





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


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






@require_sentencepiece
@require_tokenizers
class 					__A    (    _UpperCAmelCase			,				unittest.TestCase ):

			'''simple docstring'''







			lowerCAmelCase_							     =						XLMRobertaTokenizer
			lowerCAmelCase_							     =						XLMRobertaTokenizerFast
			lowerCAmelCase_							     =						True
			lowerCAmelCase_							     =						True





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				super().setUp()

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





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		"""<pad>"""
				lowerCamelCase__								=		1

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





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		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_							)       ,  1_0_0_2							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				self.assertEqual(self.get_tokenizer().vocab_size       ,  1_0_0_2							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		XLMRobertaTokenizer(lowercase_       ,  keep_accents=lowercase_							)

				lowerCamelCase__								=		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 [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]]       ,  )

				lowerCamelCase__								=		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''',
				        '''.''',
				    ]       ,  )
				lowerCamelCase__								=		tokenizer.convert_tokens_to_ids(lowercase_							)
				self.assertListEqual(
				    lowercase_       ,  [
				        value + tokenizer.fairseq_offset
				        for value in [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 2, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 2, 4]
				        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
				    ]       ,  )

				lowerCamelCase__								=		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 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				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

				lowerCamelCase__								=		(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})'							):
						lowerCamelCase__								=		self.rust_tokenizer_class.from_pretrained(lowercase_       ,  **lowercase_							)
						lowerCamelCase__								=		self.tokenizer_class.from_pretrained(lowercase_       ,  **lowercase_							)

						lowerCamelCase__								=		tempfile.mkdtemp()

						lowerCamelCase__								=		tokenizer_r.save_pretrained(lowercase_							)
						lowerCamelCase__								=		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							)							)
						lowerCamelCase__								=		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
						lowerCamelCase__								=		tokenizer_r.from_pretrained(lowercase_							)
						lowerCamelCase__								=		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
						lowerCamelCase__								=		tempfile.mkdtemp()

						lowerCamelCase__								=		tokenizer_r.save_pretrained(lowercase_       ,  legacy_format=lowercase_							)
						lowerCamelCase__								=		tokenizer_p.save_pretrained(lowercase_							)

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

						# Checks everything loads correctly in the same way
						lowerCamelCase__								=		tokenizer_r.from_pretrained(lowercase_							)
						lowerCamelCase__								=		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
						lowerCamelCase__								=		tempfile.mkdtemp()

						lowerCamelCase__								=		tokenizer_r.save_pretrained(lowercase_       ,  legacy_format=lowercase_							)
						lowerCamelCase__								=		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
						lowerCamelCase__								=		tokenizer_r.from_pretrained(lowercase_							)
						lowerCamelCase__								=		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 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				return XLMRobertaTokenizer.from_pretrained('''xlm-roberta-base'''							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				with tempfile.NamedTemporaryFile() as f:
					shutil.copyfile(lowercase_       ,  f.name							)
					lowerCamelCase__								=		XLMRobertaTokenizer(f.name       ,  keep_accents=lowercase_							)
					lowerCamelCase__								=		pickle.dumps(lowercase_							)
				pickle.loads(lowercase_							)





			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				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(lowercase_							)
				lowerCamelCase__								=		rust_tokenizer.tokenize(lowercase_							)
				self.assertListEqual(lowercase_       ,  lowercase_							)

				lowerCamelCase__								=		tokenizer.encode(lowercase_       ,  add_special_tokens=lowercase_							)
				lowerCamelCase__								=		rust_tokenizer.encode(lowercase_       ,  add_special_tokens=lowercase_							)
				self.assertListEqual(lowercase_       ,  lowercase_							)

				lowerCamelCase__								=		self.get_rust_tokenizer()
				lowerCamelCase__								=		tokenizer.encode(lowercase_							)
				lowerCamelCase__								=		rust_tokenizer.encode(lowercase_							)
				self.assertListEqual(lowercase_       ,  lowercase_							)





			@slow
			def 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		"""Hello World!"""
				lowerCamelCase__								=		[0, 3_5_3_7_8, 6_6_6_1, 3_8, 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 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				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"""
				)
				lowerCamelCase__								=		[
				    0,
				    3_2_9_3,
				    8_3,
				    1_0,
				    4_5_5_2,
				    4_9_8_9,
				    7_9_8_6,
				    6_7_8,
				    1_0,
				    5_9_1_5,
				    1_1_1,
				    1_7_9_4_5_9,
				    1_2_4_8_5_0,
				    4,
				    6_0_4_4,
				    2_3_7,
				    1_2,
				    6,
				    5,
				    6,
				    4,
				    6_7_8_0,
				    7_0_5,
				    1_5,
				    1_3_8_8,
				    4_4,
				    3_7_8,
				    1_0_1_1_4,
				    7_1_1,
				    1_5_2,
				    2_0,
				    6,
				    5,
				    2_2_3_7_6,
				    6_4_2,
				    1_2_2_1,
				    1_5_1_9_0,
				    3_4_1_5_3,
				    4_5_0,
				    5_6_0_8,
				    9_5_9,
				    1_1_1_9,
				    5_7_7_0_2,
				    1_3_6,
				    1_8_6,
				    4_7,
				    1_0_9_8,
				    2_9_3_6_7,
				    4_7,
				    # 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,
				    6_0_4_4,
				    2_3_7,
				    6_2_8_4,
				    5_0_9_0_1,
				    5_2_8,
				    3_1,
				    9_0,
				    3_4,
				    9_2_7,
				    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 		__lowerCamelCase				(    self							):



				'''simple docstring'''







				lowerCamelCase__								=		{"""input_ids""": [[0, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 5_4_2_8, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 1_2_3_9_9, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 2_7_8_9, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 8_0_5, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [0, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 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, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 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'''       ,  )




'''simple docstring'''




import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
						import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin





@require_torch
class     __magic_name__						(    unittest.TestCase,     _UpperCAmelCase):







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[Any]    ):
										lowercase_					:			List[str]										=       load_tool("""text-to-speech"""    )
										self.tool.setup()







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]    ):
										# SpeechT5 isn't deterministic
										torch.manual_seed(0    )
										lowercase_					:			List[str]										=       self.tool("""hey"""    )
										lowercase_					:			Optional[int]										=       result.to_raw()
										self.assertTrue(
										    torch.allclose(
										        resulting_tensor[:3]				,			torch.tensor([-0.0_00_59_66_66_88_32_11_58_29, -0.0_00_36_57_64_01_90_79_50_64, -0.00_01_34_39_50_27_99_88_34_85]    )				,			)    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]    ):
										# SpeechT5 isn't deterministic
										torch.manual_seed(0    )
										lowercase_					:			Union[str, Any]										=       self.tool("""hey"""    )
										lowercase_					:			int										=       result.to_raw()
										self.assertTrue(
										    torch.allclose(
										        resulting_tensor[:3]				,			torch.tensor([-0.0_00_59_66_66_88_32_11_58_29, -0.0_00_36_57_64_01_90_79_50_64, -0.00_01_34_39_50_27_99_88_34_85]    )				,			)    )





