



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

from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available


if is_sentencepiece_available():
				from transformers.models.marian.tokenization_marian import VOCAB_FILES_NAMES, save_json

from ...test_tokenization_common import TokenizerTesterMixin


_lowercase: int      			=		get_tests_dir("fixtures/test_sentencepiece.model")

_lowercase: List[str]      			=		{'''target_lang''': '''fi''', '''source_lang''': '''en'''}
_lowercase: int      			=		'''>>zh<<'''
_lowercase: Any      			=		'''Helsinki-NLP/'''

if is_torch_available():
				_lowercase: List[Any]      			=		'''pt'''
elif is_tf_available():
				_lowercase: Union[str, Any]      			=		'''tf'''
else:
				_lowercase: Union[str, Any]      			=		'''jax'''



@require_sentencepiece
class 	_lowercase							(   _A,      unittest.TestCase	):





	"""simple docstring"""
	__A							=							MarianTokenizer
	__A							=							False
	__A							=							True




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						super().setUp()
						a					     =   ['''</s>''', '''<unk>''', '''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''', '''\u0120''', '''<pad>''']
						a					     =   dict(zip(lowerCamelCase_		,       range(len(lowerCamelCase_		)		)		)		)
						a					     =   Path(self.tmpdirname		)
						save_json(lowerCamelCase_		,       save_dir / VOCAB_FILES_NAMES["vocab"]		)
						save_json(lowerCamelCase_		,       save_dir / VOCAB_FILES_NAMES["tokenizer_config_file"]		)
						if not (save_dir / VOCAB_FILES_NAMES["source_spm"]).exists():
											copyfile(lowerCamelCase_		,       save_dir / VOCAB_FILES_NAMES["source_spm"]		)
											copyfile(lowerCamelCase_		,       save_dir / VOCAB_FILES_NAMES["target_spm"]		)

						a					     =   MarianTokenizer.from_pretrained(self.tmpdirname		)
						tokenizer.save_pretrained(self.tmpdirname		)




	def      UpperCamelCase_       (self		,       **lowerCamelCase_		):
						"""simple docstring"""

						return MarianTokenizer.from_pretrained(self.tmpdirname		,       **lowerCamelCase_		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

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




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   '''</s>'''
						a					     =   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		):
						"""simple docstring"""

						a					     =   list(self.get_tokenizer().get_vocab().keys()		)

						self.assertEqual(vocab_keys[0]		,       "</s>"		)
						self.assertEqual(vocab_keys[1]		,       "<unk>"		)
						self.assertEqual(vocab_keys[-1]		,       "<pad>"		)
						self.assertEqual(len(lowerCamelCase_		)		,       9		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						self.assertEqual(self.get_tokenizer().vocab_size		,       9		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   MarianTokenizer.from_pretrained(F'''{ORG_NAME}opus-mt-en-de'''		)
						a					     =   en_de_tokenizer(["I am a small frog"]		,       return_tensors=lowerCamelCase_		)
						self.assertIsInstance(lowerCamelCase_		,       lowerCamelCase_		)
						a					     =   [38, 121, 14, 697, 38848, 0]
						self.assertListEqual(lowerCamelCase_		,       batch.input_ids[0]		)

						a					     =   tempfile.mkdtemp()
						en_de_tokenizer.save_pretrained(lowerCamelCase_		)
						a					     =   [x.name for x in Path(lowerCamelCase_		).glob("*"		)]
						self.assertIn("source.spm"		,       lowerCamelCase_		)
						MarianTokenizer.from_pretrained(lowerCamelCase_		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   self.get_tokenizer()

						a					     =   tok(
						    ["I am a small frog" * 1000, "I am a small frog"]		,       padding=lowerCamelCase_		,       truncation=lowerCamelCase_		,       return_tensors=lowerCamelCase_		)
						self.assertIsInstance(lowerCamelCase_		,       lowerCamelCase_		)
						self.assertEqual(batch.input_ids.shape		,       (2, 512)		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   self.get_tokenizer()
						a					     =   tok(["I am a tiny frog", "I am a small frog"]		,       padding=lowerCamelCase_		,       return_tensors=lowerCamelCase_		)
						self.assertIsInstance(lowerCamelCase_		,       lowerCamelCase_		)
						self.assertEqual(batch_smaller.input_ids.shape		,       (2, 10)		)




	@slow
	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   {'''input_ids''': [[43495, 462, 20, 42164, 1369, 52, 464, 132, 1703, 492, 13, 7491, 38999, 6, 8, 464, 132, 1703, 492, 13, 4669, 37867, 13, 7525, 27, 1593, 988, 13, 33972, 7029, 6, 20, 8251, 383, 2, 270, 5866, 3788, 2, 2353, 8251, 12338, 2, 13958, 387, 2, 3629, 6953, 188, 2900, 2, 13958, 8011, 11501, 23, 8460, 4073, 34009, 20, 435, 11439, 27, 8, 8460, 4073, 6004, 20, 9988, 375, 27, 33, 266, 1945, 1076, 1350, 37867, 3288, 5, 577, 1076, 4374, 8, 5082, 5, 26453, 257, 556, 403, 2, 242, 132, 383, 316, 492, 8, 10767, 6, 316, 304, 4239, 3, 0], [148, 15722, 19, 1839, 12, 1350, 13, 22327, 5082, 5418, 47567, 35938, 59, 318, 19552, 108, 2183, 54, 14976, 4835, 32, 547, 1114, 8, 315, 2417, 5, 92, 19088, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100], [36, 6395, 12570, 39147, 11597, 6, 266, 4, 45405, 7296, 3, 0, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100, 58100]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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="Helsinki-NLP/opus-mt-en-de"		,       revision="1a8c2263da11e68e50938f97e10cd57820bd504c"		,       decode_kwargs={"use_source_tokenizer": True}		,       )




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   MarianTokenizer.from_pretrained("hf-internal-testing/test-marian-two-vocabs"		)

						a					     =   '''Tämä on testi'''
						a					     =   '''This is a test'''

						a					     =   [76, 7, 2047, 2]
						a					     =   [69, 12, 11, 940, 2]

						a					     =   tokenizer(lowerCamelCase_		).input_ids
						self.assertListEqual(lowerCamelCase_		,       lowerCamelCase_		)

						a					     =   tokenizer(text_target=lowerCamelCase_		).input_ids
						self.assertListEqual(lowerCamelCase_		,       lowerCamelCase_		)

						a					     =   tokenizer.decode(lowerCamelCase_		,       skip_special_tokens=lowerCamelCase_		)
						self.assertEqual(lowerCamelCase_		,       lowerCamelCase_		)








"""simple docstring"""



from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A		:       Dict  				=		logging.get_logger(__name__)

__A		:       Union[str, Any]  				=		{
    '''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}





class 					_UpperCAmelCase       ( _A							):
					SCREAMING_SNAKE_CASE_		:				Union[str, Any]							    =   "vit_mae"




					def __init__(				self     :						Dict    ,						A     :						List[str]=7_68    ,						A     :						Any=12    ,						A     :						Union[str, Any]=12    ,						A     :						Tuple=30_72    ,						A     :						Any="gelu"    ,						A     :						Tuple=0.0    ,						A     :						List[str]=0.0    ,						A     :						Tuple=0.02    ,						A     :						Tuple=1e-12    ,						A     :						int=2_24    ,						A     :						Dict=16    ,						A     :						int=3    ,						A     :						Tuple=True    ,						A     :						Tuple=16    ,						A     :						Optional[Any]=5_12    ,						A     :						Union[str, Any]=8    ,						A     :						List[Any]=20_48    ,						A     :						Dict=0.75    ,						A     :						Any=False    ,						**A     :						Optional[int]    ,						)  ->  Union[str, Any]:
							super().__init__(**A   )

							lowercase_ : List[Any]							       =   hidden_size
							lowercase_ : str							       =   num_hidden_layers
							lowercase_ : List[Any]							       =   num_attention_heads
							lowercase_ : Any							       =   intermediate_size
							lowercase_ : Optional[int]							       =   hidden_act
							lowercase_ : List[Any]							       =   hidden_dropout_prob
							lowercase_ : int							       =   attention_probs_dropout_prob
							lowercase_ : int							       =   initializer_range
							lowercase_ : Dict							       =   layer_norm_eps
							lowercase_ : Optional[Any]							       =   image_size
							lowercase_ : str							       =   patch_size
							lowercase_ : Dict							       =   num_channels
							lowercase_ : Any							       =   qkv_bias
							lowercase_ : Union[str, Any]							       =   decoder_num_attention_heads
							lowercase_ : Optional[Any]							       =   decoder_hidden_size
							lowercase_ : List[str]							       =   decoder_num_hidden_layers
							lowercase_ : List[Any]							       =   decoder_intermediate_size
							lowercase_ : Optional[Any]							       =   mask_ratio
							lowercase_ : Optional[Any]							       =   norm_pix_loss



