


"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


UpperCAmelCase__  							=logging.get_logger(__name__)

UpperCAmelCase__  							={
    "shi-labs/dinat-mini-in1k-224": "https://huggingface.co/shi-labs/dinat-mini-in1k-224/resolve/main/config.json",
    # See all Dinat models at https://huggingface.co/models?filter=dinat
}





class    lowerCamelCase__						(		_a			,   _a    ):
						a :     Optional[Any]											=		"""dinat"""

						a :     Dict											=		{
						    """num_attention_heads""": """num_heads""",
						    """num_hidden_layers""": """num_layers""",
						}
						def __init__(		self	:	Tuple      ,       A_	:	Optional[Any]=4      ,       A_	:	int=3      ,       A_	:	Tuple=6_4      ,       A_	:	Dict=[3, 4, 6, 5]      ,       A_	:	List[str]=[2, 4, 8, 1_6]      ,       A_	:	Any=7      ,       A_	:	List[str]=[[1, 8, 1], [1, 4, 1, 4], [1, 2, 1, 2, 1, 2], [1, 1, 1, 1, 1]]      ,       A_	:	Tuple=3.0      ,       A_	:	Any=True      ,       A_	:	List[str]=0.0      ,       A_	:	Any=0.0      ,       A_	:	List[str]=0.1      ,       A_	:	str="gelu"      ,       A_	:	Optional[Any]=0.02      ,       A_	:	Any=1e-5      ,       A_	:	List[Any]=0.0      ,       A_	:	int=None      ,       A_	:	Optional[int]=None      ,       **A_	:	str      ,       ):






							'''simple docstring'''


							super().__init__(**A_							)

							__lowercase									=	patch_size
							__lowercase									=	num_channels
							__lowercase									=	embed_dim
							__lowercase									=	depths
							__lowercase									=	len(A_							)
							__lowercase									=	num_heads
							__lowercase									=	kernel_size
							__lowercase									=	dilations
							__lowercase									=	mlp_ratio
							__lowercase									=	qkv_bias
							__lowercase									=	hidden_dropout_prob
							__lowercase									=	attention_probs_dropout_prob
							__lowercase									=	drop_path_rate
							__lowercase									=	hidden_act
							__lowercase									=	layer_norm_eps
							__lowercase									=	initializer_range
							# we set the hidden_size attribute in order to make Dinat work with VisionEncoderDecoderModel
							# this indicates the channel dimension after the last stage of the model
							__lowercase									=	int(embed_dim * 2 ** (len(A_							) - 1)							)
							__lowercase									=	layer_scale_init_value
							__lowercase									=	["""stem"""] + [F'''stage{idx}''' for idx in range(1      ,       len(A_							) + 1							)]
							__lowercase							,		__lowercase									=	get_aligned_output_features_output_indices(
							    out_features=A_      ,       out_indices=A_      ,       stage_names=self.stage_names							)




"""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():
       UpperCAmelCase__  							=get_tests_dir("fixtures/test_sentencepiece.model")


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

UpperCAmelCase__  							=12_8022
UpperCAmelCase__  							=12_8028





@require_sentencepiece
class    lowerCamelCase__						(		_a			,   unittest.TestCase    ):
      a :     Dict											=		MaMaaaTokenizer
      a :     Optional[int]											=		False
      a :     str											=		False
      a :     Any											=		True
      def SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       super().setUp()

       __lowercase									=	["""</s>""", """<unk>""", """▁This""", """▁is""", """▁a""", """▁t""", """est""", """\u0120""", """<pad>"""]
       __lowercase									=	dict(zip(A_      ,       range(len(A_							)							)							)							)
       __lowercase									=	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"""]							)

       __lowercase									=	MaMaaaTokenizer.from_pretrained(self.tmpdirname							)
       tokenizer.save_pretrained(self.tmpdirname							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[Any]      ,       **A_	:	List[Any]							):






       '''simple docstring'''


       return MaMaaaTokenizer.from_pretrained(self.tmpdirname      ,       **A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[int]      ,       A_	:	Optional[int]							):






       '''simple docstring'''


       return (
           "This is a test",
           "This is a test",
       )
      def SCREAMING_SNAKE_CASE_	(		self	:	str							):






       '''simple docstring'''


       __lowercase									=	"""</s>"""
       __lowercase									=	0

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(A_							)      ,       A_							)
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(A_							)      ,       A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]							):






       '''simple docstring'''


       __lowercase									=	self.get_tokenizer()
       __lowercase									=	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 SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       pass
      def SCREAMING_SNAKE_CASE_	(		self	:	Any							):






       '''simple docstring'''


       __lowercase									=	self.get_tokenizer()

       __lowercase									=	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]      ,       )

       __lowercase									=	tokenizer.convert_ids_to_tokens([2, 3, 4, 5, 6]							)
       self.assertListEqual(A_      ,       ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]							)

       __lowercase									=	tokenizer.convert_tokens_to_string(A_							)
       self.assertEqual(A_      ,       """This is a test"""							)






      @slow
      def SCREAMING_SNAKE_CASE_	(		self	:	Dict							):






       '''simple docstring'''


       __lowercase									=	{"""input_ids""": [[1_2_8_0_2_2, 1_1_0_1_0_8, 3_9_7, 1_1, 3_8_2_7_2, 2_2_4_7, 1_2_4_8_1_1, 2_8_5, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 3_9_5_3_4, 4_4_2_8, 3_9_7, 1_0_1_9, 1_8_1_0_5, 1_5_8_6, 2_0_7, 7, 4_1_3_3_7, 1_6_7_8_6, 2_4_1, 7, 2_0_2_1_4, 1_7, 1_2_5_6_9_0, 1_0_3_9_8, 7, 4_4_3_7_8, 5_8_0_6_9, 6_8_3_4_2, 7_7_9_8, 7_3_4_3, 1_1, 2_9_9, 3_3_3_1_0, 4, 1_5_8, 3_7_3_5_0, 9_4_0_7_7, 4_5_6_9, 2_9_9, 3_3_3_1_0, 9_0, 4, 5_2_8_4_0, 2_9_0, 4, 3_1_2_7_0, 1_1_2, 2_9_9, 6_8_2, 4, 5_2_8_4_0, 3_9_9_5_3, 1_4_0_7_9, 1_9_3, 5_2_5_1_9, 9_0_8_9_4, 1_7_8_9_4, 1_2_0_6_9_7, 1_1, 4_0_4_4_5, 5_5_1, 1_7, 1_0_1_9, 5_2_5_1_9, 9_0_8_9_4, 1_7_7_5_6, 9_6_3, 1_1, 4_0_4_4_5, 4_8_0, 1_7, 9_7_9_2, 1_1_2_0, 5_1_7_3, 1_3_9_3, 6_2_4_0, 1_6_7_8_6, 2_4_1, 1_2_0_9_9_6, 2_8, 1_2_4_5, 1_3_9_3, 1_1_8_2_4_0, 1_1_1_2_3, 1_0_1_9, 9_3_6_1_2, 2_6_9_1, 1_0_6_1_8, 9_8_0_5_8, 1_2_0_4_0_9, 1_9_2_8, 2_7_9, 4, 4_0_6_8_3, 3_6_7, 1_7_8, 2_0_7, 1_0_1_9, 1_0_3, 1_0_3_1_2_1, 5_0_6, 6_5_2_9_6, 5, 2], [1_2_8_0_2_2, 2_1_2_1_7, 3_6_7, 1_1_7, 1_2_5_4_5_0, 1_2_8, 7_1_9, 7, 7_3_0_8, 4_0, 9_3_6_1_2, 1_2_6_6_9, 1_1_1_6, 1_6_7_0_4, 7_1, 1_7_7_8_5, 3_6_9_9, 1_5_5_9_2, 3_5, 1_4_4, 9_5_8_4, 2_4_1, 1_1_9_4_3, 7_1_3, 9_5_0, 7_9_9, 2_2_4_7, 8_8_4_2_7, 1_5_0, 1_4_9, 1_1_8_8_1_3, 1_2_0_7_0_6, 1_0_1_9, 1_0_6_9_0_6, 8_1_5_1_8, 2_8, 1_2_2_4, 2_2_7_9_9, 3_9_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_2_8_0_2_2, 1_6_5_8, 1_2_3_3_1_1, 5_1_5_5, 5_5_7_8, 4_7_2_2, 2_7_9, 1_4_9_4_7, 2_3_6_6, 1_1_2_0, 1_1_9_7, 1_4, 1_3_4_8, 9_2_3_2, 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    lowerCamelCase__						(		unittest.TestCase    ):
      a :     Optional[int]											=		"""facebook/m2m100_418M"""
      a :     str											=		[
          """In my opinion, there are two levels of response from the French government.""",
          """NSA Affair Emphasizes Complete Lack of Debate on Intelligence""",
      ]
      a :     int											=		[
          """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
      a :     Optional[int]											=		[EN_CODE, 5_93, 19_49, 11_57_81, 4, 7_15_86, 42_34, 6_06_33, 12_62_33, 4_32, 12_38_08, 1_55_92, 11_97, 11_71_32, 12_06_18, 5, 2]
      @classmethod
      def SCREAMING_SNAKE_CASE_	(		cls	:	str							):






       '''simple docstring'''


       __lowercase									=	MaMaaaTokenizer.from_pretrained(
           cls.checkpoint_name      ,       src_lang="""en"""      ,       tgt_lang="""fr"""							)
       __lowercase									=	1
       return cls
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[Any]							):






       '''simple docstring'''


       self.assertEqual(self.tokenizer.get_lang_id("""ar"""							)      ,       1_2_8_0_0_6							)
       self.assertEqual(self.tokenizer.get_lang_id("""en"""							)      ,       1_2_8_0_2_2							)
       self.assertEqual(self.tokenizer.get_lang_id("""ro"""							)      ,       1_2_8_0_7_6							)
       self.assertEqual(self.tokenizer.get_lang_id("""mr"""							)      ,       1_2_8_0_6_3							)
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]							):






       '''simple docstring'''


       __lowercase									=	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 SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]							):






       '''simple docstring'''


       __lowercase									=	"""en"""
       __lowercase									=	self.tokenizer.batch_encode_plus(self.src_text							).input_ids[0]
       self.assertListEqual(self.expected_src_tokens      ,       A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[Any]							):






       '''simple docstring'''


       self.assertIn(A_      ,       self.tokenizer.all_special_ids							)
       # fmt: off
       __lowercase									=	[FR_CODE, 5_3_6_4, 8_2, 8_6_4_2, 4, 2_9_4, 4_7, 8, 1_4_0_2_8, 1_3_6, 3_2_8_6, 9_7_0_6, 6, 9_0_7_9_7, 6, 1_4_4_0_1_2, 1_6_2, 8_8_1_2_8, 3_0_0_6_1, 5, 2]
       # fmt: on
       __lowercase									=	self.tokenizer.decode(A_      ,       skip_special_tokens=A_							)
       __lowercase									=	self.tokenizer.decode(generated_ids[1:]      ,       skip_special_tokens=A_							)
       self.assertEqual(A_      ,       A_							)
       self.assertNotIn(self.tokenizer.eos_token      ,       A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       __lowercase									=	tempfile.mkdtemp()
       __lowercase									=	self.tokenizer.lang_token_to_id
       self.tokenizer.save_pretrained(A_							)
       __lowercase									=	MaMaaaTokenizer.from_pretrained(A_							)
       self.assertDictEqual(new_tok.lang_token_to_id      ,       A_							)
      @require_torch
      def SCREAMING_SNAKE_CASE_	(		self	:	List[Any]							):






       '''simple docstring'''


       __lowercase									=	"""en"""
       __lowercase									=	"""fr"""

       __lowercase									=	self.tokenizer(self.src_text      ,       text_target=self.tgt_text      ,       padding=A_      ,       return_tensors="""pt"""							)

       __lowercase									=	shift_tokens_right(
           batch["""labels"""]      ,       self.tokenizer.pad_token_id      ,       self.tokenizer.eos_token_id							)

       for k in batch:
        __lowercase									=	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 SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


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

       __lowercase									=	"""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 SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]							):






       '''simple docstring'''


       __lowercase									=	"""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							)]							)

       __lowercase									=	"""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 SCREAMING_SNAKE_CASE_	(		self	:	int							):






       '''simple docstring'''


       __lowercase									=	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""": [[1_2_8_0_2_2, 5_8, 4_1_8_3, 2]],
               """attention_mask""": [[1, 1, 1, 1]],
               # ar_AR
               """forced_bos_token_id""": 1_2_8_0_0_6,
           }      ,       )
