





'''simple docstring'''


import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase					:     str												=get_tests_dir('''fixtures/test_sentencepiece.model''')
@require_sentencepiece
@require_tokenizers
class       a_   (				__lowercase	,						unittest.TestCase							):
     __A      =			ReformerTokenizer
     __A      =			ReformerTokenizerFast
     __A      =			True
     __A      =			False
     __A      =			True





     def 							lowercase__      ( self		:					Dict						):





        """simple docstring"""




        super().setUp()

        lowercase_			:Optional[int]    			= ReformerTokenizer(SCREAMING_SNAKE_CASE__	,      keep_accents=SCREAMING_SNAKE_CASE__						)
        tokenizer.save_pretrained(self.tmpdirname						)





     def 							lowercase__      ( self		:					Any						):





        """simple docstring"""




        lowercase_			:Any    			= "<s>"
        lowercase_			:List[Any]    			= 1

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





     def 							lowercase__      ( self		:					List[str]						):





        """simple docstring"""




        lowercase_			:str    			= 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(SCREAMING_SNAKE_CASE__						)	,      1_000						)





     def 							lowercase__      ( self		:					Tuple						):





        """simple docstring"""




        self.assertEqual(self.get_tokenizer().vocab_size	,      1_000						)





     def 							lowercase__      ( self		:					List[str]						):





        """simple docstring"""




        if not self.test_rust_tokenizer:
           return

        lowercase_			:Optional[Any]    			= self.get_tokenizer()
        lowercase_			:Dict    			= self.get_rust_tokenizer()

        lowercase_			:int    			= "I was born in 92000, and this is falsé."

        lowercase_			:Dict    			= tokenizer.tokenize(SCREAMING_SNAKE_CASE__						)
        lowercase_			:Any    			= rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE__						)
        self.assertListEqual(SCREAMING_SNAKE_CASE__	,      SCREAMING_SNAKE_CASE__						)

        lowercase_			:Any    			= tokenizer.encode(SCREAMING_SNAKE_CASE__	,      add_special_tokens=SCREAMING_SNAKE_CASE__						)
        lowercase_			:List[str]    			= rust_tokenizer.encode(SCREAMING_SNAKE_CASE__	,      add_special_tokens=SCREAMING_SNAKE_CASE__						)
        self.assertListEqual(SCREAMING_SNAKE_CASE__	,      SCREAMING_SNAKE_CASE__						)

        lowercase_			:int    			= self.get_rust_tokenizer()
        lowercase_			:Any    			= tokenizer.encode(SCREAMING_SNAKE_CASE__						)
        lowercase_			:Optional[int]    			= rust_tokenizer.encode(SCREAMING_SNAKE_CASE__						)
        self.assertListEqual(SCREAMING_SNAKE_CASE__	,      SCREAMING_SNAKE_CASE__						)





     def 							lowercase__      ( self		:					Union[str, Any]	,      lowercase		:					Optional[Any]=15						):





        """simple docstring"""




        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
           with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'						):
              lowercase_			:Any    			= self.rust_tokenizer_class.from_pretrained(SCREAMING_SNAKE_CASE__	,      **SCREAMING_SNAKE_CASE__						)

              # Simple input
              lowercase_			:Dict    			= "This is a simple input"
              lowercase_			:Union[str, Any]    			= ["This is a simple input 1", "This is a simple input 2"]
              lowercase_			:List[Any]    			= ("This is a simple input", "This is a pair")
              lowercase_			:str    			= [
                  ("This is a simple input 1", "This is a simple input 2"),
                  ("This is a simple pair 1", "This is a simple pair 2"),
              ]

              # Simple input tests
              self.assertRaises(SCREAMING_SNAKE_CASE__	,      tokenizer_r.encode	,      SCREAMING_SNAKE_CASE__	,      max_length=SCREAMING_SNAKE_CASE__	,      padding="max_length"						)

              # Simple input
              self.assertRaises(SCREAMING_SNAKE_CASE__	,      tokenizer_r.encode_plus	,      SCREAMING_SNAKE_CASE__	,      max_length=SCREAMING_SNAKE_CASE__	,      padding="max_length"						)

              # Simple input
              self.assertRaises(
                  SCREAMING_SNAKE_CASE__	,      tokenizer_r.batch_encode_plus	,      SCREAMING_SNAKE_CASE__	,      max_length=SCREAMING_SNAKE_CASE__	,      padding="max_length"	,      )

              # Pair input
              self.assertRaises(SCREAMING_SNAKE_CASE__	,      tokenizer_r.encode	,      SCREAMING_SNAKE_CASE__	,      max_length=SCREAMING_SNAKE_CASE__	,      padding="max_length"						)

              # Pair input
              self.assertRaises(SCREAMING_SNAKE_CASE__	,      tokenizer_r.encode_plus	,      SCREAMING_SNAKE_CASE__	,      max_length=SCREAMING_SNAKE_CASE__	,      padding="max_length"						)

              # Pair input
              self.assertRaises(
                  SCREAMING_SNAKE_CASE__	,      tokenizer_r.batch_encode_plus	,      SCREAMING_SNAKE_CASE__	,      max_length=SCREAMING_SNAKE_CASE__	,      padding="max_length"	,      )





     def 							lowercase__      ( self		:					Optional[Any]						):





        """simple docstring"""




        pass





     def 							lowercase__      ( self		:					int						):





        """simple docstring"""




        lowercase_			:List[str]    			= ReformerTokenizer(SCREAMING_SNAKE_CASE__	,      keep_accents=SCREAMING_SNAKE_CASE__						)

        lowercase_			:Any    			= tokenizer.tokenize("This is a test"						)
        self.assertListEqual(SCREAMING_SNAKE_CASE__	,      ["▁This", "▁is", "▁a", "▁t", "est"]						)

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__						)	,      [285, 46, 10, 170, 382]	,      )

        lowercase_			:Union[str, Any]    			= tokenizer.tokenize("I was born in 92000, and this is falsé."						)
        self.assertListEqual(
            SCREAMING_SNAKE_CASE__	,      [
                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",
                ".",
            ]	,      )
        lowercase_			:Optional[Any]    			= tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__						)
        self.assertListEqual(
            SCREAMING_SNAKE_CASE__	,      [8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]	,      )

        lowercase_			:str    			= tokenizer.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__						)
        self.assertListEqual(
            SCREAMING_SNAKE_CASE__	,      [
                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>",
                ".",
            ]	,      )





     @cached_property
     def 							lowercase__      ( self		:					List[Any]						):





        """simple docstring"""




        return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment"						)





     @slow
     def 							lowercase__      ( self		:					str						):





        """simple docstring"""




        lowercase_			:Union[str, Any]    			= "Hello World!"
        lowercase_			:List[str]    			= [126, 32, 262, 152, 38, 72, 287]

        self.assertListEqual(SCREAMING_SNAKE_CASE__	,      self.big_tokenizer.encode(SCREAMING_SNAKE_CASE__						)						)





     @slow
     def 							lowercase__      ( self		:					Dict						):





        """simple docstring"""




        lowercase_			:List[Any]    			= (
            "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
            " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
        )
        lowercase_			:Optional[int]    			= [
            108,
            265,
            24,
            111,
            4,
            258,
            156,
            35,
            28,
            275,
            3,
            259,
            297,
            260,
            84,
            4,
            35,
            110,
            44,
            8,
            259,
            91,
            268,
            21,
            11,
            209,
            274,
            109,
            266,
            277,
            117,
            86,
            93,
            315,
            258,
            278,
            258,
            277,
            258,
            0,
            258,
            288,
            258,
            319,
            258,
            0,
            258,
            0,
            258,
            0,
            258,
            0,
            258,
            287,
            258,
            315,
            258,
            289,
            258,
            278,
            99,
            269,
            266,
            262,
            8,
            259,
            241,
            4,
            217,
            230,
            268,
            266,
            55,
            168,
            106,
            75,
            193,
            266,
            223,
            27,
            49,
            26,
            282,
            25,
            264,
            299,
            19,
            26,
            0,
            258,
            277,
            117,
            86,
            93,
            176,
            183,
            270,
            11,
            262,
            42,
            61,
            265,
        ]

        self.assertListEqual(SCREAMING_SNAKE_CASE__	,      self.big_tokenizer.encode(SCREAMING_SNAKE_CASE__						)						)





     @require_torch
     @slow
     def 							lowercase__      ( self		:					Dict						):





        """simple docstring"""




        import torch

        from transformers import ReformerConfig, ReformerModel

        # Build sequence
        lowercase_			:Optional[int]    			= list(self.big_tokenizer.get_vocab().keys()						)[:10]
        lowercase_			:Any    			= " ".join(SCREAMING_SNAKE_CASE__						)
        lowercase_			:Any    			= self.big_tokenizer.encode_plus(SCREAMING_SNAKE_CASE__	,      return_tensors="pt"						)
        lowercase_			:List[str]    			= self.big_tokenizer.batch_encode_plus([sequence, sequence]	,      return_tensors="pt"						)

        lowercase_			:List[Any]    			= ReformerConfig()
        # The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
        lowercase_			:Dict    			= encoded_sequence["input_ids"].shape
        lowercase_			:Optional[int]    			= ReformerModel(SCREAMING_SNAKE_CASE__						)

        # Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
        assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

        with torch.no_grad():
           model(**SCREAMING_SNAKE_CASE__						)
           model(**SCREAMING_SNAKE_CASE__						)







     @slow
     def 							lowercase__      ( self		:					int						):





        """simple docstring"""




        lowercase_			:Tuple    			= {"input_ids": [[108, 265, 24, 111, 4, 258, 156, 7, 51, 279, 58, 7, 76, 25, 69, 278], [140, 243, 264, 134, 17, 267, 77, 263, 22, 262, 297, 258, 304, 177, 279, 266, 14, 89, 13, 35, 261, 299, 272, 137, 275, 278]], "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]]}  # noqa: E501
        # fmt: on

        # This tokenizer does not know some characters like ")".
        # That is the reason why we use very simple texts here.
        # Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
        lowercase_			:List[Any]    			= [
            "This is a very simple sentence.",
            "The quick brown fox jumps over the lazy dog.",
        ]

        self.tokenizer_integration_test_util(
            expected_encoding=SCREAMING_SNAKE_CASE__	,      model_name="google/reformer-crime-and-punishment"	,      revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"	,      padding=SCREAMING_SNAKE_CASE__	,      sequences=SCREAMING_SNAKE_CASE__	,      )




import copy
from typing import Dict, List, Optional

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


SCREAMING_SNAKE_CASE__   :			Dict												=    {
    "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
}

SCREAMING_SNAKE_CASE__   :			int												=    logging.get_logger(__name__)

class    lowerCAmelCase__     (	__lowercase			):
		a__       :						Any        =		"""mask2former"""
		a__       :						Dict        =		["""swin"""]
		a__       :						Any        =		{"""hidden_size""": """hidden_dim"""}






		def __init__(		self		:							Any							,			SCREAMING_SNAKE_CASE__		:							Optional[Dict] = None							,			SCREAMING_SNAKE_CASE__		:							int = 2_56							,			SCREAMING_SNAKE_CASE__		:							int = 2_56							,			SCREAMING_SNAKE_CASE__		:							int = 2_56							,			SCREAMING_SNAKE_CASE__		:							int = 10_24							,			SCREAMING_SNAKE_CASE__		:							str = "relu"							,			SCREAMING_SNAKE_CASE__		:							int = 6							,			SCREAMING_SNAKE_CASE__		:							int = 10							,			SCREAMING_SNAKE_CASE__		:							int = 8							,			SCREAMING_SNAKE_CASE__		:							float = 0.0							,			SCREAMING_SNAKE_CASE__		:							int = 20_48							,			SCREAMING_SNAKE_CASE__		:							bool = False							,			SCREAMING_SNAKE_CASE__		:							bool = False							,			SCREAMING_SNAKE_CASE__		:							int = 4							,			SCREAMING_SNAKE_CASE__		:							int = 2_55							,			SCREAMING_SNAKE_CASE__		:							int = 1_00							,			SCREAMING_SNAKE_CASE__		:							float = 0.1							,			SCREAMING_SNAKE_CASE__		:							float = 2.0							,			SCREAMING_SNAKE_CASE__		:							float = 5.0							,			SCREAMING_SNAKE_CASE__		:							float = 5.0							,			SCREAMING_SNAKE_CASE__		:							int = 1_25_44							,			SCREAMING_SNAKE_CASE__		:							float = 3.0							,			SCREAMING_SNAKE_CASE__		:							float = 0.75							,			SCREAMING_SNAKE_CASE__		:							float = 0.02							,			SCREAMING_SNAKE_CASE__		:							float = 1.0							,			SCREAMING_SNAKE_CASE__		:							bool = True							,			SCREAMING_SNAKE_CASE__		:							List[int] = [4, 8, 16, 32]							,			SCREAMING_SNAKE_CASE__		:							bool = None							,			**SCREAMING_SNAKE_CASE__		:							Tuple							,			)     ->							str:
						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=SCREAMING_SNAKE_CASE__							,			out_features=['''stage1''', '''stage2''', '''stage3''', '''stage4''']							,			)

						if isinstance(SCREAMING_SNAKE_CASE__							,			SCREAMING_SNAKE_CASE__  ):
										__lowerCamelCase    					=	backbone_config.pop('''model_type'''  )
										__lowerCamelCase    					=	CONFIG_MAPPING[backbone_model_type]
										__lowerCamelCase    					=	config_class.from_dict(SCREAMING_SNAKE_CASE__  )

						# 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__(**SCREAMING_SNAKE_CASE__  )






		@classmethod
		def  __A       (		cls		:							Any							,			SCREAMING_SNAKE_CASE__		:							PretrainedConfig							,			**SCREAMING_SNAKE_CASE__		:							Optional[Any]  )     ->							List[Any]:
						return cls(
						    backbone_config=SCREAMING_SNAKE_CASE__							,			**SCREAMING_SNAKE_CASE__							,			)







		def  __A       (		self		:							Any  )     ->							Dict[str, any]:
						__lowerCamelCase    					=	copy.deepcopy(self.__dict__  )
						__lowerCamelCase    					=	self.backbone_config.to_dict()
						__lowerCamelCase    					=	self.__class__.model_type
						return output



