SavedModel

open class SavedModel : TensorFlowInferenceModel
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Inference model built on SavedModelBundle format to predict on images.

Constructors

SavedModel
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fun SavedModel()
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Types

Companion
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object Companion
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Functions

close
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open override fun close()
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Closes internal resources: session and kGraph.

copy
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open override fun copy(copiedModelName: String?, saveOptimizerState: Boolean, copyWeights: Boolean): TensorFlowInferenceModel
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Creates a copy.

evaluate
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fun evaluate(dataset: Dataset, metric: Metrics): Double
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Evaluates dataset via metric.

graphToString
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fun graphToString(): String
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Forms the graph description in string format.

input
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fun input(inputOp: Input)
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Chain-like setter to set up inputOp.

output
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fun output(outputOp: Output)
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Chain-like setter to set up outputOp.

predict
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open override fun predict(inputData: FloatArray): Int
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Generates output prediction for the input sample.

fun predict(dataset: Dataset): List<Int>
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Predicts labels for all observation in dataset.

fun predict(inputData: FloatArray, inputTensorName: String, outputTensorName: String): Int
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Predicts the class of inputData.

fun predict(dataset: OnHeapDataset, inputTensorName: String, outputTensorName: String): List<Int>
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Predicts labels for all observation in dataset.

predictSoftly
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open override fun predictSoftly(inputData: FloatArray, predictionTensorName: String): FloatArray
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Predicts vector of probabilities instead of specific class in predict method.

reshape
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open override fun reshape(vararg dims: Long)
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Chain-like setter to set up input shape.

toString
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open override fun toString(): String
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Properties

inputDimensions
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open override val inputDimensions: LongArray
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Input specification for this model.

isModelInitialized
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var isModelInitialized: Boolean = false
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Is true when model is initialized.

kGraph
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lateinit var kGraph: KGraph
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TensorFlow wrapped computational graph.

name
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var name: String? = null
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Model name.

shape
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lateinit var shape: LongArray
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Data shape for prediction.