






"""simple docstring"""



import tempfile
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)
from transformers.utils import is_sentencepiece_available


if is_sentencepiece_available():
						from transformers.models.mam_aaa.tokenization_mam_aaa import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


if is_sentencepiece_available():
						A__	:    Any			 = get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
						from transformers.models.mam_aaa.modeling_mam_aaa import shift_tokens_right

A__	:    Any			 = 128_022
A__	:    List[Any]			 = 128_028







@require_sentencepiece
class        lowercase__      (							snake_case__,       unittest.TestCase       ):
			_UpperCAmelCase		:int             =			MaMaaaTokenizer
			_UpperCAmelCase		:int             =			False
			_UpperCAmelCase		:str             =			False
			_UpperCAmelCase		:int             =			True


			def      UpperCAmelCase__						(				self					:  str ):
										super().setUp()

										lowerCamelCase_	:							Tuple									=["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
										lowerCamelCase_	:							List[Any]									=dict(zip(_lowerCAmelCase       ,	range(len(_lowerCAmelCase ) ) ) )
										lowerCamelCase_	:							Optional[int]									=Path(self.tmpdirname )
										save_json(_lowerCAmelCase       ,	save_dir / VOCAB_FILES_NAMES["vocab_file"] )
										if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
																	copyfile(_lowerCAmelCase       ,	save_dir / VOCAB_FILES_NAMES["spm_file"] )

										lowerCamelCase_	:							str									=MaMaaaTokenizer.from_pretrained(self.tmpdirname )
										tokenizer.save_pretrained(self.tmpdirname )


			def      UpperCAmelCase__						(				self					:  Tuple       ,	**snake_case__					:  List[str] ):
										return MaMaaaTokenizer.from_pretrained(self.tmpdirname       ,	**_lowerCAmelCase )


			def      UpperCAmelCase__						(				self					:  List[Any]       ,	snake_case__					:  List[str] ):
										return (
										    "This is a test",
										    "This is a test",
										)


			def      UpperCAmelCase__						(				self					:  str ):
										lowerCamelCase_	:							Optional[Any]									="</s>"
										lowerCamelCase_	:							List[str]									=0

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


			def      UpperCAmelCase__						(				self					:  Dict ):
										lowerCamelCase_	:							List[Any]									=self.get_tokenizer()
										lowerCamelCase_	:							Optional[int]									=list(tokenizer.get_vocab().keys() )

										self.assertEqual(vocab_keys[0]       ,	"</s>" )
										self.assertEqual(vocab_keys[1]       ,	"<unk>" )
										self.assertEqual(vocab_keys[-1]       ,	"<s>" )
										self.assertEqual(len(_lowerCAmelCase )       ,	tokenizer.vocab_size + len(tokenizer.get_added_vocab() ) )


			@unittest.skip("Skip this test while all models are still to be uploaded." )
			def      UpperCAmelCase__						(				self					:  Optional[int] ):
										pass


			def      UpperCAmelCase__						(				self					:  List[Any] ):
										lowerCamelCase_	:							Tuple									=self.get_tokenizer()

										lowerCamelCase_	:							Union[str, Any]									=tokenizer.tokenize("This is a test" )
										self.assertListEqual(_lowerCAmelCase       ,	["▁This", "▁is", "▁a", "▁t", "est"] )

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(_lowerCAmelCase )       ,	[2, 3, 4, 5, 6]       ,	)

										lowerCamelCase_	:							Optional[Any]									=tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6] )
										self.assertListEqual(_lowerCAmelCase       ,	["▁This", "▁is", "▁a", "▁t", "est"] )

										lowerCamelCase_	:							str									=tokenizer.convert_tokens_to_string(_lowerCAmelCase )
										self.assertEqual(_lowerCAmelCase       ,	"This is a test" )


			@slow
			def      UpperCAmelCase__						(				self					:  Any ):
										lowerCamelCase_	:							List[Any]									={"input_ids": [[12_8022, 11_0108, 397, 11, 3_8272, 2247, 12_4811, 285, 1_8105, 1586, 207, 7, 3_9534, 4428, 397, 1019, 1_8105, 1586, 207, 7, 4_1337, 1_6786, 241, 7, 2_0214, 17, 12_5690, 1_0398, 7, 4_4378, 5_8069, 6_8342, 7798, 7343, 11, 299, 3_3310, 4, 158, 3_7350, 9_4077, 4569, 299, 3_3310, 90, 4, 5_2840, 290, 4, 3_1270, 112, 299, 682, 4, 5_2840, 3_9953, 1_4079, 193, 5_2519, 9_0894, 1_7894, 12_0697, 11, 4_0445, 551, 17, 1019, 5_2519, 9_0894, 1_7756, 963, 11, 4_0445, 480, 17, 9792, 1120, 5173, 1393, 6240, 1_6786, 241, 12_0996, 28, 1245, 1393, 11_8240, 1_1123, 1019, 9_3612, 2691, 1_0618, 9_8058, 12_0409, 1928, 279, 4, 4_0683, 367, 178, 207, 1019, 103, 10_3121, 506, 6_5296, 5, 2], [12_8022, 2_1217, 367, 117, 12_5450, 128, 719, 7, 7308, 40, 9_3612, 1_2669, 1116, 1_6704, 71, 1_7785, 3699, 1_5592, 35, 144, 9584, 241, 1_1943, 713, 950, 799, 2247, 8_8427, 150, 149, 11_8813, 12_0706, 1019, 10_6906, 8_1518, 28, 1224, 2_2799, 397, 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], [12_8022, 1658, 12_3311, 5155, 5578, 4722, 279, 1_4947, 2366, 1120, 1197, 14, 1348, 9232, 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, 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, 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], [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, 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="facebook/m2m100_418M"       ,	revision="c168bae485c864188cf9aa0e4108b0b6934dc91e"       ,	)







@require_torch
@require_sentencepiece
@require_tokenizers
class        lowercase__      (							unittest.TestCase       ):
			_UpperCAmelCase		:Tuple             =			"facebook/m2m100_418M"
			_UpperCAmelCase		:List[Any]             =			[
			    "In my opinion, there are two levels of response from the French government.",
			    "NSA Affair Emphasizes Complete Lack of Debate on Intelligence",
			]
			_UpperCAmelCase		:Optional[Any]             =			[
			    "Selon moi, il y a deux niveaux de réponse de la part du gouvernement français.",
			    "L'affaire NSA souligne l'absence totale de débat sur le renseignement",
			]

			# fmt: off
			_UpperCAmelCase		:Dict             =			[EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]


			@classmethod
			def      UpperCAmelCase__						(				cls					:  int ):
										lowerCamelCase_	:							Optional[Any]									=MaMaaaTokenizer.from_pretrained(
										    cls.checkpoint_name       ,	src_lang="en"       ,	tgt_lang="fr" )
										lowerCamelCase_	:							List[Any]									=1
										return cls


			def      UpperCAmelCase__						(				self					:  Dict ):
										self.assertEqual(self.tokenizer.get_lang_id("ar" )       ,	12_8006 )
										self.assertEqual(self.tokenizer.get_lang_id("en" )       ,	12_8022 )
										self.assertEqual(self.tokenizer.get_lang_id("ro" )       ,	12_8076 )
										self.assertEqual(self.tokenizer.get_lang_id("mr" )       ,	12_8063 )


			def      UpperCAmelCase__						(				self					:  List[Any] ):
										lowerCamelCase_	:							Any									=self.tokenizer.get_vocab()
										self.assertEqual(len(_lowerCAmelCase )       ,	self.tokenizer.vocab_size )
										self.assertEqual(vocab["<unk>"]       ,	3 )
										self.assertIn(self.tokenizer.get_lang_token("en" )       ,	_lowerCAmelCase )


			def      UpperCAmelCase__						(				self					:  Dict ):
										lowerCamelCase_	:							Optional[int]									="en"
										lowerCamelCase_	:							Any									=self.tokenizer.batch_encode_plus(self.src_text ).input_ids[0]
										self.assertListEqual(self.expected_src_tokens       ,	_lowerCAmelCase )


			def      UpperCAmelCase__						(				self					:  Tuple ):
										self.assertIn(_lowerCAmelCase       ,	self.tokenizer.all_special_ids )
										# fmt: off
										lowerCamelCase_	:							Dict									=[FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 1_4028, 136, 3286, 9706, 6, 9_0797, 6, 14_4012, 162, 8_8128, 3_0061, 5, 2]
										# fmt: on
										lowerCamelCase_	:							Union[str, Any]									=self.tokenizer.decode(_lowerCAmelCase       ,	skip_special_tokens=_lowerCAmelCase )
										lowerCamelCase_	:							Dict									=self.tokenizer.decode(generated_ids[1:]       ,	skip_special_tokens=_lowerCAmelCase )
										self.assertEqual(_lowerCAmelCase       ,	_lowerCAmelCase )
										self.assertNotIn(self.tokenizer.eos_token       ,	_lowerCAmelCase )


			def      UpperCAmelCase__						(				self					:  List[Any] ):
										lowerCamelCase_	:							Any									=tempfile.mkdtemp()
										lowerCamelCase_	:							Dict									=self.tokenizer.lang_token_to_id
										self.tokenizer.save_pretrained(_lowerCAmelCase )
										lowerCamelCase_	:							Union[str, Any]									=MaMaaaTokenizer.from_pretrained(_lowerCAmelCase )
										self.assertDictEqual(new_tok.lang_token_to_id       ,	_lowerCAmelCase )


			@require_torch
			def      UpperCAmelCase__						(				self					:  Dict ):
										lowerCamelCase_	:							Optional[int]									="en"
										lowerCamelCase_	:							Dict									="fr"

										lowerCamelCase_	:							Union[str, Any]									=self.tokenizer(self.src_text       ,	text_target=self.tgt_text       ,	padding=_lowerCAmelCase       ,	return_tensors="pt" )

										lowerCamelCase_	:							Union[str, Any]									=shift_tokens_right(
										    batch["labels"]       ,	self.tokenizer.pad_token_id       ,	self.tokenizer.eos_token_id )

										for k in batch:
																	lowerCamelCase_	:							Tuple									=batch[k].tolist()
										# batch = {k: v.tolist() for k,v in batch.items()}
										# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
										# batch.decoder_inputs_ids[0][0] ==
										assert batch.input_ids[1][0] == EN_CODE
										assert batch.input_ids[1][-1] == 2
										assert batch.labels[1][0] == FR_CODE
										assert batch.labels[1][-1] == 2
										assert batch.decoder_input_ids[1][:2] == [2, FR_CODE]


			@require_torch
			def      UpperCAmelCase__						(				self					:  Union[str, Any] ):
										lowerCamelCase_	:							int									="mr"
										self.assertListEqual(self.tokenizer.prefix_tokens       ,	[self.tokenizer.get_lang_id("mr" )] )
										self.assertListEqual(self.tokenizer.suffix_tokens       ,	[self.tokenizer.eos_token_id] )

										lowerCamelCase_	:							Dict									="zh"
										self.assertListEqual(self.tokenizer.prefix_tokens       ,	[self.tokenizer.get_lang_id("zh" )] )
										self.assertListEqual(self.tokenizer.suffix_tokens       ,	[self.tokenizer.eos_token_id] )


			@require_torch
			def      UpperCAmelCase__						(				self					:  str ):
										lowerCamelCase_	:							Tuple									="mr"
										self.tokenizer._switch_to_target_mode()
										self.assertListEqual(self.tokenizer.prefix_tokens       ,	[self.tokenizer.get_lang_id("mr" )] )
										self.assertListEqual(self.tokenizer.suffix_tokens       ,	[self.tokenizer.eos_token_id] )
										self.tokenizer._switch_to_input_mode()
										self.assertListEqual(self.tokenizer.prefix_tokens       ,	[self.tokenizer.get_lang_id(self.tokenizer.src_lang )] )

										lowerCamelCase_	:							Union[str, Any]									="zh"
										self.tokenizer._switch_to_target_mode()
										self.assertListEqual(self.tokenizer.prefix_tokens       ,	[self.tokenizer.get_lang_id("zh" )] )
										self.assertListEqual(self.tokenizer.suffix_tokens       ,	[self.tokenizer.eos_token_id] )
										self.tokenizer._switch_to_input_mode()
										self.assertListEqual(self.tokenizer.prefix_tokens       ,	[self.tokenizer.get_lang_id(self.tokenizer.src_lang )] )


			@require_torch
			def      UpperCAmelCase__						(				self					:  Dict ):
										lowerCamelCase_	:							str									=self.tokenizer._build_translation_inputs("A test"       ,	return_tensors="pt"       ,	src_lang="en"       ,	tgt_lang="ar" )

										self.assertEqual(
										    nested_simplify(_lowerCAmelCase )       ,	{
										        # en_XX, A, test, EOS
										        "input_ids": [[12_8022, 58, 4183, 2]],
										        "attention_mask": [[1, 1, 1, 1]],
										        # ar_AR
										        "forced_bos_token_id": 12_8006,
										    }       ,	)












"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__	:    List[Any]			 = {
    'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__	:    List[str]			 = [
						    'LILT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'LiltForQuestionAnswering',
						    'LiltForSequenceClassification',
						    'LiltForTokenClassification',
						    'LiltModel',
						    'LiltPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_lilt import (
												    LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    LiltForQuestionAnswering,
												    LiltForSequenceClassification,
												    LiltForTokenClassification,
												    LiltModel,
												    LiltPreTrainedModel,
												)

else:
						import sys

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



