



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     lowerCamelCase  (      lowerCAmelCase__   ,						unittest.TestCase    ):






					'''simple docstring'''





					_A		:      List[str]						=					HerbertTokenizer
					_A		:      Dict						=					HerbertTokenizerFast
					_A		:      Any						=					True






					def        lowerCAmelCase_    (	self:							str						)       ->     Any:
											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:
																	snake_case_			:Any						=      f_data.read().replace("""\n\n"""						,					"""\n"""						).strip()

											snake_case_			:Dict						=      [
											    """<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>""",
											]
											snake_case_			:Tuple						=      dict(zip(__lowerCAmelCase						,					range(len(__lowerCAmelCase						)						)						)						)
											snake_case_			:List[Any]						=      ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

											snake_case_			:Dict						=      os.path.join(self.tmpdirname						,					VOCAB_FILES_NAMES["""vocab_file"""]						)
											snake_case_			:Optional[int]						=      os.path.join(self.tmpdirname						,					VOCAB_FILES_NAMES["""merges_file"""]						)
											with open(self.vocab_file						,					"""w"""						) as fp:
																	fp.write(json.dumps(__lowerCAmelCase						)						)
											with open(self.merges_file						,					"""w"""						) as fp:
																	fp.write("""\n""".join(__lowerCAmelCase						)						)






					def        lowerCAmelCase_    (	self:							str						,					snake_case:							Any						)       ->     str:
											snake_case_			:Optional[Any]						=      """lower newer"""
											snake_case_			:int						=      """lower newer"""
											return input_text, output_text






					def        lowerCAmelCase_    (	self:							Any						)       ->     Union[str, Any]:
											snake_case_			:Tuple						=      self.tokenizer_class(vocab_file=self.vocab_file						,					merges_file=self.merges_file						)

											snake_case_			:Tuple						=      """lower"""
											snake_case_			:List[Any]						=      ["""low""", """er</w>"""]
											snake_case_			:List[Any]						=      tokenizer.tokenize(__lowerCAmelCase						)
											self.assertListEqual(__lowerCAmelCase						,					__lowerCAmelCase						)

											snake_case_			:str						=      tokens + ["""<unk>"""]
											snake_case_			:List[Any]						=      [16, 17, 23]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase						)						,					__lowerCAmelCase						)






					def        lowerCAmelCase_    (	self:							List[str]						)       ->     int:


											if not self.test_rust_tokenizer:
																	return

											snake_case_			:str						=      self.get_tokenizer()
											snake_case_			:Optional[Any]						=      self.get_rust_tokenizer()

											snake_case_			:Optional[Any]						=      """lower,newer"""

											snake_case_			:Dict						=      tokenizer.tokenize(__lowerCAmelCase						)
											snake_case_			:str						=      rust_tokenizer.tokenize(__lowerCAmelCase						)
											self.assertListEqual(__lowerCAmelCase						,					__lowerCAmelCase						)

											snake_case_			:Tuple						=      tokenizer.encode(__lowerCAmelCase						,					add_special_tokens=__lowerCAmelCase						)
											snake_case_			:Optional[int]						=      rust_tokenizer.encode(__lowerCAmelCase						,					add_special_tokens=__lowerCAmelCase						)
											self.assertListEqual(__lowerCAmelCase						,					__lowerCAmelCase						)

											snake_case_			:str						=      self.get_rust_tokenizer()
											snake_case_			:Optional[Any]						=      tokenizer.encode(__lowerCAmelCase						)
											snake_case_			:Any						=      rust_tokenizer.encode(__lowerCAmelCase						)
											self.assertListEqual(__lowerCAmelCase						,					__lowerCAmelCase						)






					@slow
					def        lowerCAmelCase_    (	self:							Optional[int]						)       ->     Union[str, Any]:
											snake_case_			:Any						=      self.tokenizer_class.from_pretrained("""allegro/herbert-base-cased"""						)

											snake_case_			:int						=      tokenizer.encode("""konstruowanie sekwencji"""						,					add_special_tokens=__lowerCAmelCase						)
											snake_case_			:Any						=      tokenizer.encode("""konstruowanie wielu sekwencji"""						,					add_special_tokens=__lowerCAmelCase						)

											snake_case_			:str						=      tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase						)
											snake_case_			:Union[str, Any]						=      tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase						,					__lowerCAmelCase						)

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





"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


__a     =    {
    "configuration_xlm_prophetnet": ["XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMProphetNetConfig"],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a     =    ["XLMProphetNetTokenizer"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__a     =    [
						    "XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "XLMProphetNetDecoder",
						    "XLMProphetNetEncoder",
						    "XLMProphetNetForCausalLM",
						    "XLMProphetNetForConditionalGeneration",
						    "XLMProphetNetModel",
						    "XLMProphetNetPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_xlm_prophetnet import XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLMProphetNetConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_xlm_prophetnet import XLMProphetNetTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_xlm_prophetnet import (
												    XLM_PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    XLMProphetNetDecoder,
												    XLMProphetNetEncoder,
												    XLMProphetNetForCausalLM,
												    XLMProphetNetForConditionalGeneration,
												    XLMProphetNetModel,
												    XLMProphetNetPreTrainedModel,
												)

else:
						import sys

						__a     =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
