@Name(value="torch::data::samplers::DistributedSampler<std::vector<size_t> >") @NoOffset @Properties(inherit=torch.class) public class DistributedSampler extends Sampler
Sampler
that selects a subset of indices to sample from and defines a
sampling behavior. In a distributed setting, this selects a subset of the
indices depending on the provided num_replicas and rank parameters. The
Sampler
performs a rounding operation based on the allow_duplicates
parameter to decide the local sample count.Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter
Constructor and Description |
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DistributedSampler(Pointer p)
Pointer cast constructor.
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Modifier and Type | Method and Description |
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long |
epoch() |
void |
set_epoch(long epoch)
Set the epoch for the current enumeration.
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address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getDirectBufferAddress, getPointer, getPointer, getPointer, getPointer, hashCode, interruptDeallocatorThread, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, physicalBytesInaccurate, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zero
public DistributedSampler(Pointer p)
Pointer(Pointer)
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