



"""simple docstring"""


import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
    slow,
)

from ...test_tokenization_common import TokenizerTesterMixin


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

if is_torch_available():
				from transformers.models.mbart.modeling_mbart import shift_tokens_right

snake_case_				     =       25_0004
snake_case_				     =       25_0020







@require_sentencepiece
@require_tokenizers
class       A_			(     SCREAMING_SNAKE_CASE_	,   unittest.TestCase				):



						"""simple docstring"""
						__UpperCamelCase						=							MBartaaTokenizer
						__UpperCamelCase						=							MBartaaTokenizerFast
						__UpperCamelCase						=							True
						__UpperCamelCase						=							True






						def 	UpperCAmelCase__     (					self :Dict					)				->			Dict:
												super().setUp()

												# We have a SentencePiece fixture for testing
												UpperCAmelCase             = MBartaaTokenizer(lowercase_   ,  src_lang='en_XX'   ,  tgt_lang='ro_RO'   ,  keep_accents=lowercase_					)
												tokenizer.save_pretrained(self.tmpdirname					)






						def 	UpperCAmelCase__     (					self :Optional[int]					)				->			Optional[Any]:
												UpperCAmelCase             = '<s>'
												UpperCAmelCase             = 0

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






						def 	UpperCAmelCase__     (					self :Any					)				->			Optional[Any]:
												UpperCAmelCase             = 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_					)   ,  10_54					)






						def 	UpperCAmelCase__     (					self :Optional[Any]					)				->			Optional[int]:
												self.assertEqual(self.get_tokenizer().vocab_size   ,  10_54					)






						def 	UpperCAmelCase__     (					self :Any					)				->			Dict:
												UpperCAmelCase             = MBartaaTokenizer(lowercase_   ,  src_lang='en_XX'   ,  tgt_lang='ro_RO'   ,  keep_accents=lowercase_					)

												UpperCAmelCase             = 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_85, 46, 10, 1_70, 3_82]]   ,  )

												UpperCAmelCase             = 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', '.']   ,  )
												UpperCAmelCase             = tokenizer.convert_tokens_to_ids(lowercase_					)
												self.assertListEqual(
												    lowercase_   ,  [
												        value + tokenizer.fairseq_offset
												        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
												    ]   ,  )

												UpperCAmelCase             = 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>', '.']   ,  )






						@slow
						def 	UpperCAmelCase__     (					self :Optional[Any]					)				->			Any:
												# fmt: off
												UpperCAmelCase             = {'input_ids': [[25_00_04, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [25_00_04, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 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], [25_00_04, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 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='facebook/mbart-large-50'   ,  revision='d3913889c59cd5c9e456b269c376325eabad57e2'   ,  )






						def 	UpperCAmelCase__     (					self :List[str]					)				->			Dict:
												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

												UpperCAmelCase             = (self.rust_tokenizer_class, 'hf-internal-testing/tiny-random-mbart50', {})
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""					):
																								UpperCAmelCase             = self.rust_tokenizer_class.from_pretrained(lowercase_   ,  **lowercase_					)
																								UpperCAmelCase             = self.tokenizer_class.from_pretrained(lowercase_   ,  **lowercase_					)

																								UpperCAmelCase             = tempfile.mkdtemp()

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

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

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

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

																								UpperCAmelCase             = tokenizer_r.save_pretrained(lowercase_   ,  legacy_format=lowercase_					)
																								UpperCAmelCase             = 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
																								UpperCAmelCase             = tokenizer_r.from_pretrained(lowercase_					)
																								UpperCAmelCase             = 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_					)







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



						"""simple docstring"""
						__UpperCamelCase						=							"""facebook/mbart-large-50-one-to-many-mmt"""
						__UpperCamelCase						=							[
						    """ UN Chief Says There Is No Military Solution in Syria""",
						    """ Secretary-General Ban Ki-moon says his response to Russia's stepped up military support for Syria is that \"there is no military solution\" to the nearly five-year conflict and more weapons will only worsen the violence and misery for millions of people.""",
						]
						__UpperCamelCase						=							[
						    """Şeful ONU declară că nu există o soluţie militară în Siria""",
						    """Secretarul General Ban Ki-moon declară că răspunsul său la intensificarea sprijinului militar al Rusiei"""
						    """ pentru Siria este că \"nu există o soluţie militară\" la conflictul de aproape cinci ani şi că noi arme nu vor"""
						    """ face decât să înrăutăţească violenţele şi mizeria pentru milioane de oameni.""",
						]
						__UpperCamelCase						=							[EN_CODE, 82_74, 12_78_73, 2_59_16, 7, 86_22, 20_71, 4_38, 6_74_85, 53, 18_78_95, 23, 5_17_12, 2]






						@classmethod
						def 	UpperCAmelCase__     (					cls :int					)				->			Optional[int]:
												UpperCAmelCase             = MBartaaTokenizer.from_pretrained(
												    cls.checkpoint_name   ,  src_lang='en_XX'   ,  tgt_lang='ro_RO'					)
												UpperCAmelCase             = 1
												return cls






						def 	UpperCAmelCase__     (					self :Optional[Any]					)				->			Optional[Any]:
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ar_AR']   ,  25_00_01					)
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['en_EN']   ,  25_00_04					)
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['ro_RO']   ,  25_00_20					)
												self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['mr_IN']   ,  25_00_38					)






						def 	UpperCAmelCase__     (					self :Dict					)				->			Tuple:
												UpperCAmelCase             = self.tokenizer.batch_encode_plus(self.src_text					).input_ids[0]
												self.assertListEqual(self.expected_src_tokens   ,  lowercase_					)






						def 	UpperCAmelCase__     (					self :int					)				->			List[Any]:
												self.assertIn(lowercase_   ,  self.tokenizer.all_special_ids					)
												UpperCAmelCase             = [RO_CODE, 8_84, 90_19, 96, 9, 9_16, 8_67_92, 36, 1_87_43, 1_55_96, 5, 2]
												UpperCAmelCase             = self.tokenizer.decode(lowercase_   ,  skip_special_tokens=lowercase_					)
												UpperCAmelCase             = self.tokenizer.decode(generated_ids[1:]   ,  skip_special_tokens=lowercase_					)
												self.assertEqual(lowercase_   ,  lowercase_					)
												self.assertNotIn(self.tokenizer.eos_token   ,  lowercase_					)






						def 	UpperCAmelCase__     (					self :Tuple					)				->			str:
												UpperCAmelCase             = ['this is gunna be a long sentence ' * 20]
												assert isinstance(src_text[0]   ,  lowercase_					)
												UpperCAmelCase             = 10
												UpperCAmelCase             = self.tokenizer(lowercase_   ,  max_length=lowercase_   ,  truncation=lowercase_					).input_ids[0]
												self.assertEqual(ids[0]   ,  lowercase_					)
												self.assertEqual(ids[-1]   ,  2					)
												self.assertEqual(len(lowercase_					)   ,  lowercase_					)






						def 	UpperCAmelCase__     (					self :List[Any]					)				->			List[Any]:
												self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', 'ar_AR']					)   ,  [25_00_53, 25_00_01]					)






						def 	UpperCAmelCase__     (					self :List[str]					)				->			Optional[Any]:
												UpperCAmelCase             = tempfile.mkdtemp()
												UpperCAmelCase             = self.tokenizer.fairseq_tokens_to_ids
												self.tokenizer.save_pretrained(lowercase_					)
												UpperCAmelCase             = MBartaaTokenizer.from_pretrained(lowercase_					)
												self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,  lowercase_					)






						@require_torch
						def 	UpperCAmelCase__     (					self :Tuple					)				->			Any:
												UpperCAmelCase             = self.tokenizer(self.src_text   ,  text_target=self.tgt_text   ,  padding=lowercase_   ,  return_tensors='pt'					)
												UpperCAmelCase             = shift_tokens_right(batch['labels']   ,  self.tokenizer.pad_token_id					)

												# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
												assert batch.input_ids[1][0] == EN_CODE
												assert batch.input_ids[1][-1] == 2
												assert batch.labels[1][0] == RO_CODE
												assert batch.labels[1][-1] == 2
												assert batch.decoder_input_ids[1][:2].tolist() == [2, RO_CODE]






						@require_torch
						def 	UpperCAmelCase__     (					self :Tuple					)				->			Dict:
												UpperCAmelCase             = self.tokenizer(
												    self.src_text   ,  text_target=self.tgt_text   ,  padding=lowercase_   ,  truncation=lowercase_   ,  max_length=len(self.expected_src_tokens					)   ,  return_tensors='pt'   ,  )
												UpperCAmelCase             = shift_tokens_right(batch['labels']   ,  self.tokenizer.pad_token_id					)

												self.assertIsInstance(lowercase_   ,  lowercase_					)

												self.assertEqual((2, 14)   ,  batch.input_ids.shape					)
												self.assertEqual((2, 14)   ,  batch.attention_mask.shape					)
												UpperCAmelCase             = batch.input_ids.tolist()[0]
												self.assertListEqual(self.expected_src_tokens   ,  lowercase_					)
												self.assertEqual(2   ,  batch.decoder_input_ids[0, 0]					)  # decoder_start_token_id
												# Test that special tokens are reset
												self.assertEqual(self.tokenizer.prefix_tokens   ,  [EN_CODE]					)
												self.assertEqual(self.tokenizer.suffix_tokens   ,  [self.tokenizer.eos_token_id]					)






						def 	UpperCAmelCase__     (					self :Tuple					)				->			Any:
												UpperCAmelCase             = self.tokenizer(self.src_text   ,  padding=lowercase_   ,  truncation=lowercase_   ,  max_length=3   ,  return_tensors='pt'					)
												UpperCAmelCase             = self.tokenizer(
												    text_target=self.tgt_text   ,  padding=lowercase_   ,  truncation=lowercase_   ,  max_length=10   ,  return_tensors='pt'					)
												UpperCAmelCase             = targets['input_ids']
												UpperCAmelCase             = shift_tokens_right(lowercase_   ,  self.tokenizer.pad_token_id					)

												self.assertEqual(batch.input_ids.shape[1]   ,  3					)
												self.assertEqual(batch.decoder_input_ids.shape[1]   ,  10					)






						@require_torch
						def 	UpperCAmelCase__     (					self :Tuple					)				->			Any:
												UpperCAmelCase             = self.tokenizer._build_translation_inputs(
												    'A test'   ,  return_tensors='pt'   ,  src_lang='en_XX'   ,  tgt_lang='ar_AR'					)

												self.assertEqual(
												    nested_simplify(lowercase_					)   ,  {
												        # en_XX, A, test, EOS
												        'input_ids': [[25_00_04, 62, 30_34, 2]],
												        'attention_mask': [[1, 1, 1, 1]],
												        # ar_AR
												        'forced_bos_token_id': 25_00_01,
												    }   ,  )









'''simple docstring'''


import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowerCamelCase__					=   logging.get_logger(__name__)

lowerCamelCase__					=   {
    'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}






class 		lowerCAmelCase__	(	UpperCAmelCase__		):
			lowerCAmelCase       :		Any				      =   "deta"
			lowerCAmelCase       :		Union[str, Any]				      =   {
			    "hidden_size": "d_model",
			    "num_attention_heads": "encoder_attention_heads",
			}




			def __init__(						self     :   Optional[Any]		,     lowerCamelCase__     :   str=None		,     lowerCamelCase__     :   str=9_00		,     lowerCamelCase__     :   Any=20_48		,     lowerCamelCase__     :   Optional[int]=6		,     lowerCamelCase__     :   str=20_48		,     lowerCamelCase__     :   Dict=8		,     lowerCamelCase__     :   Any=6		,     lowerCamelCase__     :   Union[str, Any]=10_24		,     lowerCamelCase__     :   Optional[int]=8		,     lowerCamelCase__     :   List[Any]=0.0		,     lowerCamelCase__     :   Tuple=True		,     lowerCamelCase__     :   int="relu"		,     lowerCamelCase__     :   str=2_56		,     lowerCamelCase__     :   Dict=0.1		,     lowerCamelCase__     :   Dict=0.0		,     lowerCamelCase__     :   Dict=0.0		,     lowerCamelCase__     :   Optional[int]=0.0_2		,     lowerCamelCase__     :   List[Any]=1.0		,     lowerCamelCase__     :   Optional[int]=True		,     lowerCamelCase__     :   Any=False		,     lowerCamelCase__     :   Any="sine"		,     lowerCamelCase__     :   str=5		,     lowerCamelCase__     :   Optional[int]=4		,     lowerCamelCase__     :   int=4		,     lowerCamelCase__     :   Optional[Any]=True		,     lowerCamelCase__     :   Dict=3_00		,     lowerCamelCase__     :   int=True		,     lowerCamelCase__     :   Dict=True		,     lowerCamelCase__     :   Union[str, Any]=1		,     lowerCamelCase__     :   Any=5		,     lowerCamelCase__     :   List[Any]=2		,     lowerCamelCase__     :   Union[str, Any]=1		,     lowerCamelCase__     :   str=1		,     lowerCamelCase__     :   Union[str, Any]=5		,     lowerCamelCase__     :   str=2		,     lowerCamelCase__     :   Optional[Any]=0.1		,     lowerCamelCase__     :   Union[str, Any]=0.2_5		,     **lowerCamelCase__     :   Optional[Any]		,     )      ->List[str]:



					'''simple docstring'''







					if backbone_config is None:
							logger.info("`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone."       )
							_UpperCAmelCase						:				int	    =					CONFIG_MAPPING["resnet"](out_features=["stage2", "stage3", "stage4"]       )
					else:
							if isinstance(lowerCamelCase__		,     lowerCamelCase__       ):
									_UpperCAmelCase						:				Any	    =					backbone_config.pop("model_type"       )
									_UpperCAmelCase						:				Optional[int]	    =					CONFIG_MAPPING[backbone_model_type]
									_UpperCAmelCase						:				List[str]	    =					config_class.from_dict(lowerCamelCase__       )

					_UpperCAmelCase						:				Optional[Any]	    =					backbone_config
					_UpperCAmelCase						:				Optional[int]	    =					num_queries
					_UpperCAmelCase						:				Union[str, Any]	    =					max_position_embeddings
					_UpperCAmelCase						:				Union[str, Any]	    =					d_model
					_UpperCAmelCase						:				str	    =					encoder_ffn_dim
					_UpperCAmelCase						:				Optional[int]	    =					encoder_layers
					_UpperCAmelCase						:				int	    =					encoder_attention_heads
					_UpperCAmelCase						:				Union[str, Any]	    =					decoder_ffn_dim
					_UpperCAmelCase						:				Tuple	    =					decoder_layers
					_UpperCAmelCase						:				Union[str, Any]	    =					decoder_attention_heads
					_UpperCAmelCase						:				Any	    =					dropout
					_UpperCAmelCase						:				List[str]	    =					attention_dropout
					_UpperCAmelCase						:				Union[str, Any]	    =					activation_dropout
					_UpperCAmelCase						:				Optional[int]	    =					activation_function
					_UpperCAmelCase						:				str	    =					init_std
					_UpperCAmelCase						:				Tuple	    =					init_xavier_std
					_UpperCAmelCase						:				Optional[Any]	    =					encoder_layerdrop
					_UpperCAmelCase						:				int	    =					auxiliary_loss
					_UpperCAmelCase						:				Union[str, Any]	    =					position_embedding_type
					# deformable attributes
					_UpperCAmelCase						:				List[Any]	    =					num_feature_levels
					_UpperCAmelCase						:				List[Any]	    =					encoder_n_points
					_UpperCAmelCase						:				Tuple	    =					decoder_n_points
					_UpperCAmelCase						:				Optional[int]	    =					two_stage
					_UpperCAmelCase						:				Dict	    =					two_stage_num_proposals
					_UpperCAmelCase						:				int	    =					with_box_refine
					_UpperCAmelCase						:				str	    =					assign_first_stage
					if two_stage is True and with_box_refine is False:
							raise ValueError("If two_stage is True, with_box_refine must be True."       )
					# Hungarian matcher
					_UpperCAmelCase						:				Optional[int]	    =					class_cost
					_UpperCAmelCase						:				Dict	    =					bbox_cost
					_UpperCAmelCase						:				int	    =					giou_cost
					# Loss coefficients
					_UpperCAmelCase						:				int	    =					mask_loss_coefficient
					_UpperCAmelCase						:				List[Any]	    =					dice_loss_coefficient
					_UpperCAmelCase						:				Dict	    =					bbox_loss_coefficient
					_UpperCAmelCase						:				int	    =					giou_loss_coefficient
					_UpperCAmelCase						:				Optional[Any]	    =					eos_coefficient
					_UpperCAmelCase						:				int	    =					focal_alpha
					super().__init__(is_encoder_decoder=lowerCamelCase__		,     **lowerCamelCase__       )




			@property
			def 							lowerCAmelCase__			(						self     :   int       )      ->int:



					'''simple docstring'''







					return self.encoder_attention_heads




			@property
			def 							lowerCAmelCase__			(						self     :   List[Any]       )      ->int:



					'''simple docstring'''







					return self.d_model






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



					'''simple docstring'''







					_UpperCAmelCase						:				Optional[int]	    =					copy.deepcopy(self.__dict__       )
					_UpperCAmelCase						:				Tuple	    =					self.backbone_config.to_dict()
					_UpperCAmelCase						:				List[Any]	    =					self.__class__.model_type
					return output



