public class KerasXception extends AbstractZooModel
| Constructor and Description |
|---|
KerasXception()
Instantiate the model.
|
| Modifier and Type | Method and Description |
|---|---|
org.nd4j.linalg.dataset.api.preprocessor.ImagePreProcessingScaler |
getImagePreprocessingScaler()
Get the preprocessor to process this model's data with
|
int[] |
getInputShape()
Get the input shape of this zoomodel
|
Xception.VARIATION |
getVariation()
Get the current variation of the zoo model (e.g., Resnet50 or Resnet101)
|
org.deeplearning4j.nn.graph.ComputationGraph |
init(int numLabels,
long seed,
int[] shape,
boolean filterMode)
Initialize the ZooModel as MLP.
|
void |
setVariation(Xception.VARIATION var) |
getChannelsLast, getDefaultGraph, getExtraLayersToRemove, getFeatureExtractionLayer, getNumFExtractOutputs, getOptions, getOutputlayer, getPretrainedType, getPrettyName, initZooModel, isPretrained, isRequiresPooling, listOptions, requiresPreProcessing, setChannelsLast, setExtraLayersToRemove, setFeatureExtractionLayer, setNumFExtractOutputs, setOptions, setOutputLayer, setPretrainedType, setRequiresPooling@OptionMetadata(description="The model variation to use.",
displayName="Model Variation",
commandLineParamName="variation",
commandLineParamSynopsis="-variation <String>")
public Xception.VARIATION getVariation()
AbstractZooModelgetVariation in class AbstractZooModelpublic org.nd4j.linalg.dataset.api.preprocessor.ImagePreProcessingScaler getImagePreprocessingScaler()
AbstractZooModelgetImagePreprocessingScaler in class AbstractZooModelpublic void setVariation(Xception.VARIATION var)
public org.deeplearning4j.nn.graph.ComputationGraph init(int numLabels,
long seed,
int[] shape,
boolean filterMode)
AbstractZooModelinit in class AbstractZooModelnumLabels - Number of labels to adjust the outputseed - Seedshape - shapefilterMode - True if creating for feature extractionpublic int[] getInputShape()
AbstractZooModelgetInputShape in class AbstractZooModel