nn.combinators.FFwdStack
- class nn.combinators.FFwdStack(*args, **kwargs)[source]
Bases:
Assemble modules into a feed-forward stack, with linear weights in between
FFwdStack
accepts any number of modules as positional arguments, along with the required keyword argumentweight_init_func
.The weights placed in between each module will map the
size_out
of one module with thesize_in
of the following module. Weights are not placed on the input or output of the stack.Examples
>>> FFwdStack(mod0, mod1, weight_init_func = lambda s: np.random.normal(size = s))
A stack with two modules and one set of linear weights is generated. The weights will have shape
(mod0.size_out, mod1.size_in)
.- Parameters:
*mods (Module) – Any number of modules
weight_init_func (Callable) – A function that accepts a tuple defining the shape of a matrix, and returns a matrix of that shape to be used as a set of weights
- __init__ = <method-wrapper '__init__' of function object>