DQLMlp

CLASS cleandiffuser.nn_diffusion.DQLMlp(obs_dim: int, act_dim: int, emb_dim: int = 16, timestep_emb_type: str = “positional”, timestep_emb_params: Optional[dict] = None) [SOURCE]

A simple MLP neural network backbone for diffusion model, proposed in Diffusion Q-Learning (DQL). It takes the current observation as the context tensor and generates the action to execute.

Parameters:

• obs_dim (int): The dimension of the observation tensor \(\bm o_t\).
• act_dim (int): The dimension of the action tensor \(\bm x_t\).
• emb_dim (int): The dimension of the time embedding. Default is 16.
• timestep_emb_type (str): The type of the time embedding. It can be either “positional” or “fourier”. Default is “positional”.
• timestep_emb_params (Optional[dict]): The parameters for the time embedding. Default is None.

forward(x: torch.Tensor, t: torch.Tensor, c: torch.Tensor) -> torch.Tensor

Parameters:

• x (torch.Tensor): The input tensor \(\bm x_t\) in shape (..., act_dim)
• t (torch.Tensor): The time tensor \(t\) in shape (..., 1).
• c (torch.Tensor): The context tensor \(\bm c\) in shape (..., obs_dim).

Returns:

• torch.Tensor: The output tensor in shape (..., act_dim).