
"""simple docstring"""

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 	_lowercase       (    __UpperCAmelCase		):
	lowercase_				=     ['image_processor', 'tokenizer']
	lowercase_				=     'BridgeTowerImageProcessor'
	lowercase_				=     ('RobertaTokenizer', 'RobertaTokenizerFast')




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




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

			return encoding




	def       _UpperCamelCase   (			self		,			*UpperCAmelCase_		,			**UpperCAmelCase_ )		->							Optional[int]:
			return self.tokenizer.batch_decode(*UpperCAmelCase_		,			**UpperCAmelCase_ )




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




	@property
	def       _UpperCamelCase   (			self )		->							Any:
			lowerCamelCase					:      Tuple          =   self.tokenizer.model_input_names
			lowerCamelCase					:      Optional[Any]          =   self.image_processor.model_input_names
			return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names ) )








"""simple docstring"""

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


_A						=			logging.get_logger(__name__)

_A						=			{
    'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
        'https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json'
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}






class 	_lowercase       (    __UpperCAmelCase		):
	lowercase_				=     'trajectory_transformer'
	lowercase_				=     ['past_key_values']
	lowercase_				=     {
	    'hidden_size': 'n_embd',
	    'num_attention_heads': 'n_head',
	    'num_hidden_layers': 'n_layer',
	}




	def __init__(			self		,			UpperCAmelCase_=100		,			UpperCAmelCase_=5		,			UpperCAmelCase_=1		,			UpperCAmelCase_=1		,			UpperCAmelCase_=249		,			UpperCAmelCase_=6		,			UpperCAmelCase_=17		,			UpperCAmelCase_=25		,			UpperCAmelCase_=4		,			UpperCAmelCase_=4		,			UpperCAmelCase_=128		,			UpperCAmelCase_=0.1		,			UpperCAmelCase_=0.1		,			UpperCAmelCase_=0.1		,			UpperCAmelCase_=0.0006		,			UpperCAmelCase_=512		,			UpperCAmelCase_=0.02		,			UpperCAmelCase_=1E-1_2		,			UpperCAmelCase_=1		,			UpperCAmelCase_=True		,			UpperCAmelCase_=1		,			UpperCAmelCase_=50256		,			UpperCAmelCase_=50256		,			**UpperCAmelCase_		,			)		->							List[Any]:
			lowerCamelCase					:      int          =   vocab_size
			lowerCamelCase					:      List[str]          =   action_weight
			lowerCamelCase					:      List[Any]          =   reward_weight
			lowerCamelCase					:      List[str]          =   value_weight
			lowerCamelCase					:      Tuple          =   max_position_embeddings
			lowerCamelCase					:      List[str]          =   block_size
			lowerCamelCase					:      Any          =   action_dim
			lowerCamelCase					:      List[Any]          =   observation_dim
			lowerCamelCase					:      Any          =   transition_dim
			lowerCamelCase					:      int          =   learning_rate
			lowerCamelCase					:      Union[str, Any]          =   n_layer
			lowerCamelCase					:      Tuple          =   n_head
			lowerCamelCase					:      Any          =   n_embd
			lowerCamelCase					:      Union[str, Any]          =   embd_pdrop
			lowerCamelCase					:      Optional[int]          =   attn_pdrop
			lowerCamelCase					:      int          =   resid_pdrop
			lowerCamelCase					:      Optional[int]          =   initializer_range
			lowerCamelCase					:      List[str]          =   layer_norm_eps
			lowerCamelCase					:      Any          =   kaiming_initializer_range
			lowerCamelCase					:      str          =   use_cache
			super().__init__(pad_token_id=UpperCAmelCase_		,			bos_token_id=UpperCAmelCase_		,			eos_token_id=UpperCAmelCase_		,			**UpperCAmelCase_ )






