nn.gates.layers

fn dropout_gate[T](mask &vtl.Tensor[T], prob f64) &DropoutGate[T]

fn flatten_gate[T](input &autograd.Variable[T], cached_shape []int) &FlattenGate[T]

fn input_gate[T]() &InputGate[T]

fn linear_gate[T](input &autograd.Variable[T], weight &autograd.Variable[T], bias &autograd.Variable[T]) &LinearGate[T]

fn lstm_gate[T](input_ &vtl.Tensor[T],
	hidden_ &vtl.Tensor[T],
	cell_ &vtl.Tensor[T],
	w_ih &vtl.Tensor[T],
	w_hh &vtl.Tensor[T],
	b_ih &vtl.Tensor[T],
	b_hh &vtl.Tensor[T]) &LSTMGate[T]

fn maxpool2d_gate[T](max_indices &vtl.Tensor[int], kernel []int, shape []int, stride []int, padding []int) &MaxPool2DGate[T]

fn (g &DropoutGate[T]) backward[T](payload &autograd.Payload[T]) ![]&vtl.Tensor[T]

fn (g &DropoutGate[T]) cache[T](mut result autograd.Variable[T], args ...autograd.CacheParam) !

fn (g &FlattenGate[T]) backward[T](payload &autograd.Payload[T]) ![]&vtl.Tensor[T]

fn (g &FlattenGate[T]) cache[T](mut result autograd.Variable[T], args ...autograd.CacheParam) !

fn (g &InputGate[T]) backward[T](payload &autograd.Payload[T]) ![]&vtl.Tensor[T]

fn (g &InputGate[T]) cache[T](mut result autograd.Variable[T], args ...autograd.CacheParam) !

fn (g &LSTMGate[T]) backward[T](payload &autograd.Payload[T]) ![]&vtl.Tensor[T]

fn (g &LSTMGate[T]) cache[T](mut result autograd.Variable[T], args ...autograd.CacheParam) !

fn (g &LinearGate[T]) backward[T](payload &autograd.Payload[T]) ![]&vtl.Tensor[T]

fn (g &LinearGate[T]) cache[T](mut result autograd.Variable[T], args ...autograd.CacheParam) !

fn (g &MaxPool2DGate[T]) backward[T](payload &autograd.Payload[T]) ![]&vtl.Tensor[T]

fn (g &MaxPool2DGate[T]) cache[T](mut result autograd.Variable[T], args ...autograd.CacheParam) !

struct DropoutGate[T] {
pub:
	prob f64
	mask &vtl.Tensor[T] = unsafe { nil }
}

struct FlattenGate[T] {
pub:
	input        &autograd.Variable[T] = unsafe { nil }
	cached_shape []int
}

struct InputGate[T] {}

struct LSTMGate[T] {
	input_  &vtl.Tensor[T] = unsafe { nil }
	hidden_ &vtl.Tensor[T] = unsafe { nil }
	cell_   &vtl.Tensor[T] = unsafe { nil }
	w_ih    &vtl.Tensor[T] = unsafe { nil }
	w_hh    &vtl.Tensor[T] = unsafe { nil }
	b_ih    &vtl.Tensor[T] = unsafe { nil }
	b_hh    &vtl.Tensor[T] = unsafe { nil }
}

LSTMGate implements the forward pass of LSTM with full gradients. This is a basic implementation; for production use an optimized version.

struct LinearGate[T] {
pub:
	input  &autograd.Variable[T] = unsafe { nil }
	weight &autograd.Variable[T] = unsafe { nil }
	bias   &autograd.Variable[T] = unsafe { nil }
}

struct MaxPool2DGate[T] {
pub:
	max_indices &vtl.Tensor[int] = unsafe { nil }
	kernel      []int
	shape       []int
	stride      []int
	padding     []int
}