object Quantization
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!=(arg0: Any): Boolean
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- @native() @throws( ... )
- def dequantize(input: Tensor[Float], buffer: Array[Byte], offset: Int, max: Array[Float], min: Array[Float]): Unit
- def dequantize(data: Array[Float], start: Int, end: Int, quantizedData: Array[Byte], offset: Int, max: Array[Float], min: Array[Float], size: Array[Int]): Unit
- def dequantize(src: Array[Float], start: Int, end: Int, dst: Array[Byte], dstOffset: Int, max: Float, min: Float): Unit
- def dequantize(byte: Byte, max: Float, min: Float): Float
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finalize(): Unit
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- def findMax(src: Array[Float], start: Int, end: Int): Float
- def findMin(src: Array[Float], start: Int, end: Int): Float
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getClass(): Class[_]
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hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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- def loss(before: Tensor[Float], after: Tensor[Float]): Double
- def loss(before: Array[Float], after: Array[Float], start: Int, end: Int): Double
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ne(arg0: AnyRef): Boolean
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def
notify(): Unit
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final
def
notifyAll(): Unit
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- def quantize[T](model: Module[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Module[T]
- def quantize(input: Tensor[Float], buffer: Array[Byte], offset: Int): (Array[Float], Array[Float])
- def quantize(src: Array[Float], start: Int, end: Int, dst: Array[Byte], dstOffset: Int, size: Array[Int]): (Array[Float], Array[Float])
- def quantize(src: Array[Float], start: Int, end: Int, dst: Array[Byte], dstOffset: Int): (Float, Float)
- def quantize(value: Float, max: Float, min: Float): Byte
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final
def
wait(arg0: Long): Unit
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