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


SCREAMING_SNAKE_CASE :	Optional[int]							     =		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE :	Any							     =		{
    """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    A_ (       a_ ):
		_SCREAMING_SNAKE_CASE    				=			"""trajectory_transformer"""
		_SCREAMING_SNAKE_CASE    				=			["""past_key_values"""]
		_SCREAMING_SNAKE_CASE    				=			{
		    """hidden_size""": """n_embd""",
		    """num_attention_heads""": """n_head""",
		    """num_hidden_layers""": """n_layer""",
		}

		def __init__(		self :      List[str]     ,							__SCREAMING_SNAKE_CASE :      Optional[int]=1_00     ,							__SCREAMING_SNAKE_CASE :      List[Any]=5     ,							__SCREAMING_SNAKE_CASE :      Any=1     ,							__SCREAMING_SNAKE_CASE :      Any=1     ,							__SCREAMING_SNAKE_CASE :      Tuple=2_49     ,							__SCREAMING_SNAKE_CASE :      Tuple=6     ,							__SCREAMING_SNAKE_CASE :      str=17     ,							__SCREAMING_SNAKE_CASE :      Any=25     ,							__SCREAMING_SNAKE_CASE :      List[str]=4     ,							__SCREAMING_SNAKE_CASE :      Dict=4     ,							__SCREAMING_SNAKE_CASE :      Any=1_28     ,							__SCREAMING_SNAKE_CASE :      List[str]=0.1     ,							__SCREAMING_SNAKE_CASE :      Optional[Any]=0.1     ,							__SCREAMING_SNAKE_CASE :      int=0.1     ,							__SCREAMING_SNAKE_CASE :      Any=0.00_06     ,							__SCREAMING_SNAKE_CASE :      List[str]=5_12     ,							__SCREAMING_SNAKE_CASE :      Dict=0.02     ,							__SCREAMING_SNAKE_CASE :      Union[str, Any]=1E-12     ,							__SCREAMING_SNAKE_CASE :      Any=1     ,							__SCREAMING_SNAKE_CASE :      str=True     ,							__SCREAMING_SNAKE_CASE :      Union[str, Any]=1     ,							__SCREAMING_SNAKE_CASE :      Tuple=5_02_56     ,							__SCREAMING_SNAKE_CASE :      str=5_02_56     ,							**__SCREAMING_SNAKE_CASE :      List[Any]     ,							):
			__a       =  vocab_size
			__a       =  action_weight
			__a       =  reward_weight
			__a       =  value_weight
			__a       =  max_position_embeddings
			__a       =  block_size
			__a       =  action_dim
			__a       =  observation_dim
			__a       =  transition_dim
			__a       =  learning_rate
			__a       =  n_layer
			__a       =  n_head
			__a       =  n_embd
			__a       =  embd_pdrop
			__a       =  attn_pdrop
			__a       =  resid_pdrop
			__a       =  initializer_range
			__a       =  layer_norm_eps
			__a       =  kaiming_initializer_range
			__a       =  use_cache
			super().__init__(pad_token_id=__UpperCamelCase     ,							bos_token_id=__UpperCamelCase     ,							eos_token_id=__UpperCamelCase     ,							**__UpperCamelCase       )



from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
  if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import UnCLIPImageVariationPipeline, UnCLIPPipeline
else:
  from .pipeline_unclip import UnCLIPPipeline
  from .pipeline_unclip_image_variation import UnCLIPImageVariationPipeline
  from .text_proj import UnCLIPTextProjModel


