






'''simple docstring'''







import copy
from typing import Dict, List, Optional

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


UpperCamelCase    :      List[Any]  			=		{
    'facebook/mask2former-swin-small-coco-instance': (
        'https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json'
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

UpperCamelCase    :      int  			=		logging.get_logger(__name__)




class 		UpperCamelCase__    (a			):




		'''simple docstring'''





		_UpperCamelCase				  =					'mask2former'
		_UpperCamelCase				  =					['swin']
		_UpperCamelCase				  =					{'hidden_size': 'hidden_dim'}






		def __init__(      self   ,_lowerCAmelCase = None   ,_lowerCAmelCase = 2_56   ,_lowerCAmelCase = 2_56   ,_lowerCAmelCase = 2_56   ,_lowerCAmelCase = 10_24   ,_lowerCAmelCase = "relu"   ,_lowerCAmelCase = 6   ,_lowerCAmelCase = 10   ,_lowerCAmelCase = 8   ,_lowerCAmelCase = 0.0   ,_lowerCAmelCase = 20_48   ,_lowerCAmelCase = False   ,_lowerCAmelCase = False   ,_lowerCAmelCase = 4   ,_lowerCAmelCase = 2_55   ,_lowerCAmelCase = 1_00   ,_lowerCAmelCase = 0.1   ,_lowerCAmelCase = 2.0   ,_lowerCAmelCase = 5.0   ,_lowerCAmelCase = 5.0   ,_lowerCAmelCase = 1_25_44   ,_lowerCAmelCase = 3.0   ,_lowerCAmelCase = 0.75   ,_lowerCAmelCase = 0.02   ,_lowerCAmelCase = 1.0   ,_lowerCAmelCase = True   ,_lowerCAmelCase = [4, 8, 16, 32]   ,_lowerCAmelCase = None   ,**_lowerCAmelCase   ,):
								if backbone_config is None:
														logger.info("""`backbone_config` is `None`. Initializing the config with the default `Swin` backbone."""       )
														lowerCamelCase__         =  CONFIG_MAPPING["""swin"""](
														    image_size=2_24   ,in_channels=3   ,patch_size=4   ,embed_dim=96   ,depths=[2, 2, 18, 2]   ,num_heads=[3, 6, 12, 24]   ,window_size=7   ,drop_path_rate=0.3   ,use_absolute_embeddings=_lowerCAmelCase   ,out_features=["""stage1""", """stage2""", """stage3""", """stage4"""]   ,)

								if isinstance(_lowerCAmelCase   ,_lowerCAmelCase       ):
														lowerCamelCase__         =  backbone_config.pop("""model_type"""       )
														lowerCamelCase__         =  CONFIG_MAPPING[backbone_model_type]
														lowerCamelCase__         =  config_class.from_dict(_lowerCAmelCase       )

								# verify that the backbone is supported
								if backbone_config.model_type not in self.backbones_supported:
														logger.warning_once(
														    F'''Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. '''
														    F'''Supported model types: {",".join(self.backbones_supported       )}'''       )

								lowerCamelCase__         =  backbone_config
								lowerCamelCase__         =  feature_size
								lowerCamelCase__         =  mask_feature_size
								lowerCamelCase__         =  hidden_dim
								lowerCamelCase__         =  encoder_feedforward_dim
								lowerCamelCase__         =  activation_function
								lowerCamelCase__         =  encoder_layers
								lowerCamelCase__         =  decoder_layers
								lowerCamelCase__         =  num_attention_heads
								lowerCamelCase__         =  dropout
								lowerCamelCase__         =  dim_feedforward
								lowerCamelCase__         =  pre_norm
								lowerCamelCase__         =  enforce_input_projection
								lowerCamelCase__         =  common_stride
								lowerCamelCase__         =  ignore_value
								lowerCamelCase__         =  num_queries
								lowerCamelCase__         =  no_object_weight
								lowerCamelCase__         =  class_weight
								lowerCamelCase__         =  mask_weight
								lowerCamelCase__         =  dice_weight
								lowerCamelCase__         =  train_num_points
								lowerCamelCase__         =  oversample_ratio
								lowerCamelCase__         =  importance_sample_ratio
								lowerCamelCase__         =  init_std
								lowerCamelCase__         =  init_xavier_std
								lowerCamelCase__         =  use_auxiliary_loss
								lowerCamelCase__         =  feature_strides
								lowerCamelCase__         =  output_auxiliary_logits
								lowerCamelCase__         =  decoder_layers

								super().__init__(**_lowerCAmelCase       )






		@classmethod
		def 			UpperCamelCase_					(      cls   ,_lowerCAmelCase   ,**_lowerCAmelCase       ):
								return cls(
								    backbone_config=_lowerCAmelCase   ,**_lowerCAmelCase   ,)






		def 			UpperCamelCase_					(      self       ):
								lowerCamelCase__         =  copy.deepcopy(self.__dict__       )
								lowerCamelCase__         =  self.backbone_config.to_dict()
								lowerCamelCase__         =  self.__class__.model_type
								return output









'''simple docstring'''







import unittest

from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase    :      List[Any]  			=		get_tests_dir('fixtures/test_sentencepiece_with_bytefallback.model')




@require_sentencepiece
@require_tokenizers
class 		UpperCamelCase__    (a   ,unittest.TestCase			):




		'''simple docstring'''





		_UpperCamelCase				  =					GPTSwaTokenizer
		_UpperCamelCase				  =					False
		_UpperCamelCase				  =					True
		_UpperCamelCase				  =					False






		def 			UpperCamelCase_					(      self       ):
								super().setUp()

								# We have a SentencePiece fixture for testing
								lowerCamelCase__         =  GPTSwaTokenizer(_lowerCAmelCase   ,eos_token="""<unk>"""   ,bos_token="""<unk>"""   ,pad_token="""<unk>"""       )

								tokenizer.save_pretrained(self.tmpdirname       )






		def 			UpperCamelCase_					(      self   ,_lowerCAmelCase       ):
								lowerCamelCase__         =  """This is a test"""
								lowerCamelCase__         =  """This is a test"""
								return input_text, output_text






		def 			UpperCamelCase_					(      self       ):
								lowerCamelCase__         =  """<s>"""
								lowerCamelCase__         =  1

								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       ):
								lowerCamelCase__         =  list(self.get_tokenizer().get_vocab().keys()       )

								self.assertEqual(vocab_keys[0]   ,"""<unk>"""       )
								self.assertEqual(vocab_keys[1]   ,"""<s>"""       )
								self.assertEqual(vocab_keys[-1]   ,"""j"""       )
								self.assertEqual(len(_lowerCAmelCase       )   ,20_00       )






		def 			UpperCamelCase_					(      self       ):
								self.assertEqual(self.get_tokenizer().vocab_size   ,20_00       )






		def 			UpperCamelCase_					(      self       ):
								lowerCamelCase__         =  GPTSwaTokenizer(_lowerCAmelCase       )

								lowerCamelCase__         =  tokenizer.tokenize("""This is a test"""       )
								self.assertListEqual(_lowerCAmelCase   ,["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]       )

								self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase       )   ,[4_65, 2_87, 2_65, 6_31, 8_42]       )

								lowerCamelCase__         =  tokenizer.tokenize("""I was born in 92000, and this is falsé."""       )
								# fmt: off
								self.assertListEqual(
								    _lowerCAmelCase   ,["""▁I""", """▁was""", """▁bor""", """n""", """▁in""", """▁""", """<0x39>""", """2""", """0""", """0""", """0""", """,""", """▁and""", """▁this""", """▁is""", """▁f""", """al""", """s""", """<0xC3>""", """<0xA9>""", """."""]   ,)
								# fmt: on

								lowerCamelCase__         =  tokenizer.convert_tokens_to_ids(_lowerCAmelCase       )
								self.assertListEqual(
								    _lowerCAmelCase   ,[2_62, 2_72, 15_25, 2_86, 2_71, 2_68, 60, 9_16, 6_33, 6_33, 6_33, 2_59, 2_66, 3_01, 2_87, 3_84, 3_67, 2_63, 1_98, 1_72, 2_60]   ,)

								lowerCamelCase__         =  tokenizer.convert_ids_to_tokens(_lowerCAmelCase       )
								# fmt: off
								self.assertListEqual(
								    _lowerCAmelCase   ,["""▁I""", """▁was""", """▁bor""", """n""", """▁in""", """▁""", """<0x39>""", """2""", """0""", """0""", """0""", """,""", """▁and""", """▁this""", """▁is""", """▁f""", """al""", """s""", """<0xC3>""", """<0xA9>""", """."""]       )
								# fmt: on






		def 			UpperCamelCase_					(      self       ):
								lowerCamelCase__         =  GPTSwaTokenizer(_lowerCAmelCase       )
								lowerCamelCase__         =  ["""This is a test""", """I was born in 92000, and this is falsé."""]
								lowerCamelCase__         =  [
								    [4_65, 2_87, 2_65, 6_31, 8_42],
								    [2_62, 2_72, 15_25, 2_86, 2_71, 2_68, 60, 9_16, 6_33, 6_33, 6_33, 2_59, 2_66, 3_01, 2_87, 3_84, 3_67, 2_63, 1_98, 1_72, 2_60],
								]

								# Test that encode_fast returns the same as tokenize + convert_tokens_to_ids
								for text, expected_ids in zip(_lowerCAmelCase   ,_lowerCAmelCase       ):
														self.assertListEqual(tokenizer.encode_fast(_lowerCAmelCase       )   ,_lowerCAmelCase       )

								# Test that decode_fast returns the input text
								for text, token_ids in zip(_lowerCAmelCase   ,_lowerCAmelCase       ):
														self.assertEqual(tokenizer.decode_fast(_lowerCAmelCase       )   ,_lowerCAmelCase       )






		@slow
		def 			UpperCamelCase_					(      self       ):
								lowerCamelCase__         =  [
								    """<|python|>def fibonacci(n)\n    if n < 0:\n        print('Incorrect input')""",
								    """Hey there, how are you doing this fine day?""",
								    """This is a text with a trailing spaces followed by a dot     .""",
								    """Häj sväjs lillebrör! =)""",
								    """Det är inget fel på Mr. Cool""",
								]

								# fmt: off
								lowerCamelCase__         =  {"""input_ids""": [[6_34_23, 5, 68_11, 1_49_54, 2_82, 8_16, 38_21, 6_34_66, 6_34_25, 6_34_62, 18, 6_39_78, 6_78, 3_01, 13_20, 6_34_23, 6_34_55, 6_34_58, 18, 6_39_82, 42_46, 39_40, 19_01, 4_77_89, 55_47, 1_89_94], [1_96_30, 11_00, 6_34_46, 13_42, 6_33, 5_44, 44_88, 5_93, 51_02, 24_16, 6_34_95, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [16_52, 4_28, 2_68, 19_36, 5_15, 2_68, 5_85_93, 2_24_13, 91_06, 5_46, 2_68, 3_32_13, 6_39_79, 6_98, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_51_30, 6_34_50, 9_24, 6_34_49, 22_49, 40_62, 15_58, 3_18, 6_35_04, 2_14_98, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [5_09, 3_77, 28_27, 25_59, 3_32, 65_75, 6_34_43, 2_68_01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """token_type_ids""": [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [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], [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]]}
								# fmt: on
								self.tokenizer_integration_test_util(
								    expected_encoding=_lowerCAmelCase   ,model_name="""AI-Sweden/gpt-sw3-126m"""   ,sequences=_lowerCAmelCase   ,)

