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Author SHA1 Message Date
Judah Jacobson
56038ba27e Depend on a newer proto-lens and remove orphan Ord instances. (#146)
proto-lens-0.2.2.0 generates Ord instances for all message types,
so we can remove the orphan instances we previously added.

Dependends on proto-lens-protoc-0.2.2.1 or newer due to google/proto-lens#113.
2017-08-02 22:47:55 -07:00
Judah Jacobson
42f4fc647e Add resource-based variable ops. (#98)
The main difference between these and the `Ref`-bases ops is the explicit
`readValue` op.  I'm not sure how this should interact with gradients
and save/restore, so I'm keeping it as a separate module for now.  Once we
figure out the details, we can merge it into `TensorFlow.Ops` and replace
all uses of the old `Ref`-based ops.  (That would also fix #92.)

Also replaces our special case newtype `ResourceHandle` to
`Tensor Value ResourceHandle`, where `ResourceHandle` is the TF proto
corresponding to `DT_RESOURCE`.
2017-04-16 09:24:02 -07:00
Judah Jacobson
d62c614695 Distinguish between "rendered" and "unrendered" Tensors. (#88)
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.
2017-04-06 15:10:33 -07:00
Judah Jacobson
2c5c879037 Introduce a MonadBuild class, and remove buildAnd. (#83)
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`.
2017-03-18 12:08:53 -07:00
fkm3
b3c0997a8c Add support for logging to tensorboard (#74)
Add support for logging to tensorboard

Based on @gnezdo's internal version with some differences:

* Uses a pure haskell implementation of EventWriter instead of FFI.
* Special `buildAnd*` functions were dropped in favor of using
  `mergeAllSummaries :: Build SummaryTensor` with the normal
  `build` function.
2017-02-20 19:16:42 -08:00
Greg Steuck
67690d1499 Initial commit 2016-10-24 19:26:42 +00:00