

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


SCREAMING_SNAKE_CASE		:str						=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:Tuple						=     {
    """vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:Dict										=      """glpn"""






     def __init__(				self		,						_lowercase=3		,						_lowercase=4		,						_lowercase=[2, 2, 2, 2]		,						_lowercase=[8, 4, 2, 1]		,						_lowercase=[32, 64, 160, 256]		,						_lowercase=[7, 3, 3, 3]		,						_lowercase=[4, 2, 2, 2]		,						_lowercase=[1, 2, 5, 8]		,						_lowercase=[4, 4, 4, 4]		,						_lowercase="gelu"		,						_lowercase=0.0		,						_lowercase=0.0		,						_lowercase=0.02		,						_lowercase=0.1		,						_lowercase=1e-6		,						_lowercase=64		,						_lowercase=10		,						_lowercase=-1		,						**_lowercase		,						)->     str:
         super().__init__(**_lowercase	)

         UpperCamelCase_			  =						num_channels
         UpperCamelCase_			  =						num_encoder_blocks
         UpperCamelCase_			  =						depths
         UpperCamelCase_			  =						sr_ratios
         UpperCamelCase_			  =						hidden_sizes
         UpperCamelCase_			  =						patch_sizes
         UpperCamelCase_			  =						strides
         UpperCamelCase_			  =						mlp_ratios
         UpperCamelCase_			  =						num_attention_heads
         UpperCamelCase_			  =						hidden_act
         UpperCamelCase_			  =						hidden_dropout_prob
         UpperCamelCase_			  =						attention_probs_dropout_prob
         UpperCamelCase_			  =						initializer_range
         UpperCamelCase_			  =						drop_path_rate
         UpperCamelCase_			  =						layer_norm_eps
         UpperCamelCase_			  =						decoder_hidden_size
         UpperCamelCase_			  =						max_depth
         UpperCamelCase_			  =						head_in_index



from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:Dict										=      ["""image_processor""", """tokenizer"""]
     UpperCamelCase_	:str										=      """BridgeTowerImageProcessor"""
     UpperCamelCase_	:Tuple										=      ("""RobertaTokenizer""", """RobertaTokenizerFast""")






     def __init__(				self		,						_lowercase		,						_lowercase	)->     Any:
         super().__init__(_lowercase		,						_lowercase	)






     def __call__(				self		,						_lowercase		,						_lowercase = None		,						_lowercase = True		,						_lowercase = False		,						_lowercase = None		,						_lowercase = None		,						_lowercase = 0		,						_lowercase = None		,						_lowercase = None		,						_lowercase = None		,						_lowercase = False		,						_lowercase = False		,						_lowercase = False		,						_lowercase = False		,						_lowercase = True		,						_lowercase = None		,						**_lowercase		,						)->     BatchEncoding:
         UpperCamelCase_			  =						self.tokenizer(
             text=_lowercase		,						add_special_tokens=_lowercase		,						padding=_lowercase		,						truncation=_lowercase		,						max_length=_lowercase		,						stride=_lowercase		,						pad_to_multiple_of=_lowercase		,						return_token_type_ids=_lowercase		,						return_attention_mask=_lowercase		,						return_overflowing_tokens=_lowercase		,						return_special_tokens_mask=_lowercase		,						return_offsets_mapping=_lowercase		,						return_length=_lowercase		,						verbose=_lowercase		,						return_tensors=_lowercase		,						**_lowercase		,						)
         # add pixel_values + pixel_mask
         UpperCamelCase_			  =						self.image_processor(
             _lowercase		,						return_tensors=_lowercase		,						do_normalize=_lowercase		,						do_center_crop=_lowercase		,						**_lowercase	)
         encoding.update(_lowercase	)

         return encoding






     def 	UpperCAmelCase_				(				self		,						*_lowercase		,						**_lowercase	)->     Union[str, Any]:
         return self.tokenizer.batch_decode(*_lowercase		,						**_lowercase	)






     def 	UpperCAmelCase_				(				self		,						*_lowercase		,						**_lowercase	)->     List[Any]:
         return self.tokenizer.decode(*_lowercase		,						**_lowercase	)






     @property
     def 	UpperCAmelCase_				(				self	)->     Any:
         UpperCamelCase_			  =						self.tokenizer.model_input_names
         UpperCamelCase_			  =						self.image_processor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names	)	)
