'''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     a__( lowerCAmelCase__			,						unittest.TestCase     ):


			'''simple docstring'''






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



			def 							a_	(       self):




					"""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:
							lowerCAmelCase        =  f_data.read().replace("""\n\n"""	,   """\n""").strip()

					lowerCAmelCase        =  [
					    """<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>""",
					]
					lowerCAmelCase        =  dict(zip(__lowerCAmelCase	,   range(len(__lowerCAmelCase))))
					lowerCAmelCase        =  ["""l o 123""", """lo w 1456""", """e r</w> 1789""", """"""]

					lowerCAmelCase        =  os.path.join(self.tmpdirname	,   VOCAB_FILES_NAMES["""vocab_file"""])
					lowerCAmelCase        =  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 							a_	(       self	,   __lowerCAmelCase):




					"""simple docstring"""


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



			def 							a_	(       self):




					"""simple docstring"""


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

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

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



			def 							a_	(       self):




					"""simple docstring"""


					if not self.test_rust_tokenizer:
							return

					lowerCAmelCase        =  self.get_tokenizer()
					lowerCAmelCase        =  self.get_rust_tokenizer()

					lowerCAmelCase        =  """lower,newer"""

					lowerCAmelCase        =  tokenizer.tokenize(__lowerCAmelCase)
					lowerCAmelCase        =  rust_tokenizer.tokenize(__lowerCAmelCase)
					self.assertListEqual(__lowerCAmelCase	,   __lowerCAmelCase)

					lowerCAmelCase        =  tokenizer.encode(__lowerCAmelCase	,   add_special_tokens=__lowerCAmelCase)
					lowerCAmelCase        =  rust_tokenizer.encode(__lowerCAmelCase	,   add_special_tokens=__lowerCAmelCase)
					self.assertListEqual(__lowerCAmelCase	,   __lowerCAmelCase)

					lowerCAmelCase        =  self.get_rust_tokenizer()
					lowerCAmelCase        =  tokenizer.encode(__lowerCAmelCase)
					lowerCAmelCase        =  rust_tokenizer.encode(__lowerCAmelCase)
					self.assertListEqual(__lowerCAmelCase	,   __lowerCAmelCase)







			@slow
			def 							a_	(       self):




					"""simple docstring"""


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

					lowerCAmelCase        =  tokenizer.encode("""konstruowanie sekwencji"""	,   add_special_tokens=__lowerCAmelCase)
					lowerCAmelCase        =  tokenizer.encode("""konstruowanie wielu sekwencji"""	,   add_special_tokens=__lowerCAmelCase)

					lowerCAmelCase        =  tokenizer.build_inputs_with_special_tokens(__lowerCAmelCase)
					lowerCAmelCase        =  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_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__lowercase				   =  {
    '''configuration_bart''': ['''BART_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BartConfig''', '''BartOnnxConfig'''],
    '''tokenization_bart''': ['''BartTokenizer'''],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase				   =  ['''BartTokenizerFast''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase				   =  [
						    '''BART_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''BartForCausalLM''',
						    '''BartForConditionalGeneration''',
						    '''BartForQuestionAnswering''',
						    '''BartForSequenceClassification''',
						    '''BartModel''',
						    '''BartPretrainedModel''',
						    '''PretrainedBartModel''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase				   =  [
						    '''TFBartForConditionalGeneration''',
						    '''TFBartForSequenceClassification''',
						    '''TFBartModel''',
						    '''TFBartPretrainedModel''',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						__lowercase				   =  [
						    '''FlaxBartDecoderPreTrainedModel''',
						    '''FlaxBartForCausalLM''',
						    '''FlaxBartForConditionalGeneration''',
						    '''FlaxBartForQuestionAnswering''',
						    '''FlaxBartForSequenceClassification''',
						    '''FlaxBartModel''',
						    '''FlaxBartPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
						from .tokenization_bart import BartTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_bart_fast import BartTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_bart import (
												    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
												    BartForCausalLM,
												    BartForConditionalGeneration,
												    BartForQuestionAnswering,
												    BartForSequenceClassification,
												    BartModel,
												    BartPretrainedModel,
												    PretrainedBartModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_bart import (
												    TFBartForConditionalGeneration,
												    TFBartForSequenceClassification,
												    TFBartModel,
												    TFBartPretrainedModel,
												)

						try:
												if not is_flax_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_flax_bart import (
												    FlaxBartDecoderPreTrainedModel,
												    FlaxBartForCausalLM,
												    FlaxBartForConditionalGeneration,
												    FlaxBartForQuestionAnswering,
												    FlaxBartForSequenceClassification,
												    FlaxBartModel,
												    FlaxBartPreTrainedModel,
												)

else:
						import sys

						__lowercase				   =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




