

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


A_ :				List[Any]						 =    get_tests_dir('fixtures/test_sentencepiece.model')



@require_sentencepiece
@require_tokenizers
class 					_a		(__magic_name__	,     unittest.TestCase       ):


					'''simple docstring'''






					UpperCAmelCase__:     Dict													= XGLMTokenizer
					UpperCAmelCase__:     List[Any]													= XGLMTokenizerFast
					UpperCAmelCase__:     Tuple													= True
					UpperCAmelCase__:     str													= True






					def 						__A    (				self    ):
						super().setUp()

						# We have a SentencePiece fixture for testing
						A__							:					Any       =	XGLMTokenizer(A__					, keep_accents=A__    )
						tokenizer.save_pretrained(self.tmpdirname    )






					def 						__A    (				self    ):
						A__							:					Tuple       =	"""<pad>"""
						A__							:					Tuple       =	1

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






					def 						__A    (				self    ):
						A__							:					Dict       =	list(self.get_tokenizer().get_vocab().keys()    )

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






					def 						__A    (				self    ):
						self.assertEqual(self.get_tokenizer().vocab_size					, 1008    )






					def 						__A    (				self    ):
						A__							:					Optional[int]       =	XGLMTokenizer(A__					, keep_accents=A__    )

						A__							:					Tuple       =	tokenizer.tokenize("""This is a test"""    )
						self.assertListEqual(A__					, ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]    )

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

						A__							:					List[Any]       =	tokenizer.tokenize("""I was born in 92000, and this is falsé."""    )
						self.assertListEqual(
						    A__					, [
						        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""",
						        """.""",
						    ]					, )
						A__							:					List[str]       =	tokenizer.convert_tokens_to_ids(A__    )
						self.assertListEqual(
						    A__					, [
						        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]
						    ]					, )

						A__							:					List[Any]       =	tokenizer.convert_ids_to_tokens(A__    )
						self.assertListEqual(
						    A__					, [
						        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 						__A    (				self    ):
						return XGLMTokenizer.from_pretrained("""facebook/xglm-564M"""    )






					def 						__A    (				self    ):
						with tempfile.NamedTemporaryFile() as f:
							shutil.copyfile(A__					, f.name    )
							A__							:					List[str]       =	XGLMTokenizer(f.name					, keep_accents=A__    )
							A__							:					List[Any]       =	pickle.dumps(A__    )
						pickle.loads(A__    )






					def 						__A    (				self    ):
						if not self.test_rust_tokenizer:
							return

						A__							:					List[str]       =	self.get_tokenizer()
						A__							:					Dict       =	self.get_rust_tokenizer()

						A__							:					int       =	"""I was born in 92000, and this is falsé."""

						A__							:					List[Any]       =	tokenizer.tokenize(A__    )
						A__							:					str       =	rust_tokenizer.tokenize(A__    )
						self.assertListEqual(A__					, A__    )

						A__							:					Union[str, Any]       =	tokenizer.encode(A__					, add_special_tokens=A__    )
						A__							:					List[str]       =	rust_tokenizer.encode(A__					, add_special_tokens=A__    )
						self.assertListEqual(A__					, A__    )

						A__							:					int       =	self.get_rust_tokenizer()
						A__							:					Optional[int]       =	tokenizer.encode(A__    )
						A__							:					List[str]       =	rust_tokenizer.encode(A__    )
						self.assertListEqual(A__					, A__    )






					@slow
					def 						__A    (				self    ):
						A__							:					Optional[int]       =	"""Hello World!"""
						A__							:					Union[str, Any]       =	[2, 3_1227, 4447, 35]

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






					@slow
					def 						__A    (				self    ):
						A__							:					Dict       =	(
						    """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
						A__							:					str       =	[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(A__					, self.big_tokenizer.encode(A__    )    )






					@slow
					def 						__A    (				self    ):
						# fmt: off
						A__							:					Tuple       =	{
						    """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=A__					, model_name="""facebook/xglm-564M"""					, padding=A__					, )






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available


A_ :				Optional[Any]						 =    {}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A_ :				str						 =    ['BartphoTokenizer']

if TYPE_CHECKING:
	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_bartpho import BartphoTokenizer

else:
	import sys

	A_ :				Optional[int]						 =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



