


import copy

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


lowerCAmelCase__						:int         =							logging.get_logger(__name__)

lowerCAmelCase__						:Optional[int]         =							{
    '''facebook/sam-vit-huge''': '''https://huggingface.co/facebook/sam-vit-huge/resolve/main/config.json''',
    '''facebook/sam-vit-large''': '''https://huggingface.co/facebook/sam-vit-large/resolve/main/config.json''',
    '''facebook/sam-vit-base''': '''https://huggingface.co/facebook/sam-vit-base/resolve/main/config.json''',
}

class 	__a   (       UpperCAmelCase    ):
		def __init__(    self    ,					_SCREAMING_SNAKE_CASE=256    ,					_SCREAMING_SNAKE_CASE=1024    ,					_SCREAMING_SNAKE_CASE=16    ,					_SCREAMING_SNAKE_CASE=16    ,					_SCREAMING_SNAKE_CASE=4    ,					_SCREAMING_SNAKE_CASE="gelu"    ,					_SCREAMING_SNAKE_CASE=1e-6    ,					**_SCREAMING_SNAKE_CASE    ,					)				-> Tuple:




									"""simple docstring"""





									super().__init__(**_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase					=    hidden_size
									_UpperCAmelCase					=    image_size
									_UpperCAmelCase					=    patch_size
									_UpperCAmelCase					=    image_size // patch_size
									_UpperCAmelCase					=    mask_input_channels
									_UpperCAmelCase					=    num_point_embeddings
									_UpperCAmelCase					=    hidden_act
									_UpperCAmelCase					=    layer_norm_eps



class 	__a   (       UpperCAmelCase    ):
		def __init__(    self    ,					_SCREAMING_SNAKE_CASE=256    ,					_SCREAMING_SNAKE_CASE="relu"    ,					_SCREAMING_SNAKE_CASE=2048    ,					_SCREAMING_SNAKE_CASE=2    ,					_SCREAMING_SNAKE_CASE=8    ,					_SCREAMING_SNAKE_CASE=2    ,					_SCREAMING_SNAKE_CASE=3    ,					_SCREAMING_SNAKE_CASE=3    ,					_SCREAMING_SNAKE_CASE=256    ,					_SCREAMING_SNAKE_CASE=1e-6    ,					**_SCREAMING_SNAKE_CASE    ,					)				-> List[Any]:




									"""simple docstring"""





									super().__init__(**_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase					=    hidden_size
									_UpperCAmelCase					=    hidden_act
									_UpperCAmelCase					=    mlp_dim
									_UpperCAmelCase					=    num_hidden_layers
									_UpperCAmelCase					=    num_attention_heads
									_UpperCAmelCase					=    attention_downsample_rate
									_UpperCAmelCase					=    num_multimask_outputs
									_UpperCAmelCase					=    iou_head_depth
									_UpperCAmelCase					=    iou_head_hidden_dim
									_UpperCAmelCase					=    layer_norm_eps



class 	__a   (       UpperCAmelCase    ):
		def __init__(    self    ,					_SCREAMING_SNAKE_CASE=768    ,					_SCREAMING_SNAKE_CASE=256    ,					_SCREAMING_SNAKE_CASE=12    ,					_SCREAMING_SNAKE_CASE=12    ,					_SCREAMING_SNAKE_CASE=3    ,					_SCREAMING_SNAKE_CASE=1024    ,					_SCREAMING_SNAKE_CASE=16    ,					_SCREAMING_SNAKE_CASE="gelu"    ,					_SCREAMING_SNAKE_CASE=1e-0_6    ,					_SCREAMING_SNAKE_CASE=0.0    ,					_SCREAMING_SNAKE_CASE=1e-1_0    ,					_SCREAMING_SNAKE_CASE=True    ,					_SCREAMING_SNAKE_CASE=4.0    ,					_SCREAMING_SNAKE_CASE=True    ,					_SCREAMING_SNAKE_CASE=True    ,					_SCREAMING_SNAKE_CASE=14    ,					_SCREAMING_SNAKE_CASE=[2, 5, 8, 11]    ,					_SCREAMING_SNAKE_CASE=128    ,					_SCREAMING_SNAKE_CASE=None    ,					**_SCREAMING_SNAKE_CASE    ,					)				-> List[str]:




									"""simple docstring"""





									super().__init__(**_SCREAMING_SNAKE_CASE		)

									_UpperCAmelCase					=    hidden_size
									_UpperCAmelCase					=    output_channels
									_UpperCAmelCase					=    num_hidden_layers
									_UpperCAmelCase					=    num_attention_heads
									_UpperCAmelCase					=    num_channels
									_UpperCAmelCase					=    image_size
									_UpperCAmelCase					=    patch_size
									_UpperCAmelCase					=    hidden_act
									_UpperCAmelCase					=    layer_norm_eps
									_UpperCAmelCase					=    attention_dropout
									_UpperCAmelCase					=    initializer_range
									_UpperCAmelCase					=    qkv_bias
									_UpperCAmelCase					=    mlp_ratio
									_UpperCAmelCase					=    use_abs_pos
									_UpperCAmelCase					=    use_rel_pos
									_UpperCAmelCase					=    window_size
									_UpperCAmelCase					=    global_attn_indexes
									_UpperCAmelCase					=    num_pos_feats
									_UpperCAmelCase					=    int(hidden_size * mlp_ratio		) if mlp_dim is None else mlp_dim



class 	__a   (       UpperCAmelCase    ):
		_a			:						Any    			=			'sam'
		_a			:						Any    			=			True
		def __init__(    self    ,					_SCREAMING_SNAKE_CASE=None    ,					_SCREAMING_SNAKE_CASE=None    ,					_SCREAMING_SNAKE_CASE=None    ,					_SCREAMING_SNAKE_CASE=0.02    ,					**_SCREAMING_SNAKE_CASE    ,					)				-> Tuple:




									"""simple docstring"""





									super().__init__(**_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase					=    vision_config if vision_config is not None else {}
									_UpperCAmelCase					=    prompt_encoder_config if prompt_encoder_config is not None else {}
									_UpperCAmelCase					=    mask_decoder_config if mask_decoder_config is not None else {}

									if isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																_UpperCAmelCase					=    vision_config.to_dict()
									if isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																_UpperCAmelCase					=    prompt_encoder_config.to_dict()
									if isinstance(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE		):
																_UpperCAmelCase					=    mask_decoder_config.to_dict()

									_UpperCAmelCase					=    SamVisionConfig(**_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase					=    SamPromptEncoderConfig(**_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase					=    SamMaskDecoderConfig(**_SCREAMING_SNAKE_CASE		)
									_UpperCAmelCase					=    initializer_range






		def 			UpperCAmelCase__       (    self		)				-> str:




									"""simple docstring"""





									_UpperCAmelCase					=    copy.deepcopy(self.__dict__		)
									_UpperCAmelCase					=    self.vision_config.to_dict()
									_UpperCAmelCase					=    self.prompt_encoder_config.to_dict()
									_UpperCAmelCase					=    self.mask_decoder_config.to_dict()
									_UpperCAmelCase					=    self.__class__.model_type
									return output




import os
from shutil import copyfile
from typing import Optional, Tuple

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
		from .tokenization_deberta_va import DebertaVaTokenizer
else:
		lowerCAmelCase__						:int         =							None

lowerCAmelCase__						:List[str]         =							logging.get_logger(__name__)

lowerCAmelCase__						:List[str]         =							{'''vocab_file''': '''spm.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase__						:List[str]         =							{
    '''vocab_file''': {
        '''microsoft/deberta-v2-xlarge''': '''https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xxlarge''': '''https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'''
        ),
        '''microsoft/deberta-v2-xxlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'''
        ),
    }
}

lowerCAmelCase__						:List[str]         =							{
    '''microsoft/deberta-v2-xlarge''': 5_1_2,
    '''microsoft/deberta-v2-xxlarge''': 5_1_2,
    '''microsoft/deberta-v2-xlarge-mnli''': 5_1_2,
    '''microsoft/deberta-v2-xxlarge-mnli''': 5_1_2,
}

lowerCAmelCase__						:Any         =							{
    '''microsoft/deberta-v2-xlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xlarge-mnli''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge-mnli''': {'''do_lower_case''': False},
}

class 	__a   (       UpperCAmelCase    ):
		_a			:						Tuple    			=			VOCAB_FILES_NAMES
		_a			:						int    			=			PRETRAINED_VOCAB_FILES_MAP
		_a			:						Optional[Any]    			=			PRETRAINED_INIT_CONFIGURATION
		_a			:						str    			=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_a			:						Optional[int]    			=			DebertaVaTokenizer
		def __init__(    self    ,					_SCREAMING_SNAKE_CASE=None    ,					_SCREAMING_SNAKE_CASE=None    ,					_SCREAMING_SNAKE_CASE=False    ,					_SCREAMING_SNAKE_CASE=False    ,					_SCREAMING_SNAKE_CASE="[CLS]"    ,					_SCREAMING_SNAKE_CASE="[SEP]"    ,					_SCREAMING_SNAKE_CASE="[UNK]"    ,					_SCREAMING_SNAKE_CASE="[SEP]"    ,					_SCREAMING_SNAKE_CASE="[PAD]"    ,					_SCREAMING_SNAKE_CASE="[CLS]"    ,					_SCREAMING_SNAKE_CASE="[MASK]"    ,					**_SCREAMING_SNAKE_CASE    ,					)				-> None:




									"""simple docstring"""





									super().__init__(
									    _SCREAMING_SNAKE_CASE    ,					tokenizer_file=_SCREAMING_SNAKE_CASE    ,					do_lower_case=_SCREAMING_SNAKE_CASE    ,					bos_token=_SCREAMING_SNAKE_CASE    ,					eos_token=_SCREAMING_SNAKE_CASE    ,					unk_token=_SCREAMING_SNAKE_CASE    ,					sep_token=_SCREAMING_SNAKE_CASE    ,					pad_token=_SCREAMING_SNAKE_CASE    ,					cls_token=_SCREAMING_SNAKE_CASE    ,					mask_token=_SCREAMING_SNAKE_CASE    ,					split_by_punct=_SCREAMING_SNAKE_CASE    ,					**_SCREAMING_SNAKE_CASE    ,					)

									_UpperCAmelCase					=    do_lower_case
									_UpperCAmelCase					=    split_by_punct
									_UpperCAmelCase					=    vocab_file
									_UpperCAmelCase					=    False if not self.vocab_file else True
		def 			UpperCAmelCase__       (    self    ,					_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE=None		)				-> str:




									"""simple docstring"""





									if token_ids_a is None:
																return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
									_UpperCAmelCase					=    [self.cls_token_id]
									_UpperCAmelCase					=    [self.sep_token_id]
									return cls + token_ids_a + sep + token_ids_a + sep
		def 			UpperCAmelCase__       (    self    ,					_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE=None    ,					_SCREAMING_SNAKE_CASE=False		)				-> Any:




									"""simple docstring"""





									if already_has_special_tokens:
																return super().get_special_tokens_mask(
																    token_ids_a=_SCREAMING_SNAKE_CASE    ,					token_ids_a=_SCREAMING_SNAKE_CASE    ,					already_has_special_tokens=_SCREAMING_SNAKE_CASE		)

									if token_ids_a is not None:
																return [1] + ([0] * len(_SCREAMING_SNAKE_CASE		)) + [1] + ([0] * len(_SCREAMING_SNAKE_CASE		)) + [1]
									return [1] + ([0] * len(_SCREAMING_SNAKE_CASE		)) + [1]
		def 			UpperCAmelCase__       (    self    ,					_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE=None		)				-> Union[str, Any]:




									"""simple docstring"""





									_UpperCAmelCase					=    [self.sep_token_id]
									_UpperCAmelCase					=    [self.cls_token_id]
									if token_ids_a is None:
																return len(cls + token_ids_a + sep		) * [0]
									return len(cls + token_ids_a + sep		) * [0] + len(token_ids_a + sep		) * [1]






		def 			UpperCAmelCase__       (    self    ,					_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE = None		)				-> Tuple[str]:




									"""simple docstring"""





									if not self.can_save_slow_tokenizer:
																raise ValueError(
																    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
																    'tokenizer.'		)

									if not os.path.isdir(_SCREAMING_SNAKE_CASE		):
																logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''		)
																return
									_UpperCAmelCase					=    os.path.join(
									    _SCREAMING_SNAKE_CASE    ,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']		)

									if os.path.abspath(self.vocab_file		) != os.path.abspath(_SCREAMING_SNAKE_CASE		):
																copyfile(self.vocab_file    ,					_SCREAMING_SNAKE_CASE		)

									return (out_vocab_file,)
