



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


lowercase_						=       get_tests_dir("""fixtures/test_sentencepiece.model""")
@require_sentencepiece
@require_tokenizers
class 			_snake_case     (   lowercase__      ,		unittest.TestCase):
				UpperCamelCase__			:   int       						=XLMRobertaTokenizer
				UpperCamelCase__			:   List[Any]       						=XLMRobertaTokenizerFast
				UpperCamelCase__			:   List[str]       						=True
				UpperCamelCase__			:   Optional[int]       						=True




				def 							A__ (  self   :  List[Any]  ):
							super().setUp()

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




				def 							A__ (  self   :  Optional[Any]  ):
							lowercase__   					=			"<pad>"
							lowercase__   					=			1

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




				def 							A__ (  self   :  Optional[Any]  ):
							lowercase__   					=			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(__lowercase  ),   1002  )




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




				def 							A__ (  self   :  str  ):
							lowercase__   					=			XLMRobertaTokenizer(__lowercase,   keep_accents=__lowercase  )

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

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

							lowercase__   					=			tokenizer.tokenize("I was born in 92000, and this is falsé."  )
							self.assertListEqual(
							    __lowercase,   [
							        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",
							        ".",
							    ],   )
							lowercase__   					=			tokenizer.convert_tokens_to_ids(__lowercase  )
							self.assertListEqual(
							    __lowercase,   [
							        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 ^
							    ],   )

							lowercase__   					=			tokenizer.convert_ids_to_tokens(__lowercase  )
							self.assertListEqual(
							    __lowercase,   [
							        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   :  str  ):
							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

							lowercase__   					=			(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})'''  ):
													lowercase__   					=			self.rust_tokenizer_class.from_pretrained(__lowercase,   **__lowercase  )
													lowercase__   					=			self.tokenizer_class.from_pretrained(__lowercase,   **__lowercase  )

													lowercase__   					=			tempfile.mkdtemp()

													lowercase__   					=			tokenizer_r.save_pretrained(__lowercase  )
													lowercase__   					=			tokenizer_p.save_pretrained(__lowercase  )

													# 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  )  )
													lowercase__   					=			tuple(f for f in tokenizer_r_files if "tokenizer.json" not in f  )
													self.assertSequenceEqual(__lowercase,   __lowercase  )

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

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

													shutil.rmtree(__lowercase  )

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

													lowercase__   					=			tokenizer_r.save_pretrained(__lowercase,   legacy_format=__lowercase  )
													lowercase__   					=			tokenizer_p.save_pretrained(__lowercase  )

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

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

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

													shutil.rmtree(__lowercase  )

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

													lowercase__   					=			tokenizer_r.save_pretrained(__lowercase,   legacy_format=__lowercase  )
													lowercase__   					=			tokenizer_p.save_pretrained(__lowercase  )

													# 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
													lowercase__   					=			tokenizer_r.from_pretrained(__lowercase  )
													lowercase__   					=			tokenizer_p.from_pretrained(__lowercase  )

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

													shutil.rmtree(__lowercase  )




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




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




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

							lowercase__   					=			self.get_tokenizer()
							lowercase__   					=			self.get_rust_tokenizer()

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

							lowercase__   					=			tokenizer.tokenize(__lowercase  )
							lowercase__   					=			rust_tokenizer.tokenize(__lowercase  )
							self.assertListEqual(__lowercase,   __lowercase  )

							lowercase__   					=			tokenizer.encode(__lowercase,   add_special_tokens=__lowercase  )
							lowercase__   					=			rust_tokenizer.encode(__lowercase,   add_special_tokens=__lowercase  )
							self.assertListEqual(__lowercase,   __lowercase  )

							lowercase__   					=			self.get_rust_tokenizer()
							lowercase__   					=			tokenizer.encode(__lowercase  )
							lowercase__   					=			rust_tokenizer.encode(__lowercase  )
							self.assertListEqual(__lowercase,   __lowercase  )




				@slow
				def 							A__ (  self   :  str  ):
							lowercase__   					=			"Hello World!"
							lowercase__   					=			[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(__lowercase,   self.big_tokenizer.encode(__lowercase  )  )




				@slow
				def 							A__ (  self   :  List[str]  ):
							lowercase__   					=			(
							    "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"
							)
							lowercase__   					=			[
							    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(__lowercase,   self.big_tokenizer.encode(__lowercase  )  )




				@slow
				def 							A__ (  self   :  Dict  ):
							# fmt: off
							lowercase__   					=			{"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=__lowercase,   model_name="xlm-roberta-base",   revision="d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3",   )









import argparse
import json
import subprocess



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					):
			lowercase__   					=			[]

			lowercase__   					=			(
			    f'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'''
			    " https://api.github.com/repos/huggingface/transformers/actions/runners"
			)
			lowercase__   					=			subprocess.run(SCREAMING_SNAKE_CASE_  ,					shell=SCREAMING_SNAKE_CASE_  ,					stdout=subprocess.PIPE					)
			lowercase__   					=			output.stdout.decode("utf-8"					)
			lowercase__   					=			json.loads(SCREAMING_SNAKE_CASE_					)

			lowercase__   					=			status["runners"]
			for runner in runners:
						if runner["name"] in target_runners:
									if runner["status"] == "offline":
												offline_runners.append(SCREAMING_SNAKE_CASE_					)

    # save the result so we can report them on Slack
			with open("offline_runners.txt"  ,					"w"					) as fp:
						fp.write(json.dumps(SCREAMING_SNAKE_CASE_					)					)

			if len(SCREAMING_SNAKE_CASE_					) > 0:
						lowercase__   					=			"\n".join([x["name"] for x in offline_runners]					)
						raise ValueError(f'''The following runners are offline:\n{failed}'''					)


if __name__ == "__main__":



							def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					):
										return values.split(","					)

							lowercase_						=       argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    """--target_runners""",
							    default=None,
							    type=list_str,
							    required=True,
							    help="""Comma-separated list of runners to check status.""",
							)

							parser.add_argument(
							    """--token""", default=None, type=str, required=True, help="""A token that has actions:read permission."""
							)
							lowercase_						=       parser.parse_args()




							get_runner_status(args.target_runners, args.token)




