case class CudaDevice(i: Int) extends Device with Product with Serializable
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- new CudaDevice(i: Int)
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final
def
##(): Int
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def
==(arg0: Any): Boolean
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def
allocateBuffers[S](size: Long, options: STenOptions)(implicit arg0: Sc[S]): BufferPair
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asInstanceOf[T0]: T0
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getClass(): Class[_]
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def
isInstanceOf[T0]: Boolean
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def
measureTime[A](f: ⇒ A): (A, Long)
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- CudaDevice → Device
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final
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notify(): Unit
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def
notifyAll(): Unit
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def
options[S](precision: FloatingPointPrecision)(implicit arg0: Sc[S]): STenOptions
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- CudaDevice → Device
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def
setSeed(seed: Long): Unit
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- CudaDevice → Device
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
to(t: Tensor): Tensor
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- CudaDevice → Device
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def
to[S](t: STenOptions)(implicit arg0: Sc[S]): STenOptions
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- CudaDevice → Device
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def
to[S](t: STen)(implicit arg0: Sc[S]): STen
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def
toBatched[S](tensors: Seq[STen], buffers: BufferPair)(implicit arg0: Sc[S]): Seq[STen]
Copies tensors to this device in a single cross device copy.
Copies tensors to this device in a single cross device copy. srcBuffer is supposed to be on the source device. dstBuffer has to be on
this
device. Tensors are first copied to the srcBuffer, then the srcBuffer is copied to dstBuffer, then the dstBuffer is split into views.All tensors must have the same data type.
Might make sense to pin the srcBuffer.
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final
def
wait(arg0: Long, arg1: Int): Unit
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def
wait(): Unit
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def
withOtherStreamThenSync[A](synchronizeBefore: Boolean)(f: ⇒ A): A
Executes f on a new stream f must not switch to other threads Restores the stream to the default stream
Executes f on a new stream f must not switch to other threads Restores the stream to the default stream
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def
finalize(): Unit
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