
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():
				lowercase__							:							Dict									=			get_tests_dir("fixtures/test_sentencepiece.model")


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

lowercase__							:							Optional[int]									=			1_2_8_0_2_2
lowercase__							:							str									=			1_2_8_0_2_8






@require_sentencepiece
class        SCREAMING_SNAKE_CASE__    (							_UpperCamelCase   ,		unittest.TestCase    ):

							"""simple docstring"""






							_snake_case     		=  MaMaaaTokenizer
							_snake_case     		=  False
							_snake_case     		=  False
							_snake_case     		=  True



							def     A__		(  self			)->   str:





								'''simple docstring'''






								super().setUp()

								__UpperCamelCase       =			["</s>", "<unk>", "▁This", "▁is", "▁a", "▁t", "est", "\u0120", "<pad>"]
								__UpperCamelCase       =			dict(zip(__a     ,	range(len(__a			)			)			)			)
								__UpperCamelCase       =			Path(self.tmpdirname			)
								save_json(__a     ,	save_dir / VOCAB_FILES_NAMES['''vocab_file''']			)
								if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
									copyfile(__a     ,	save_dir / VOCAB_FILES_NAMES['''spm_file''']			)

								__UpperCamelCase       =			MaMaaaTokenizer.from_pretrained(self.tmpdirname			)
								tokenizer.save_pretrained(self.tmpdirname			)



							def     A__		(  self     ,	**SCREAMING_SNAKE_CASE_			)->   Optional[int]:





								'''simple docstring'''






								return MaMaaaTokenizer.from_pretrained(self.tmpdirname     ,	**__a			)



							def     A__		(  self     ,	SCREAMING_SNAKE_CASE_			)->   int:





								'''simple docstring'''






								return (
								    "This is a test",
								    "This is a test",
								)



							def     A__		(  self			)->   Union[str, Any]:





								'''simple docstring'''






								__UpperCamelCase       =			"</s>"
								__UpperCamelCase       =			0

								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			)->   int:





								'''simple docstring'''






								__UpperCamelCase       =			self.get_tokenizer()
								__UpperCamelCase       =			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(__a			)     ,	tokenizer.vocab_size + len(tokenizer.get_added_vocab()			)			)



							@unittest.skip('''Skip this test while all models are still to be uploaded.'''			)
							def     A__		(  self			)->   Optional[int]:





								'''simple docstring'''






								pass



							def     A__		(  self			)->   str:





								'''simple docstring'''






								__UpperCamelCase       =			self.get_tokenizer()

								__UpperCamelCase       =			tokenizer.tokenize('''This is a test'''			)
								self.assertListEqual(__a     ,	['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']			)

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

								__UpperCamelCase       =			tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]			)
								self.assertListEqual(__a     ,	['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']			)

								__UpperCamelCase       =			tokenizer.convert_tokens_to_string(__a			)
								self.assertEqual(__a     ,	'''This is a test'''			)



							@slow
							def     A__		(  self			)->   Tuple:





								'''simple docstring'''






								__UpperCamelCase       =			{"input_ids": [[128022, 110108, 397, 11, 38272, 2247, 124811, 285, 18105, 1586, 207, 7, 39534, 4428, 397, 1019, 18105, 1586, 207, 7, 41337, 16786, 241, 7, 20214, 17, 125690, 10398, 7, 44378, 58069, 68342, 7798, 7343, 11, 299, 33310, 4, 158, 37350, 94077, 4569, 299, 33310, 90, 4, 52840, 290, 4, 31270, 112, 299, 682, 4, 52840, 39953, 14079, 193, 52519, 90894, 17894, 120697, 11, 40445, 551, 17, 1019, 52519, 90894, 17756, 963, 11, 40445, 480, 17, 9792, 1120, 5173, 1393, 6240, 16786, 241, 120996, 28, 1245, 1393, 118240, 11123, 1019, 93612, 2691, 10618, 98058, 120409, 1928, 279, 4, 40683, 367, 178, 207, 1019, 103, 103121, 506, 65296, 5, 2], [128022, 21217, 367, 117, 125450, 128, 719, 7, 7308, 40, 93612, 12669, 1116, 16704, 71, 17785, 3699, 15592, 35, 144, 9584, 241, 11943, 713, 950, 799, 2247, 88427, 150, 149, 118813, 120706, 1019, 106906, 81518, 28, 1224, 22799, 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], [128022, 1658, 123311, 5155, 5578, 4722, 279, 14947, 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=__a     ,	model_name='''facebook/m2m100_418M'''     ,	revision='''c168bae485c864188cf9aa0e4108b0b6934dc91e'''     ,	)






@require_torch
@require_sentencepiece
@require_tokenizers
class        SCREAMING_SNAKE_CASE__    (							unittest.TestCase    ):

							"""simple docstring"""






							_snake_case     		=  "facebook/m2m100_418M"
							_snake_case     		=  [
							    "In my opinion, there are two levels of response from the French government.",
							    "NSA Affair Emphasizes Complete Lack of Debate on Intelligence",
							]
							_snake_case     		=  [
							    "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
							_snake_case     		=  [EN_CODE, 593, 1949, 115781, 4, 71586, 4234, 60633, 126233, 432, 123808, 15592, 1197, 117132, 120618, 5, 2]



							@classmethod
							def     A__		(  cls			)->   str:





								'''simple docstring'''






								__UpperCamelCase       =			MaMaaaTokenizer.from_pretrained(
								    cls.checkpoint_name     ,	src_lang='''en'''     ,	tgt_lang='''fr'''			)
								__UpperCamelCase       =			1
								return cls



							def     A__		(  self			)->   Optional[Any]:





								'''simple docstring'''






								self.assertEqual(self.tokenizer.get_lang_id('''ar'''			)     ,	128006			)
								self.assertEqual(self.tokenizer.get_lang_id('''en'''			)     ,	128022			)
								self.assertEqual(self.tokenizer.get_lang_id('''ro'''			)     ,	128076			)
								self.assertEqual(self.tokenizer.get_lang_id('''mr'''			)     ,	128063			)



							def     A__		(  self			)->   Union[str, Any]:





								'''simple docstring'''






								__UpperCamelCase       =			self.tokenizer.get_vocab()
								self.assertEqual(len(__a			)     ,	self.tokenizer.vocab_size			)
								self.assertEqual(vocab['''<unk>''']     ,	3			)
								self.assertIn(self.tokenizer.get_lang_token('''en'''			)     ,	__a			)



							def     A__		(  self			)->   str:





								'''simple docstring'''






								__UpperCamelCase       =			"en"
								__UpperCamelCase       =			self.tokenizer.batch_encode_plus(self.src_text			).input_ids[0]
								self.assertListEqual(self.expected_src_tokens     ,	__a			)



							def     A__		(  self			)->   Optional[Any]:





								'''simple docstring'''






								self.assertIn(__a     ,	self.tokenizer.all_special_ids			)
								# fmt: off
								__UpperCamelCase       =			[FR_CODE, 5364, 82, 8642, 4, 294, 47, 8, 14028, 136, 3286, 9706, 6, 90797, 6, 144012, 162, 88128, 30061, 5, 2]
								# fmt: on
								__UpperCamelCase       =			self.tokenizer.decode(__a     ,	skip_special_tokens=__a			)
								__UpperCamelCase       =			self.tokenizer.decode(generated_ids[1:]     ,	skip_special_tokens=__a			)
								self.assertEqual(__a     ,	__a			)
								self.assertNotIn(self.tokenizer.eos_token     ,	__a			)



							def     A__		(  self			)->   Optional[Any]:





								'''simple docstring'''






								__UpperCamelCase       =			tempfile.mkdtemp()
								__UpperCamelCase       =			self.tokenizer.lang_token_to_id
								self.tokenizer.save_pretrained(__a			)
								__UpperCamelCase       =			MaMaaaTokenizer.from_pretrained(__a			)
								self.assertDictEqual(new_tok.lang_token_to_id     ,	__a			)



							@require_torch
							def     A__		(  self			)->   Any:





								'''simple docstring'''






								__UpperCamelCase       =			"en"
								__UpperCamelCase       =			"fr"

								__UpperCamelCase       =			self.tokenizer(self.src_text     ,	text_target=self.tgt_text     ,	padding=__a     ,	return_tensors='''pt'''			)

								__UpperCamelCase       =			shift_tokens_right(
								    batch['''labels''']     ,	self.tokenizer.pad_token_id     ,	self.tokenizer.eos_token_id			)

								for k in batch:
									__UpperCamelCase       =			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     A__		(  self			)->   Optional[Any]:





								'''simple docstring'''






								__UpperCamelCase       =			"mr"
								self.assertListEqual(self.tokenizer.prefix_tokens     ,	[self.tokenizer.get_lang_id('''mr'''			)]			)
								self.assertListEqual(self.tokenizer.suffix_tokens     ,	[self.tokenizer.eos_token_id]			)

								__UpperCamelCase       =			"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     A__		(  self			)->   List[str]:





								'''simple docstring'''






								__UpperCamelCase       =			"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			)]			)

								__UpperCamelCase       =			"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     A__		(  self			)->   Optional[Any]:





								'''simple docstring'''






								__UpperCamelCase       =			self.tokenizer._build_translation_inputs('''A test'''     ,	return_tensors='''pt'''     ,	src_lang='''en'''     ,	tgt_lang='''ar'''			)

								self.assertEqual(
								    nested_simplify(__a			)     ,	{
								        # en_XX, A, test, EOS
								        '''input_ids''': [[128022, 58, 4183, 2]],
								        '''attention_mask''': [[1, 1, 1, 1]],
								        # ar_AR
								        '''forced_bos_token_id''': 128006,
								    }     ,	)






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase__							:							int									=			{
    "configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
    "processing_git": ["GitProcessor"],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase__							:							Tuple									=			[
				    "GIT_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "GitForCausalLM",
				    "GitModel",
				    "GitPreTrainedModel",
				    "GitVisionModel",
				]

if TYPE_CHECKING:
				from .configuration_git import GIT_PRETRAINED_CONFIG_ARCHIVE_MAP, GitConfig, GitVisionConfig
				from .processing_git import GitProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_git import (
								    GIT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    GitForCausalLM,
								    GitModel,
								    GitPreTrainedModel,
								    GitVisionModel,
								)

else:
				import sys

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




