Trait/Object

com.intel.analytics.zoo.pipeline.api

Net

Related Docs: object Net | package api

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trait Net extends AnyRef

A placeholder to add layer's utilities

Linear Supertypes
AnyRef, Any
Known Subclasses
Activation, Activation, AddConstant, AtrousConvolution1D, AtrousConvolution2D, Average, AveragePooling1D, AveragePooling1D, AveragePooling2D, AveragePooling3D, BERT, BatchNormalization, Bidirectional, BinaryThreshold, Bridge, CAdd, CMul, Conv1D, Conv2D, ConvLSTM2D, ConvLSTM3D, Convolution1D, Convolution2D, Convolution3D, Cropping1D, Cropping1D, Cropping2D, Cropping3D, Decoder, Deconvolution2D, Dense, Dense, Dropout, Dropout, ELU, Embedding, Encoder, Exp, Expand, ExpandDim, Flatten, Flatten, GRU, GaussianDropout, GaussianNoise, GaussianSampler, GlobalAveragePooling1D, GlobalAveragePooling1D, GlobalAveragePooling2D, GlobalAveragePooling2D, GlobalAveragePooling3D, GlobalAveragePooling3D, GlobalMaxPooling1D, GlobalMaxPooling1D, GlobalMaxPooling2D, GlobalMaxPooling2D, GlobalMaxPooling3D, GlobalMaxPooling3D, HardShrink, HardTanh, Highway, Identity, Input, KerasLayerWrapper, KerasNet, LRN2D, LSTM, LambdaLayer, LayerNorm, LayerWrapperByForward, LeakyReLU, LocallyConnected1D, LocallyConnected1D, LocallyConnected2D, Log, Masking, Max, MaxPooling1D, MaxPooling1D, MaxPooling2D, MaxPooling3D, Maximum, MaxoutDense, Merge, Minimum, Model, Mul, MulConstant, Narrow, Negative, PReLU, Permute, Pooling1D, Pooling2D, Power, RNNDecoder, RNNEncoder, RReLU, RepeatVector, Reshape, ResizeBilinear, SReLU, Select, SelectTable, SeparableConvolution2D, Sequential, ShareConvolution2D, SimpleRNN, SoftMax, SoftMax, SoftShrink, SparseDense, SparseEmbedding, SpatialDropout1D, SpatialDropout2D, SpatialDropout3D, SplitTensor, Sqrt, Square, Squeeze, Threshold, ThresholdedReLU, TimeDistributed, UpSampling1D, UpSampling2D, UpSampling3D, WithinChannelLRN2D, WordEmbedding, ZeroPadding1D, ZeroPadding2D, ZeroPadding3D
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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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  9. def from[T](vars: Variable[T]*)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Variable[T]

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    Build graph: some other modules point to current module

    Build graph: some other modules point to current module

    vars

    upstream variables

    returns

    Variable containing current module

  10. final def getClass(): Class[_]

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  11. def hashCode(): Int

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  12. def isFrozen[T]()(implicit arg0: ClassTag[T]): Boolean

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  13. final def isInstanceOf[T0]: Boolean

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  14. final def ne(arg0: AnyRef): Boolean

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. final def synchronized[T0](arg0: ⇒ T0): T0

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  18. def toString(): String

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  19. final def wait(): Unit

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  20. final def wait(arg0: Long, arg1: Int): Unit

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  21. final def wait(arg0: Long): Unit

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