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 Operations. 
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> Interface implemented by operands of a TensorFlow operation. 
Operation Performs computation on Tensors. 
OperationBuilder A builder for Operations. 

Classes

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 GraphOperations to a Graph
Output<T> A symbolic handle to a tensor produced by an Operation
SavedModelBundle SavedModelBundle represents a model loaded from storage. 
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 Operations and evaluate Tensors
Shape The possibly partially known shape of a tensor produced by an operation. 
Tensor<T> A statically typed multi-dimensional array whose elements are of a type described by T. 
TensorFlow Static utility methods describing the TensorFlow runtime. 
Tensors Type-safe factory methods for creating Tensor objects. 

Enums

DataType Represents the type of elements in a Tensor as an enum. 
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. 
EagerSession.ResourceCleanupStrategy Controls how TensorFlow resources are cleaned up when they are no longer needed. 

Exceptions

TensorFlowException Unchecked exception thrown when executing TensorFlow Graphs.