



import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
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


SCREAMING_SNAKE_CASE     				=						get_tests_dir("fixtures/test_sentencepiece.model")



@require_sentencepiece
@require_tokenizers
class 	lowerCamelCase      (						_UpperCamelCase,     unittest.TestCase  ):







					'''simple docstring'''







					lowerCAmelCase_				:    Dict									=  XLMRobertaTokenizer
					lowerCAmelCase_				:    Optional[Any]									=  XLMRobertaTokenizerFast
					lowerCAmelCase_				:    Tuple									=  True
					lowerCAmelCase_				:    Any									=  True



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

							# We have a SentencePiece fixture for testing
							UpperCAmelCase_						=				XLMRobertaTokenizer(lowerCAmelCase    ,	keep_accents=lowerCAmelCase     )
							tokenizer.save_pretrained(self.tmpdirname     )



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

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



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

							self.assertEqual(vocab_keys[0]    ,	"<s>"     )
							self.assertEqual(vocab_keys[1]    ,	"<pad>"     )
							self.assertEqual(vocab_keys[-1]    ,	"<mask>"     )
							self.assertEqual(len(lowerCAmelCase     )    ,	1002     )



					def    A__		(			self     ):
							self.assertEqual(self.get_tokenizer().vocab_size    ,	1002     )



					def    A__		(			self     ):
							UpperCAmelCase_						=				XLMRobertaTokenizer(lowerCAmelCase    ,	keep_accents=lowerCAmelCase     )

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

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

							UpperCAmelCase_						=				tokenizer.tokenize("I was born in 92000, and this is falsé."     )
							self.assertListEqual(
							    lowerCAmelCase    ,	[
							        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",
							        ".",
							    ]    ,	)
							UpperCAmelCase_						=				tokenizer.convert_tokens_to_ids(lowerCAmelCase     )
							self.assertListEqual(
							    lowerCAmelCase    ,	[
							        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]
							        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
							    ]    ,	)

							UpperCAmelCase_						=				tokenizer.convert_ids_to_tokens(lowerCAmelCase     )
							self.assertListEqual(
							    lowerCAmelCase    ,	[
							        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>",
							        ".",
							    ]    ,	)



					def    A__		(			self     ):
							if not self.test_slow_tokenizer:
									# as we don't have a slow version, we can't compare the outputs between slow and fast versions
									return

							UpperCAmelCase_						=				(self.rust_tokenizer_class, "hf-internal-testing/tiny-xlm-roberta", {})
							for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
											UpperCAmelCase_						=				self.rust_tokenizer_class.from_pretrained(lowerCAmelCase    ,	**lowerCAmelCase     )
											UpperCAmelCase_						=				self.tokenizer_class.from_pretrained(lowerCAmelCase    ,	**lowerCAmelCase     )

											UpperCAmelCase_						=				tempfile.mkdtemp()

											UpperCAmelCase_						=				tokenizer_r.save_pretrained(lowerCAmelCase     )
											UpperCAmelCase_						=				tokenizer_p.save_pretrained(lowerCAmelCase     )

											# Checks it save with the same files + the tokenizer.json file for the fast one
											self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files     )     )
											UpperCAmelCase_						=				tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f     )
											self.assertSequenceEqual(lowerCAmelCase    ,	lowerCAmelCase     )

											# Checks everything loads correctly in the same way
											UpperCAmelCase_						=				tokenizer_r.from_pretrained(lowerCAmelCase     )
											UpperCAmelCase_						=				tokenizer_p.from_pretrained(lowerCAmelCase     )

											# Check special tokens are set accordingly on Rust and Python
											for key in tokenizer_pp.special_tokens_map:
													self.assertTrue(hasattr(lowerCAmelCase    ,	lowerCAmelCase     )     )
													# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
													# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

											shutil.rmtree(lowerCAmelCase     )

											# Save tokenizer rust, legacy_format=True
											UpperCAmelCase_						=				tempfile.mkdtemp()

											UpperCAmelCase_						=				tokenizer_r.save_pretrained(lowerCAmelCase    ,	legacy_format=lowerCAmelCase     )
											UpperCAmelCase_						=				tokenizer_p.save_pretrained(lowerCAmelCase     )

											# Checks it save with the same files
											self.assertSequenceEqual(lowerCAmelCase    ,	lowerCAmelCase     )

											# Checks everything loads correctly in the same way
											UpperCAmelCase_						=				tokenizer_r.from_pretrained(lowerCAmelCase     )
											UpperCAmelCase_						=				tokenizer_p.from_pretrained(lowerCAmelCase     )

											# Check special tokens are set accordingly on Rust and Python
											for key in tokenizer_pp.special_tokens_map:
													self.assertTrue(hasattr(lowerCAmelCase    ,	lowerCAmelCase     )     )

											shutil.rmtree(lowerCAmelCase     )

											# Save tokenizer rust, legacy_format=False
											UpperCAmelCase_						=				tempfile.mkdtemp()

											UpperCAmelCase_						=				tokenizer_r.save_pretrained(lowerCAmelCase    ,	legacy_format=lowerCAmelCase     )
											UpperCAmelCase_						=				tokenizer_p.save_pretrained(lowerCAmelCase     )

											# Checks it saved the tokenizer.json file
											self.assertTrue(any("tokenizer.json" in f for f in tokenizer_r_files     )     )

											# Checks everything loads correctly in the same way
											UpperCAmelCase_						=				tokenizer_r.from_pretrained(lowerCAmelCase     )
											UpperCAmelCase_						=				tokenizer_p.from_pretrained(lowerCAmelCase     )

											# Check special tokens are set accordingly on Rust and Python
											for key in tokenizer_pp.special_tokens_map:
													self.assertTrue(hasattr(lowerCAmelCase    ,	lowerCAmelCase     )     )

											shutil.rmtree(lowerCAmelCase     )



					@cached_property
					def    A__		(			self     ):
							return XLMRobertaTokenizer.from_pretrained("xlm-roberta-base"     )



					def    A__		(			self     ):
							with tempfile.NamedTemporaryFile() as f:
									shutil.copyfile(lowerCAmelCase    ,	f.name     )
									UpperCAmelCase_						=				XLMRobertaTokenizer(f.name    ,	keep_accents=lowerCAmelCase     )
									UpperCAmelCase_						=				pickle.dumps(lowerCAmelCase     )
							pickle.loads(lowerCAmelCase     )



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

							UpperCAmelCase_						=				self.get_tokenizer()
							UpperCAmelCase_						=				self.get_rust_tokenizer()

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

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

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

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



					@slow
					def    A__		(			self     ):
							UpperCAmelCase_						=				"Hello World!"
							UpperCAmelCase_						=				[0, 3_5378, 6661, 38, 2]
							# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
							# xlmr.eval()
							# xlmr.encode(symbols)

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



					@slow
					def    A__		(			self     ):
							UpperCAmelCase_						=				(
							    "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"
							)
							UpperCAmelCase_						=				[
							    0,
							    3293,
							    83,
							    10,
							    4552,
							    4989,
							    7986,
							    678,
							    10,
							    5915,
							    111,
							    17_9459,
							    12_4850,
							    4,
							    6044,
							    237,
							    12,
							    6,
							    5,
							    6,
							    4,
							    6780,
							    705,
							    15,
							    1388,
							    44,
							    378,
							    1_0114,
							    711,
							    152,
							    20,
							    6,
							    5,
							    2_2376,
							    642,
							    1221,
							    1_5190,
							    3_4153,
							    450,
							    5608,
							    959,
							    1119,
							    5_7702,
							    136,
							    186,
							    47,
							    1098,
							    2_9367,
							    47,
							    # 4426, # What fairseq tokenizes from "<unk>": "_<"
							    # 3678, # What fairseq tokenizes from "<unk>": "unk"
							    # 2740, # What fairseq tokenizes from "<unk>": ">"
							    3,  # What we tokenize from "<unk>": "<unk>"
							    6,  # Residue from the tokenization: an extra sentencepiece underline
							    4,
							    6044,
							    237,
							    6284,
							    5_0901,
							    528,
							    31,
							    90,
							    34,
							    927,
							    2,
							]
							# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
							# xlmr.eval()
							# xlmr.encode(symbols)

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



					@slow
					def    A__		(			self     ):
							# fmt: off
							UpperCAmelCase_						=				{"input_ids": [[0, 1_1062, 8_2772, 7, 15, 8_2772, 538, 5_1529, 237, 1_7198, 1290, 206, 9, 21_5175, 1314, 136, 1_7198, 1290, 206, 9, 5_6359, 42, 12_2009, 9, 1_6466, 16, 8_7344, 4537, 9, 4717, 7_8381, 6, 15_9958, 7, 15, 2_4480, 618, 4, 527, 2_2693, 5428, 4, 2777, 2_4480, 9874, 4, 4_3523, 594, 4, 803, 1_8392, 3_3189, 18, 4, 4_3523, 2_4447, 1_2399, 100, 2_4955, 8_3658, 9626, 14_4057, 15, 839, 2_2335, 16, 136, 2_4955, 8_3658, 8_3479, 15, 3_9102, 724, 16, 678, 645, 2789, 1328, 4589, 42, 12_2009, 11_5774, 23, 805, 1328, 4_6876, 7, 136, 5_3894, 1940, 4_2227, 4_1159, 1_7721, 823, 425, 4, 2_7512, 9_8722, 206, 136, 5531, 4970, 919, 1_7336, 5, 2], [0, 2_0080, 618, 83, 8_2775, 47, 479, 9, 1517, 73, 5_3894, 333, 8_0581, 11_0117, 1_8811, 5256, 1295, 51, 15_2526, 297, 7986, 390, 12_4416, 538, 3_5431, 214, 98, 1_5044, 2_5737, 136, 7108, 4_3701, 23, 756, 13_5355, 7, 5, 2, 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], [0, 581, 6_3773, 11_9455, 6, 14_7797, 8_8203, 7, 645, 70, 21, 3285, 1_0269, 5, 2, 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]], "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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=lowerCAmelCase    ,	model_name="xlm-roberta-base"    ,	revision="d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3"    ,	)






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


SCREAMING_SNAKE_CASE     				=						{
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			SCREAMING_SNAKE_CASE     				=						[
			    "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "GPTBigCodeForSequenceClassification",
			    "GPTBigCodeForTokenClassification",
			    "GPTBigCodeForCausalLM",
			    "GPTBigCodeModel",
			    "GPTBigCodePreTrainedModel",
			]

if TYPE_CHECKING:
			from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_gpt_bigcode import (
						    GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    GPTBigCodeForCausalLM,
						    GPTBigCodeForSequenceClassification,
						    GPTBigCodeForTokenClassification,
						    GPTBigCodeModel,
						    GPTBigCodePreTrainedModel,
						)


else:
			import sys

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

