



'''simple docstring'''



import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase	:		List[str]				=   get_tests_dir('''fixtures/test_sentencepiece.model''')






@require_sentencepiece
@require_tokenizers
class 					UpperCAmelCase__	(		UpperCamelCase__							,       unittest.TestCase ):
					a      :     Dict        =							XGLMTokenizer
					a      :     str        =							XGLMTokenizerFast
					a      :     int        =							True
					a      :     Optional[Any]        =							True



					def        UpperCAmelCase_ (    self     )     ->			List[str]:
						super().setUp()

						# We have a SentencePiece fixture for testing
						__lowerCAmelCase												=  XGLMTokenizer(UpperCamelCase			,				keep_accents=UpperCamelCase     )
						tokenizer.save_pretrained(self.tmpdirname     )



					def        UpperCAmelCase_ (    self     )     ->			str:
						__lowerCAmelCase												=  "<pad>"
						__lowerCAmelCase												=  1

						self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCamelCase     )			,				UpperCamelCase     )
						self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCamelCase     )			,				UpperCamelCase     )



					def        UpperCAmelCase_ (    self     )     ->			Optional[Any]:
						__lowerCAmelCase												=  list(self.get_tokenizer().get_vocab().keys()     )

						self.assertEqual(vocab_keys[0]			,				"<s>"     )
						self.assertEqual(vocab_keys[1]			,				"<pad>"     )
						self.assertEqual(len(UpperCamelCase     )			,				1008     )



					def        UpperCAmelCase_ (    self     )     ->			Optional[int]:
						self.assertEqual(self.get_tokenizer().vocab_size			,				1008     )



					def        UpperCAmelCase_ (    self     )     ->			List[str]:
						__lowerCAmelCase												=  XGLMTokenizer(UpperCamelCase			,				keep_accents=UpperCamelCase     )

						__lowerCAmelCase												=  tokenizer.tokenize("This is a test"     )
						self.assertListEqual(UpperCamelCase			,				["▁This", "▁is", "▁a", "▁t", "est"]     )

						self.assertListEqual(
						    tokenizer.convert_tokens_to_ids(UpperCamelCase     )			,				[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]			,				)

						__lowerCAmelCase												=  tokenizer.tokenize("I was born in 92000, and this is falsé."     )
						self.assertListEqual(
						    UpperCamelCase			,				[
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "9",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "é",
						        ".",
						    ]			,				)
						__lowerCAmelCase												=  tokenizer.convert_tokens_to_ids(UpperCamelCase     )
						self.assertListEqual(
						    UpperCamelCase			,				[
						        value + tokenizer.fairseq_offset
						        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
						    ]			,				)

						__lowerCAmelCase												=  tokenizer.convert_ids_to_tokens(UpperCamelCase     )
						self.assertListEqual(
						    UpperCamelCase			,				[
						        SPIECE_UNDERLINE + "I",
						        SPIECE_UNDERLINE + "was",
						        SPIECE_UNDERLINE + "b",
						        "or",
						        "n",
						        SPIECE_UNDERLINE + "in",
						        SPIECE_UNDERLINE + "",
						        "<unk>",
						        "2",
						        "0",
						        "0",
						        "0",
						        ",",
						        SPIECE_UNDERLINE + "and",
						        SPIECE_UNDERLINE + "this",
						        SPIECE_UNDERLINE + "is",
						        SPIECE_UNDERLINE + "f",
						        "al",
						        "s",
						        "<unk>",
						        ".",
						    ]			,				)



					@cached_property
					def        UpperCAmelCase_ (    self     )     ->			List[str]:
						return XGLMTokenizer.from_pretrained("facebook/xglm-564M"     )



					def        UpperCAmelCase_ (    self     )     ->			str:
						with tempfile.NamedTemporaryFile() as f:
							shutil.copyfile(UpperCamelCase			,				f.name     )
							__lowerCAmelCase												=  XGLMTokenizer(f.name			,				keep_accents=UpperCamelCase     )
							__lowerCAmelCase												=  pickle.dumps(UpperCamelCase     )
						pickle.loads(UpperCamelCase     )



					def        UpperCAmelCase_ (    self     )     ->			List[str]:
						if not self.test_rust_tokenizer:
							return

						__lowerCAmelCase												=  self.get_tokenizer()
						__lowerCAmelCase												=  self.get_rust_tokenizer()

						__lowerCAmelCase												=  "I was born in 92000, and this is falsé."

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

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

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



					@slow
					def        UpperCAmelCase_ (    self     )     ->			Optional[Any]:
						__lowerCAmelCase												=  "Hello World!"
						__lowerCAmelCase												=  [2, 3_1227, 4447, 35]

						self.assertListEqual(UpperCamelCase			,				self.big_tokenizer.encode(UpperCamelCase     )     )



					@slow
					def        UpperCAmelCase_ (    self     )     ->			Tuple:
						__lowerCAmelCase												=  (
						    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
						    " add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth"
						)
						# fmt: off
						__lowerCAmelCase												=  [2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 7_1630, 2_8085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 1_3675, 377, 652, 7580, 1_0341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 20_2277, 1_7892, 33, 60, 87, 4, 3234, 157, 61, 2667, 5_2376, 19, 88, 23, 735]
						# fmt: on

						self.assertListEqual(UpperCamelCase			,				self.big_tokenizer.encode(UpperCamelCase     )     )



					@slow
					def        UpperCAmelCase_ (    self     )     ->			Union[str, Any]:
						# fmt: off
						__lowerCAmelCase												=  {
						    "input_ids": [[2, 10_8825, 1163, 15, 8_8010, 473, 1_5898, 157, 1_3672, 1857, 312, 8, 23_8021, 1163, 53, 1_3672, 1857, 312, 8, 5_3283, 18_2396, 8, 1_8566, 16, 3_6733, 4101, 8, 230, 24_4017, 12_2553, 7, 15, 13_2597, 4, 293, 1_2511, 7610, 4, 3414, 13_2597, 9, 4, 3_2361, 362, 4, 734, 2_8512, 3_2569, 18, 4, 3_2361, 2_6096, 1_4982, 73, 1_8715, 2_1433, 23_5261, 15, 492, 1_2427, 16, 53, 1_8715, 2_1433, 6_5454, 15, 2_3659, 563, 16, 278, 597, 2843, 595, 7931, 18_2396, 6_4186, 22, 886, 595, 13_2981, 53, 2_5540, 3449, 4_3982, 3_9901, 5951, 878, 330, 4, 2_7694, 8_0269, 312, 53, 6517, 1_1780, 611, 2_0408, 5], [2, 6, 13_2597, 67, 4_2897, 33, 592, 8, 16_3729, 2_5540, 361, 13_6997, 10_9514, 17_3230, 7, 501, 60, 10_2913, 196, 5631, 235, 6_3243, 473, 6, 23_1757, 74, 5277, 7905, 53, 3095, 3_7317, 22, 454, 18_3874, 5], [2, 268, 3_1298, 4_6530, 6, 13_2935, 4_3831, 7, 597, 32, 24, 3688, 9865, 5]],
						    "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
						}  # noqa: E501
						# fmt: on

						self.tokenizer_integration_test_util(
						    expected_encoding=UpperCamelCase			,				model_name="facebook/xglm-564M"			,				padding=UpperCamelCase			,				)




'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase	:		Union[str, Any]				=   {
    '''configuration_distilbert''': [
        '''DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DistilBertConfig''',
        '''DistilBertOnnxConfig''',
    ],
    '''tokenization_distilbert''': ['''DistilBertTokenizer'''],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Tuple				=   ['''DistilBertTokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Tuple				=   [
	    '''DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DistilBertForMaskedLM''',
	    '''DistilBertForMultipleChoice''',
	    '''DistilBertForQuestionAnswering''',
	    '''DistilBertForSequenceClassification''',
	    '''DistilBertForTokenClassification''',
	    '''DistilBertModel''',
	    '''DistilBertPreTrainedModel''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		List[str]				=   [
	    '''TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFDistilBertForMaskedLM''',
	    '''TFDistilBertForMultipleChoice''',
	    '''TFDistilBertForQuestionAnswering''',
	    '''TFDistilBertForSequenceClassification''',
	    '''TFDistilBertForTokenClassification''',
	    '''TFDistilBertMainLayer''',
	    '''TFDistilBertModel''',
	    '''TFDistilBertPreTrainedModel''',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase	:		Optional[int]				=   [
	    '''FlaxDistilBertForMaskedLM''',
	    '''FlaxDistilBertForMultipleChoice''',
	    '''FlaxDistilBertForQuestionAnswering''',
	    '''FlaxDistilBertForSequenceClassification''',
	    '''FlaxDistilBertForTokenClassification''',
	    '''FlaxDistilBertModel''',
	    '''FlaxDistilBertPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_distilbert import (
	    DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    DistilBertConfig,
	    DistilBertOnnxConfig,
	)
	from .tokenization_distilbert import DistilBertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_distilbert_fast import DistilBertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_distilbert import (
		    DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DistilBertForMaskedLM,
		    DistilBertForMultipleChoice,
		    DistilBertForQuestionAnswering,
		    DistilBertForSequenceClassification,
		    DistilBertForTokenClassification,
		    DistilBertModel,
		    DistilBertPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_distilbert import (
		    TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFDistilBertForMaskedLM,
		    TFDistilBertForMultipleChoice,
		    TFDistilBertForQuestionAnswering,
		    TFDistilBertForSequenceClassification,
		    TFDistilBertForTokenClassification,
		    TFDistilBertMainLayer,
		    TFDistilBertModel,
		    TFDistilBertPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_distilbert import (
		    FlaxDistilBertForMaskedLM,
		    FlaxDistilBertForMultipleChoice,
		    FlaxDistilBertForQuestionAnswering,
		    FlaxDistilBertForSequenceClassification,
		    FlaxDistilBertForTokenClassification,
		    FlaxDistilBertModel,
		    FlaxDistilBertPreTrainedModel,
		)

else:
	import sys

	lowerCAmelCase	:		List[str]				=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)