class
MaxPooling1D extends Convolution with Layer
Instance Constructors
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new
MaxPooling1D(kernelSize: List[Int], stride: List[Int] = immutable.this.List.apply[Int](1), padding: List[Int] = immutable.this.List.apply[Int](0), dilation: List[Int] = immutable.this.List.apply[Int](1), nIn: Option[List[Int]] = scala.None, name: String = "")
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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def
compile: Layer
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def
describe(): String
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val
dimension: Int
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final
def
eq(arg0: AnyRef): Boolean
-
def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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def
inputShape: List[Int]
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final
def
isInstanceOf[T0]: Boolean
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val
nChannels: Int
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val
nFilter: Int
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val
name: String
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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def
outputShape: List[Int]
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def
reshapeInput(nIn: List[Int]): MaxPooling1D
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from AnyRef
Inherited from Any
1D max pooling layer in neural net architectures.