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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.


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


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. 
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. 


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


TensorFlowException Unchecked exception thrown when executing TensorFlow Graphs.