Distinguish between "rendered" and "unrendered" Tensors.
There are now three types of `Tensor`:
- `Tensor Value a`: rendered value
- `Tensor Ref a`: rendered reference
- `Tensor Build a` : unrendered value
The extra bookkeeping makes it easier to track (and enforce) which tensors are
rendered or not. For examples where this has been confusing in the past, see
With this change, pure ops look similar to before, returning `Tensor Build`
instead of `Tensor Value`. "Stateful" (monadic) ops are unchanged. For
example:
add :: OneOf [..] t => Tensor v'1 t -> Tensor v'2 t -> Tensor Build t
assign :: (MonadBuild m, TensorType t)
=> Tensor Ref t -> Tensor v'2 t -> m (Tensor Ref t)
The `gradients` function now requires that the variables over which it's
differentiating are pre-rendered:
gradients :: (..., Rendered v2) => Tensor v1 a -> [Tensor v2 a]
-> m [Tensor Value a]
(`Rendered v2` means that `v2` is either a `Ref` or a `Value`.)
Additionally, the implementation of `gradients` now takes care to render every
intermediate value when performing the reverse accumulation. I suspect this
fixes an exponential blowup for complicated expressions.
This change adds a class that both `Build` and `Session` are instances of:
class MonadBuild m where
build :: Build a -> m a
All stateful ops (generated and manually written) now have a signature that returns
an instance of `MonadBuild` (rather than just `Build`). For example:
assign_ :: (MonadBuild m, TensorType t)
=> Tensor Ref t -> Tensor v t -> m (Tensor Ref t)
This lets us remove a bunch of spurious calls to `build` in user code. It also
lets us replace the pattern `buildAnd run foo` with the simpler pattern `foo >>= run`
(or `run =<< foo`, which is sometimes nicer when foo is a complicated expression).
I went ahead and deleted `buildAnd` altogether since it seems to lead to
confusion; in particular a few tests had `buildAnd run . pure` which is
actually equivalent to just `run`.
* Fix for embedding gradient calculation
- Passes vectors instead of scalars to slice
- converts the numRows to a scalar
- add `toScalar` utility function
- minor change to test case so that it actually works
* added lib for testing helper functions
* add flatSlice function
