Package org.tensorflow

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

See: Description

Interface Summary

Interface	Description
Operand<T>	Interface implemented by operands of a TensorFlow operation.

Class Summary

Class	Description
Graph	A data flow graph representing a TensorFlow computation.
Operation	A Graph node that performs computation on Tensors.
OperationBuilder	A builder for Operations in a Graph.
Output<T>	A symbolic handle to a tensor produced by an Operation.
SavedModelBundle	SavedModelBundle represents a model loaded from storage.
Session	Driver for Graph execution.
Session.Run	Output tensors and metadata obtained when executing a session.
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.

Enum Summary

Enum	Description
DataType	Represents the type of elements in a Tensor as an enum.

Exception Summary

Exception	Description
TensorFlowException	Unchecked exception thrown when executing TensorFlow Graphs.

Package org.tensorflow Description

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.