org.bytedeco.pytorch.DistributedSampler Maven / Gradle / Ivy

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// Targeted by JavaCPP version 1.5.9: DO NOT EDIT THIS FILE

package org.bytedeco.pytorch;

import org.bytedeco.pytorch.Allocator;
import org.bytedeco.pytorch.Function;
import org.bytedeco.pytorch.Module;
import java.nio.*;
import org.bytedeco.javacpp.*;
import org.bytedeco.javacpp.annotation.*;

import static org.bytedeco.javacpp.presets.javacpp.*;
import static org.bytedeco.openblas.global.openblas_nolapack.*;
import static org.bytedeco.openblas.global.openblas.*;

import static org.bytedeco.pytorch.global.torch.*;


/** A {@code 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
 *  {@code Sampler} performs a rounding operation based on the {@code allow_duplicates}
 *  parameter to decide the local sample count. */
@Name("torch::data::samplers::DistributedSampler >") @NoOffset @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
public class DistributedSampler extends Sampler {
    static { Loader.load(); }
    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
    public DistributedSampler(Pointer p) { super(p); }


  /** Set the epoch for the current enumeration. This can be used to alter the
   *  sample selection and shuffling behavior. */
  public native void set_epoch(@Cast("size_t") long epoch);

  public native @Cast("size_t") long epoch();
}