pub trait Mamba2BackendExt: Backend {
// Provided method
fn ssd_serial_recalculated(
x_bnlhp: FloatTensor<Self>,
dt_discretized_bhnl: FloatTensor<Self>,
b_bnlgr: FloatTensor<Self>,
c_bnlgr: FloatTensor<Self>,
d_h: FloatTensor<Self>,
initial_state_bhpr: FloatTensor<Self>,
a_decay_h: FloatTensor<Self>,
) -> (FloatTensor<Self>, FloatTensor<Self>) { ... }
}Expand description
Extends the backend and wraps it for burn.
Provided Methods§
Sourcefn ssd_serial_recalculated(
x_bnlhp: FloatTensor<Self>,
dt_discretized_bhnl: FloatTensor<Self>,
b_bnlgr: FloatTensor<Self>,
c_bnlgr: FloatTensor<Self>,
d_h: FloatTensor<Self>,
initial_state_bhpr: FloatTensor<Self>,
a_decay_h: FloatTensor<Self>,
) -> (FloatTensor<Self>, FloatTensor<Self>)
fn ssd_serial_recalculated( x_bnlhp: FloatTensor<Self>, dt_discretized_bhnl: FloatTensor<Self>, b_bnlgr: FloatTensor<Self>, c_bnlgr: FloatTensor<Self>, d_h: FloatTensor<Self>, initial_state_bhpr: FloatTensor<Self>, a_decay_h: FloatTensor<Self>, ) -> (FloatTensor<Self>, FloatTensor<Self>)
Returns:
y_bnlhp.final_state_bhpr.
Dyn Compatibility§
This trait is not dyn compatible.
In older versions of Rust, dyn compatibility was called "object safety", so this trait is not object safe.
Implementations on Foreign Types§
Source§impl<B: Backend + Mamba2BackendExt, C: CheckpointStrategy> Mamba2BackendExt for Autodiff<B, C>
impl<B: Backend + Mamba2BackendExt, C: CheckpointStrategy> Mamba2BackendExt for Autodiff<B, C>
Source§fn ssd_serial_recalculated(
x_bnlhp: FloatTensor<Self>,
dt_discretized_bhnl: FloatTensor<Self>,
b_bnlgr: FloatTensor<Self>,
c_bnlgr: FloatTensor<Self>,
d_h: FloatTensor<Self>,
initial_state_bhpr: FloatTensor<Self>,
a_decay_h: FloatTensor<Self>,
) -> (FloatTensor<Self>, FloatTensor<Self>)
fn ssd_serial_recalculated( x_bnlhp: FloatTensor<Self>, dt_discretized_bhnl: FloatTensor<Self>, b_bnlgr: FloatTensor<Self>, c_bnlgr: FloatTensor<Self>, d_h: FloatTensor<Self>, initial_state_bhpr: FloatTensor<Self>, a_decay_h: FloatTensor<Self>, ) -> (FloatTensor<Self>, FloatTensor<Self>)
Memory-efficient combined forward+backward.
The two output tensors are concatenated into a single 1-D tracked tensor
so that one Backward<B, 7> node covers both outputs. The caller
receives split+reshaped slices of that combined tensor; burn’s autodiff
accumulates their upstream gradients back into a single gradient vector
before firing this backward.