DecisionTransformer¶
- class torchrl.modules.DecisionTransformer(state_dim, action_dim, config: dict | DTConfig = None)[source]¶
Online Decion Transformer.
Desdescribed in https://arxiv.org/abs/2202.05607 .
The transformer utilizes a default config to create the GPT2 model if the user does not provide a specific config. default_config = { … “n_embd”: 256, … “n_layer”: 4, … “n_head”: 4, … “n_inner”: 1024, … “activation”: “relu”, … “n_positions”: 1024, … “resid_pdrop”: 0.1, … “attn_pdrop”: 0.1, }
- Parameters:
state_dim (int) – dimension of the state space
action_dim (int) – dimension of the action space
config (
DTConfig
or dict, optional) – transformer architecture configuration, used to create the GPT2Config from transformers. Defaults todefault_config
.
Example
>>> config = DecisionTransformer.default_config() >>> config.n_embd = 128 >>> print(config) DTConfig(n_embd: 128, n_layer: 4, n_head: 4, n_inner: 1024, activation: relu, n_positions: 1024, resid_pdrop: 0.1, attn_pdrop: 0.1) >>> # alternatively >>> config = DecisionTransformer.DTConfig(n_embd=128) >>> model = DecisionTransformer(state_dim=4, action_dim=2, config=config) >>> batch_size = [3, 32] >>> length = 10 >>> observation = torch.randn(*batch_size, length, 4) >>> action = torch.randn(*batch_size, length, 2) >>> return_to_go = torch.randn(*batch_size, length, 1) >>> output = model(observation, action, return_to_go) >>> output.shape torch.Size([3, 32, 10, 128])
- class DTConfig(n_embd: Any = 256, n_layer: Any = 4, n_head: Any = 4, n_inner: Any = 1024, activation: Any = 'relu', n_positions: Any = 1024, resid_pdrop: Any = 0.1, attn_pdrop: Any = 0.1)[source]¶
Default configuration for DecisionTransformer.
- forward(observation: Tensor, action: Tensor, return_to_go: Tensor)[source]¶
Define the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.