Interface ExampleTransformer
- All Superinterfaces:
com.oracle.labs.mlrg.olcut.config.Configurable,com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>,Serializable
- All Known Implementing Classes:
DenseTransformer,ImageTransformer
public interface ExampleTransformer
extends com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>, Serializable
Transforms a
SparseVector, extracting the features from it as a OnnxTensor.
This usually densifies the example, so can be a lot larger than the input example.
N.B. ONNX support is experimental, and may change without a major version bump.
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Method Summary
Modifier and TypeMethodDescriptionai.onnxruntime.OnnxTensortransform(ai.onnxruntime.OrtEnvironment env, List<SparseVector> vectors) Converts a list ofSparseVectors representing a batch of features into aOnnxTensor.ai.onnxruntime.OnnxTensortransform(ai.onnxruntime.OrtEnvironment env, SparseVector vector) Converts aSparseVectorrepresenting the features into aOnnxTensor.Methods inherited from interface com.oracle.labs.mlrg.olcut.config.Configurable
postConfigMethods inherited from interface com.oracle.labs.mlrg.olcut.provenance.Provenancable
getProvenance
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Method Details
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transform
ai.onnxruntime.OnnxTensor transform(ai.onnxruntime.OrtEnvironment env, SparseVector vector) throws ai.onnxruntime.OrtException Converts aSparseVectorrepresenting the features into aOnnxTensor.It generates it as a single example minibatch.
- Parameters:
env- The OrtEnvironment to create the tensor in.vector- The features to convert.- Returns:
- A dense OnnxTensor representing this vector.
- Throws:
ai.onnxruntime.OrtException- if the transformation failed.
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transform
ai.onnxruntime.OnnxTensor transform(ai.onnxruntime.OrtEnvironment env, List<SparseVector> vectors) throws ai.onnxruntime.OrtException Converts a list ofSparseVectors representing a batch of features into aOnnxTensor.- Parameters:
env- The OrtEnvironment to create the tensor in.vectors- The batch of features to convert.- Returns:
- A dense OnnxTensor representing this minibatch.
- Throws:
ai.onnxruntime.OrtException- if the transformation failed.
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