- 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.
Defines an environment for creating and executing TensorFlow
|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.|
A builder for
|Tensor||A statically typed multi-dimensional array.|
|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.|
A Builder class for building
|EagerSession||An environment for executing TensorFlow operations eagerly.|
|Graph||A data flow graph representing a TensorFlow computation.|
Implementation for an
|Output <T extends TType >||
A symbolic handle to a tensor produced by an
|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.Run||Output tensors and metadata obtained when executing a session.|
Describe the inputs and outputs of an executable entity, such as a
|Signature.Builder||Builds a new function signature.|
|TensorFlow||Static utility methods describing the TensorFlow runtime.|
|TensorMapper <T extends TType >||
Maps the native memory of a