Lambda¶

class continual.Lambda(fn=None, forward_only_fn=None, forward_step_only_fn=None, forward_steps_only_fn=None, takes_time=False)[source]¶

Module wrapper for stateless functions.

Note

Operations performed in a Lambda are not counted in ptflops

Parameters:

fn (Callable[[Tensor], Tensor]) – Function to be called during forward.
forward_only_fn – Function to be called only during forward. fn is used for the other call modes.
forward_step_only_fn – Function to be called only during forward_step. fn is used for the other call modes.
forward_steps_only_fn – Function to be called only during forward_steps. fn is used for the other call modes.
forward_only_fn – Function to be called only during forward. fn is used for the other call modes.
takes_time – If True, fn receives all steps, if False, it received one step and no time dimension. Defaults to False.

Examples:

x = torch.arange(90).reshape(1,3,30) * 1.0

# Using named function
def same_stats_different_values(x):
    return torch.randn_like(x) * x.std() + x.mean()

same_stats_layer = co.Lambda(same_stats_different_values)
same_stats_layer(x)

# Using unnamed function
mean_layer = co.Lambda(lambda x: torch.ones_like(x) * x.mean())
mean_layer(x)

# Using functor
sigmoid = co.Lambda(torch.nn.Sigmoid())
sigmoid(x)