Safe Haskell	None
Language	Haskell2010

TensorFlow.Session

Synopsis

type Session = SessionT IO
data SessionT m a
data Options
sessionConfig :: Lens' Options ConfigProto
sessionTarget :: Lens' Options ByteString
sessionTracer :: Lens' Options Tracer
runSession :: (MonadMask m, MonadIO m) => SessionT m a -> m a
runSessionWithOptions :: (MonadMask m, MonadIO m) => Options -> SessionT m a -> m a
class Monad m => MonadBuild m where
- build :: Build a -> m a
extend :: MonadIO m => SessionT m ()
addGraphDef :: MonadBuild m => GraphDef -> m ()
run :: (MonadIO m, Fetchable t a) => t -> SessionT m a
runWithFeeds :: (MonadIO m, Fetchable t a) => [Feed] -> t -> SessionT m a
run_ :: (MonadIO m, Nodes t) => t -> SessionT m ()
runWithFeeds_ :: (MonadIO m, Nodes t) => [Feed] -> t -> SessionT m ()
asyncProdNodes :: (MonadIO m, Nodes t) => t -> SessionT m ()

Documentation

type Session = SessionT IO Source #

data SessionT m a Source #

Instances

Instances details

MonadTrans SessionT Source #
Instance details Defined in TensorFlow.Session Methods lift :: Monad m => m a -> SessionT m a #
Monad m => Monad (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods (>>=) :: SessionT m a -> (a -> SessionT m b) -> SessionT m b # (>>) :: SessionT m a -> SessionT m b -> SessionT m b # return :: a -> SessionT m a #
Functor m => Functor (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods fmap :: (a -> b) -> SessionT m a -> SessionT m b # (<$) :: a -> SessionT m b -> SessionT m a #
MonadFail m => MonadFail (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods fail :: String -> SessionT m a #
Monad m => Applicative (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods pure :: a -> SessionT m a # (<>) :: SessionT m (a -> b) -> SessionT m a -> SessionT m b # liftA2 :: (a -> b -> c) -> SessionT m a -> SessionT m b -> SessionT m c # (>) :: SessionT m a -> SessionT m b -> SessionT m b # (<*) :: SessionT m a -> SessionT m b -> SessionT m a #
MonadIO m => MonadIO (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods liftIO :: IO a -> SessionT m a #
MonadCatch m => MonadCatch (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods catch :: Exception e => SessionT m a -> (e -> SessionT m a) -> SessionT m a
MonadMask m => MonadMask (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods mask :: ((forall a. SessionT m a -> SessionT m a) -> SessionT m b) -> SessionT m b uninterruptibleMask :: ((forall a. SessionT m a -> SessionT m a) -> SessionT m b) -> SessionT m b generalBracket :: SessionT m a -> (a -> ExitCase b -> SessionT m c) -> (a -> SessionT m b) -> SessionT m (b, c)
MonadThrow m => MonadThrow (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods throwM :: Exception e => e -> SessionT m a
Monad m => MonadBuild (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods build :: Build a -> SessionT m a Source #

data Options Source #

Customization for session. Use the lenses to update: sessionTarget, sessionTracer, sessionConfig.

Instances

Instances details

Default Options Source #
Instance details Defined in TensorFlow.Session Methods def :: Options

sessionConfig :: Lens' Options ConfigProto Source #

Uses the specified config for the created session.

sessionTarget :: Lens' Options ByteString Source #

Target can be: "local", ip:port, host:port. The set of supported factories depends on the linked in libraries.

sessionTracer :: Lens' Options Tracer Source #

Uses the given logger to monitor session progress.

runSession :: (MonadMask m, MonadIO m) => SessionT m a -> m a Source #

Run Session actions in a new TensorFlow session.

runSessionWithOptions :: (MonadMask m, MonadIO m) => Options -> SessionT m a -> m a Source #

Run Session actions in a new TensorFlow session created with the given option setter actions (sessionTarget, sessionConfig).

class Monad m => MonadBuild m where Source #

Lift a Build action into a monad, including any explicit op renderings.

Methods

build :: Build a -> m a Source #

Instances

Instances details

Monad m => MonadBuild (BuildT m) Source #
Instance details Defined in TensorFlow.Build Methods build :: Build a -> BuildT m a Source #
Monad m => MonadBuild (SessionT m) Source #
Instance details Defined in TensorFlow.Session Methods build :: Build a -> SessionT m a Source #

extend :: MonadIO m => SessionT m () Source #

Add all pending rendered nodes to the TensorFlow graph and runs any pending initializers.

Note that run, runWithFeeds, etc. will all call this function implicitly.

addGraphDef :: MonadBuild m => GraphDef -> m () Source #

run :: (MonadIO m, Fetchable t a) => t -> SessionT m a Source #

Run a subgraph t, rendering any dependent nodes that aren't already rendered, and fetch the corresponding values for a.

runWithFeeds :: (MonadIO m, Fetchable t a) => [Feed] -> t -> SessionT m a Source #

Run a subgraph t, rendering any dependent nodes that aren't already rendered, feed the given input values, and fetch the corresponding result values for a.

run_ :: (MonadIO m, Nodes t) => t -> SessionT m () Source #

Run a subgraph t, rendering and extending any dependent nodes that aren't already rendered. This behaves like run except that it doesn't do any fetches.

runWithFeeds_ :: (MonadIO m, Nodes t) => [Feed] -> t -> SessionT m () Source #

Run a subgraph t, rendering any dependent nodes that aren't already rendered, feed the given input values, and fetch the corresponding result values for a. This behaves like runWithFeeds except that it doesn't do any fetches.

asyncProdNodes Source #

Arguments

:: (MonadIO m, Nodes t)
=> t	Node to evaluate concurrently.
-> SessionT m ()

Starts a concurrent thread which evaluates the given Nodes forever until runSession exits or an exception occurs. Graph extension happens synchronously, but the resultant run proceeds as a separate thread.