as remote_file:
								with open(__lowercase  ,      "rb" ) as local_file:
												_A       	=      local_file.read(__lowercase )
												while chunk:
																remote_file.write(__lowercase )
																_A       	=      local_file.read(__lowercase )






def   a__			(					__lowercase  ,      __lowercase  ,      __lowercase=False )						->						Union[str, Any]:
				_A       	=      FileSystems
				if os.path.exists(__lowercase ):
								if force_download:
												logger.info(f"""Local path already exist: {remote_file_path}. Overwriting it as force_upload=True.""" )
								else:
												logger.info(f"""Local path already exist: {remote_file_path}. Skipping it as force_upload=False.""" )
												return
				with fs.open(__lowercase ) as remote_file:
								with open(__lowercase  ,      "wb" ) as local_file:
												_A       	=      remote_file.read(__lowercase )
												while chunk:
																local_file.write(__lowercase )
																_A       	=      remote_file.read(__lowercase )