Class TensorflowTrainer<T extends Output<T>>

java.lang.Object
org.tribuo.interop.tensorflow.TensorflowTrainer<T>
All Implemented Interfaces:
com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<TrainerProvenance>, Trainer<T>

public final class TensorflowTrainer<T extends Output<T>> extends Object implements Trainer<T>
Trainer for Tensorflow. Expects the underlying Tensorflow graph to have specific placeholders and targets listed below. This trainer only works with graphs setup for minibatches. To recover single example training just use a batch size of 1.

This trainer uses the serialisation functionality in TensorflowUtil, as opposed to a SavedModel or a checkpoint.

N.B. Tensorflow support is experimental and may change without a major version bump.

  • Field Details

  • Constructor Details

    • TensorflowTrainer

      public TensorflowTrainer(Path graphPath, ExampleTransformer<T> exampleTransformer, OutputTransformer<T> outputTransformer, int minibatchSize, int epochs, int testBatchSize) throws IOException
      Constructs a Trainer for a tensorflow graph.
      Parameters:
      graphPath - The path to the graph protobuf. Must have the targets and placeholders specified above.
      exampleTransformer - The example transformer to convert a Tribuo Example into a Tensor.
      outputTransformer - The output transformer to convert a Tribuo Output into a Tensor and back. This encodes the output type.
      minibatchSize - The minibatch size to use in training.
      epochs - The number of SGD epochs to run.
      testBatchSize - The minibatch size to use at test time.
      Throws:
      IOException - If the graphPath is invalid or failed to load.
    • TensorflowTrainer

      public TensorflowTrainer(byte[] graphDef, ExampleTransformer<T> exampleTransformer, OutputTransformer<T> outputTransformer, int minibatchSize, int epochs, int testBatchSize)
      Constructs a Trainer for a tensorflow graph.
      Parameters:
      graphDef - The graph definition as a byte array. Must have the targets and placeholders specified above.
      exampleTransformer - The example transformer to convert a Tribuo Example into a Tensor.
      outputTransformer - The output transformer to convert a Tribuo Output into a Tensor and back. This encodes the output type.
      minibatchSize - The minibatch size to use in training.
      epochs - The number of SGD epochs to run.
      testBatchSize - The minibatch size to use at test time.
  • Method Details

    • postConfig

      public void postConfig() throws IOException
      Used by the OLCUT configuration system, and should not be called by external code.
      Specified by:
      postConfig in interface com.oracle.labs.mlrg.olcut.config.Configurable
      Throws:
      IOException
    • train

      public Model<T> train(Dataset<T> examples, Map<String, com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance)
      Description copied from interface: Trainer
      Trains a predictive model using the examples in the given data set.
      Specified by:
      train in interface Trainer<T extends Output<T>>
      Parameters:
      examples - the data set containing the examples.
      runProvenance - Training run specific provenance (e.g., fold number).
      Returns:
      a predictive model that can be used to generate predictions for new examples.
    • toString

      public String toString()
      Overrides:
      toString in class Object
    • getInvocationCount

      public int getInvocationCount()
      Description copied from interface: Trainer
      The number of times this trainer instance has had it's train method invoked.

      This is used to determine how many times the trainer's RNG has been accessed to ensure replicability in the random number stream.

      Specified by:
      getInvocationCount in interface Trainer<T extends Output<T>>
      Returns:
      The number of train invocations.
    • getProvenance

      Specified by:
      getProvenance in interface com.oracle.labs.mlrg.olcut.provenance.Provenancable<T extends Output<T>>