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

Uses the specified config for the created session.

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

Uses the given logger to monitor session progress.

Run Session actions in a new TensorFlow session.

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

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

Helper combinator for doing something with the result of a Build action. Example usage:

buildAnd run :: Fetchable t a => Build t -> Session a

Lift a Build action into a Session, including any explicit op renderings. Returns the merged summary ops which can be used for logging, see build for a convenient wrapper.

Types that tensor representations (e.g. Tensor, ControlNode) can be fetched into.

Includes collections of tensors (e.g. tuples).

Types that contain ops which can be run.

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

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.

A pair of a Tensor and some data that should be fed into that Tensor when running the graph.

Create a Feed for feeding the given data into a Tensor when running the graph.

Note that if a Tensor is rendered, its identity may change; so feeding the rendered Tensor may be different than feeding the original Tensor.

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 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.

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.

An action for building nodes in a TensorFlow graph.

An action for building nodes in a TensorFlow graph. Used to manage build state internally as part of the Session monad.

Render a Tensor, fixing its name, scope, device and control inputs from the Build context. Also renders any dependencies of the Tensor that weren't already rendered.

This operation is idempotent; render >=> render === render. However, rendering a (previously un-rendered) Tensor in two different contexts may result in two different Tensors.

Produce a GraphDef proto representation of the nodes that are rendered in the given Build action.

A type of graph node which has no outputs. These nodes are valuable for causing side effects when they are run.

A named output of a TensorFlow operation.

The type parameter a is the type of the elements in the Tensor. The parameter v is either Value or Ref, depending on whether the graph is treating this op output as an immutable Value or a stateful Ref (e.g., a variable). Note that a Tensor Ref can be casted into a Tensor Value via value.

This class provides a runtime switch on whether a Tensor should be treated as a Value or as a Ref.

Lens for the attributes of a tensor.

Only valid if the tensor has not yet been rendered. If the tensor has been rendered, the traversal will be over nothing (nothing can be read or written).

Cast a 'Tensor *' into a 'Tensor Value'. Common usage is to cast a Ref into Value. This behaves like a no-op.

Create a Tensor for a given name. This can be used to reference nodes in a GraphDef that was loaded via addGraphDef. TODO(judahjacobson): add more safety checks here.

Data about a tensor that is encoded for the TensorFlow APIs.

The class of scalar types supported by tensorflow.

Shape (dimensions) of a tensor.

A Constraint specifying the possible choices of a TensorType.

We implement a Constraint like OneOf '[Double, Float] a by turning the natural representation as a conjunction, i.e.,

   a == Double || a == Float

into a disjunction like

    a /= Int32 && a /= Int64 && a /= ByteString && ...

using an enumeration of all the possible TensorTypes.

A constraint checking that two types are different.

Places all nodes rendered in the given Build action on the same device as the given Tensor (see also withDevice). Make sure that the action has side effects of rendering the desired tensors. A pure return would not have the desired effect.

A device that a node can be assigned to. There's a naming convention where the device names are constructed from job and replica names.

Set a device for all nodes rendered in the given Build action (unless further overridden by another use of withDevice).

Prepend a scope to all nodes rendered in the given Build action.

Returns a Tensor with a given name and the same shape and contents as the input.

TODO(judahjacobson): This breaks when used with uninitialize Tensor Refs, since RefIdentity doesn't have SetAllowsUninitializedInput(). Look into whether we can change that op.

Modify a Build action, such that all new ops rendered in it will depend on the nodes in the first argument.

Create an op that groups multiple operations.

When this op finishes, all ops in the input n have finished. This op has no output.

Returns a Tensor with the same shape and contents as the input.

Does nothing. Only useful as a placeholder for control edges.