def common_AE_encoder_tail(stack: Stacker,
latent_code_size,
bn=False,
activation='relu') -> Stacker:
stack.linear(latent_code_size)
if bn:
stack.bn()
stack.activation(activation)
return stack
def encoder_tail(stack: Stacker,
latent_code_size,
bn=False,
activation='none') -> Stacker:
stack.linear(latent_code_size * 2)
if bn:
stack.bn()
stack.activation(activation)
return stack
def common_linear_stack(stack: Stacker,
net_shapes,
bn=True,
activation='relu') -> Stacker:
for shape in net_shapes:
stack.linear(shape)
if bn:
stack.bn()
stack.activation(activation)
return stack
def common_AE_decoder_tail(stack: Stacker,
flatten_size,
output_shape,
bn=False,
activation='sigmoid') -> Stacker:
stack.linear(flatten_size)
if bn:
stack.bn()
stack.activation(activation)
stack.reshape(output_shape)
return stack
def encoder_tail(stack: Stacker,
Y_flatten_size,
z_size,
bn=False,
activation='none'):
stack.linear(z_size + Y_flatten_size)
if bn:
stack.bn()
stack.activation(activation)
zs = stack.last_layer[:, :z_size]
Ys_gen = stack.last_layer[:, z_size:]
hs = softmax(Ys_gen)
return zs, Ys_gen, hs
