
"""simple docstring"""







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


lowerCamelCase__        =		logging.get_logger(__name__)

lowerCamelCase__        =		{
    """edbeeching/decision-transformer-gym-hopper-medium""": (
        """https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json"""
    ),
    # See all DecisionTransformer models at https://huggingface.co/models?filter=decision_transformer
}




class 			A__	(     _lowerCamelCase):
		A_						:	str           =     'decision_transformer'
		A_						:	Optional[Any]           =     ['past_key_values']
		A_						:	Any           =     {
		    'max_position_embeddings': 'n_positions',
		    'num_attention_heads': 'n_head',
		    'num_hidden_layers': 'n_layer',
		}

		def __init__(				self	,		_SCREAMING_SNAKE_CASE=17	,		_SCREAMING_SNAKE_CASE=4	,		_SCREAMING_SNAKE_CASE=1_28	,		_SCREAMING_SNAKE_CASE=40_96	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=1	,		_SCREAMING_SNAKE_CASE=10_24	,		_SCREAMING_SNAKE_CASE=3	,		_SCREAMING_SNAKE_CASE=1	,		_SCREAMING_SNAKE_CASE=None	,		_SCREAMING_SNAKE_CASE="relu"	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE=0.1	,		_SCREAMING_SNAKE_CASE=1E-5	,		_SCREAMING_SNAKE_CASE=0.02	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=True	,		_SCREAMING_SNAKE_CASE=5_02_56	,		_SCREAMING_SNAKE_CASE=5_02_56	,		_SCREAMING_SNAKE_CASE=False	,		_SCREAMING_SNAKE_CASE=False	,		**_SCREAMING_SNAKE_CASE	,		):
			__lowerCAmelCase      :						Tuple						      =				state_dim
			__lowerCAmelCase      :						Optional[Any]						      =				act_dim
			__lowerCAmelCase      :						str						      =				hidden_size
			__lowerCAmelCase      :						str						      =				max_ep_len
			__lowerCAmelCase      :						Optional[int]						      =				action_tanh
			__lowerCAmelCase      :						List[str]						      =				vocab_size
			__lowerCAmelCase      :						List[Any]						      =				n_positions
			__lowerCAmelCase      :						Optional[int]						      =				n_layer
			__lowerCAmelCase      :						Optional[Any]						      =				n_head
			__lowerCAmelCase      :						Tuple						      =				n_inner
			__lowerCAmelCase      :						int						      =				activation_function
			__lowerCAmelCase      :						List[Any]						      =				resid_pdrop
			__lowerCAmelCase      :						List[Any]						      =				embd_pdrop
			__lowerCAmelCase      :						Dict						      =				attn_pdrop
			__lowerCAmelCase      :						Tuple						      =				layer_norm_epsilon
			__lowerCAmelCase      :						Optional[int]						      =				initializer_range
			__lowerCAmelCase      :						Union[str, Any]						      =				scale_attn_weights
			__lowerCAmelCase      :						Union[str, Any]						      =				use_cache
			__lowerCAmelCase      :						int						      =				scale_attn_by_inverse_layer_idx
			__lowerCAmelCase      :						str						      =				reorder_and_upcast_attn

			__lowerCAmelCase      :						Union[str, Any]						      =				bos_token_id
			__lowerCAmelCase      :						Dict						      =				eos_token_id

			super().__init__(bos_token_id=_SCREAMING_SNAKE_CASE	,		eos_token_id=_SCREAMING_SNAKE_CASE	,		**_SCREAMING_SNAKE_CASE			)

"""simple docstring"""







lowerCamelCase__        =		"""0.21.0"""

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
							from .utils import rich