org.tensorflow

Defines classes to build, save, load and execute TensorFlow models.

WARNING : The API is currently experimental and is not covered by TensorFlow API stability guarantees . See README.md for installation instructions.

The LabelImage example demonstrates use of this API to classify images using a pre-trained Inception architecture convolutional neural network. It demonstrates:

  • Graph construction: using the OperationBuilder class to construct a graph to decode, resize and normalize a JPEG image.
  • Model loading: Using Graph.importGraphDef() to load a pre-trained Inception model.
  • Graph execution: Using a Session to execute the graphs and find the best label for an image.

Additional examples can be found in the tensorflow/models GitHub repository.

Interfaces

ExecutionEnvironment Defines an environment for creating and executing TensorFlow Operation s.
Graph.WhileSubgraphBuilder Used to instantiate an abstract class which overrides the buildSubgraph method to build a conditional or body subgraph for a while loop.
Operand <T extends TType > Interface implemented by operands of a TensorFlow operation.
Operation Performs computation on Tensors.
OperationBuilder A builder for Operation s.
Tensor A statically typed multi-dimensional array.

Classes

ConcreteFunction A graph that can be invoked as a single function, with an input and output signature.
DeviceSpec Represents a (possibly partial) specification for a TensorFlow device.
DeviceSpec.Builder A Builder class for building DeviceSpec class.
EagerSession An environment for executing TensorFlow operations eagerly.
EagerSession.Options
Graph A data flow graph representing a TensorFlow computation.
GraphOperation Implementation for an Operation added as a node to a Graph .
GraphOperationBuilder An OperationBuilder for adding GraphOperation s to a Graph .
Output <T extends TType > A symbolic handle to a tensor produced by an Operation .
RawTensor A tensor which memory has not been mapped to a data space directly accessible from the JVM.
SavedModelBundle SavedModelBundle represents a model loaded from storage.
SavedModelBundle.Exporter Options for exporting a SavedModel.
SavedModelBundle.Loader Options for loading a SavedModel.
Server An in-process TensorFlow server, for use in distributed training.
Session Driver for Graph execution.
Session.Run Output tensors and metadata obtained when executing a session.
Session.Runner Run Operation s and evaluate Tensors .
Signature Describe the inputs and outputs of an executable entity, such as a ConcreteFunction , among other useful metadata.
Signature.Builder Builds a new function signature.
Signature.TensorDescription
TensorFlow Static utility methods describing the TensorFlow runtime.
TensorMapper <T extends TType > Maps the native memory of a RawTensor to a n-dimensional typed data space accessible from the JVM.

Enums

DeviceSpec.DeviceType
EagerSession.DevicePlacementPolicy Controls how to act when we try to run an operation on a given device but some input tensors are not on that device.
ExecutionEnvironment.Types