* Map torch::data::datasets::DistributedSampler and `StreamSampler…

…` from PyTorch (issue #1215)

pytorch/src/gen/java/org/bytedeco/pytorch/BatchSize.java

@@ -0,0 +1,32 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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 wrapper around a batch size value, which implements the
+ *  {@code CustomBatchRequest} interface. */
+@Namespace("torch::data::samplers") @NoOffset @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class BatchSize extends CustomBatchRequest {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public BatchSize(Pointer p) { super(p); }
+
+  public BatchSize(@Cast("size_t") long size) { super((Pointer)null); allocate(size); }
+  private native void allocate(@Cast("size_t") long size);
+  public native @Cast("size_t") @NoException(true) long size();
+  public native @Cast("size_t") @Name("operator size_t") @NoException(true) long asLong();
+  public native @Cast("size_t") long size_(); public native BatchSize size_(long setter);
+}

pytorch/src/gen/java/org/bytedeco/pytorch/BatchSizeOptional.java

@@ -0,0 +1,32 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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.*;
+
+@NoOffset @Name("c10::optional<torch::data::samplers::BatchSize>") @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class BatchSizeOptional extends Pointer {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public BatchSizeOptional(Pointer p) { super(p); }
+    public BatchSizeOptional(BatchSize value) { this(); put(value); }
+    public BatchSizeOptional()       { allocate();  }
+    private native void allocate();
+    public native @Name("operator =") @ByRef BatchSizeOptional put(@ByRef BatchSizeOptional x);
+
+    public native boolean has_value();
+    public native @Name("value") @ByRef BatchSize get();
+    @ValueSetter public native BatchSizeOptional put(@ByRef BatchSize value);
+}
+

pytorch/src/gen/java/org/bytedeco/pytorch/BatchSizeSampler.java

@@ -0,0 +1,39 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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.*;
+
+@Name("torch::data::samplers::Sampler<torch::data::samplers::BatchSize>") @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class BatchSizeSampler extends Pointer {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public BatchSizeSampler(Pointer p) { super(p); }
+
+
+  /** Resets the {@code Sampler}'s internal state.
+   *  Typically called before a new epoch.
+   *  Optionally, accepts a new size when reseting the sampler. */
+  public native void reset(@ByVal SizeTOptional new_size);
+
+  /** Returns the next index if possible, or an empty optional if the
+   *  sampler is exhausted for this epoch. */
+  public native @ByVal BatchSizeOptional next(@Cast("size_t") long batch_size);
+
+  /** Serializes the {@code Sampler} to the {@code archive}. */
+  public native void save(@ByRef OutputArchive archive);
+
+  /** Deserializes the {@code Sampler} from the {@code archive}. */
+  public native void load(@ByRef InputArchive archive);
+}

pytorch/src/gen/java/org/bytedeco/pytorch/CustomBatchRequest.java

@@ -0,0 +1,28 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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 base class for custom index types. */
+@Namespace("torch::data::samplers") @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class CustomBatchRequest extends Pointer {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public CustomBatchRequest(Pointer p) { super(p); }
+
+
+  /** The number of elements accessed by this index. */
+  public native @Cast("size_t") long size();
+}

pytorch/src/gen/java/org/bytedeco/pytorch/DistributedRandomSampler.java

@@ -0,0 +1,57 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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.*;
+
+
+/** Select samples randomly. The sampling order is shuffled at each {@code reset()}
+ *  call. */
+@Namespace("torch::data::samplers") @NoOffset @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class DistributedRandomSampler extends DistributedSampler {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public DistributedRandomSampler(Pointer p) { super(p); }
+
+  public DistributedRandomSampler(
+        @Cast("size_t") long size,
+        @Cast("size_t") long num_replicas/*=1*/,
+        @Cast("size_t") long rank/*=0*/,
+        @Cast("bool") boolean allow_duplicates/*=true*/) { super((Pointer)null); allocate(size, num_replicas, rank, allow_duplicates); }
+  private native void allocate(
+        @Cast("size_t") long size,
+        @Cast("size_t") long num_replicas/*=1*/,
+        @Cast("size_t") long rank/*=0*/,
+        @Cast("bool") boolean allow_duplicates/*=true*/);
+  public DistributedRandomSampler(
+        @Cast("size_t") long size) { super((Pointer)null); allocate(size); }
+  private native void allocate(
+        @Cast("size_t") long size);
+
+  /** Resets the {@code DistributedRandomSampler} to a new set of indices. */
+  public native void reset(@ByVal(nullValue = "c10::optional<size_t>(c10::nullopt)") SizeTOptional new_size);
+  public native void reset();
+
+  /** Returns the next batch of indices. */
+  public native @ByVal SizeTVectorOptional next(@Cast("size_t") long batch_size);
+
+  /** Serializes the {@code DistributedRandomSampler} to the {@code archive}. */
+  public native void save(@ByRef OutputArchive archive);
+
+  /** Deserializes the {@code DistributedRandomSampler} from the {@code archive}. */
+  public native void load(@ByRef InputArchive archive);
+
+  /** Returns the current index of the {@code DistributedRandomSampler}. */
+  public native @Cast("size_t") @NoException(true) long index();
+}

pytorch/src/gen/java/org/bytedeco/pytorch/DistributedSampler.java

@@ -0,0 +1,36 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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<std::vector<size_t> >") @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();
+}

pytorch/src/gen/java/org/bytedeco/pytorch/DistributedSequentialSampler.java

@@ -0,0 +1,56 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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.*;
+
+
+/** Select samples sequentially. */
+@Namespace("torch::data::samplers") @NoOffset @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class DistributedSequentialSampler extends DistributedSampler {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public DistributedSequentialSampler(Pointer p) { super(p); }
+
+  public DistributedSequentialSampler(
+        @Cast("size_t") long size,
+        @Cast("size_t") long num_replicas/*=1*/,
+        @Cast("size_t") long rank/*=0*/,
+        @Cast("bool") boolean allow_duplicates/*=true*/) { super((Pointer)null); allocate(size, num_replicas, rank, allow_duplicates); }
+  private native void allocate(
+        @Cast("size_t") long size,
+        @Cast("size_t") long num_replicas/*=1*/,
+        @Cast("size_t") long rank/*=0*/,
+        @Cast("bool") boolean allow_duplicates/*=true*/);
+  public DistributedSequentialSampler(
+        @Cast("size_t") long size) { super((Pointer)null); allocate(size); }
+  private native void allocate(
+        @Cast("size_t") long size);
+
+  /** Resets the {@code DistributedSequentialSampler} to a new set of indices. */
+  public native void reset(@ByVal(nullValue = "c10::optional<size_t>(c10::nullopt)") SizeTOptional new_size);
+  public native void reset();
+
+  /** Returns the next batch of indices. */
+  public native @ByVal SizeTVectorOptional next(@Cast("size_t") long batch_size);
+
+  /** Serializes the {@code DistributedSequentialSampler} to the {@code archive}. */
+  public native void save(@ByRef OutputArchive archive);
+
+  /** Deserializes the {@code DistributedSequentialSampler} from the {@code archive}. */
+  public native void load(@ByRef InputArchive archive);
+
+  /** Returns the current index of the {@code DistributedSequentialSampler}. */
+  public native @Cast("size_t") @NoException(true) long index();
+}

pytorch/src/gen/java/org/bytedeco/pytorch/StreamSampler.java

@@ -0,0 +1,50 @@
+// Targeted by JavaCPP version 1.5.9-SNAPSHOT: 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 sampler for (potentially infinite) streams of data.
+ * 
+ *  The major feature of the {@code StreamSampler} is that it does not return
+ *  particular indices, but instead only the number of elements to fetch from
+ *  the dataset. The dataset has to decide how to produce those elements. */
+@Namespace("torch::data::samplers") @NoOffset @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class StreamSampler extends BatchSizeSampler {
+    static { Loader.load(); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public StreamSampler(Pointer p) { super(p); }
+
+  /** Constructs the {@code StreamSampler} with the number of individual examples that
+   *  should be fetched until the sampler is exhausted. */
+  public StreamSampler(@Cast("size_t") long epoch_size) { super((Pointer)null); allocate(epoch_size); }
+  private native void allocate(@Cast("size_t") long epoch_size);
+
+  /** Resets the internal state of the sampler. */
+  public native void reset(@ByVal(nullValue = "c10::optional<size_t>(c10::nullopt)") SizeTOptional new_size);
+  public native void reset();
+
+  /** Returns a {@code BatchSize} object with the number of elements to fetch in the
+   *  next batch. This number is the minimum of the supplied {@code batch_size} and
+   *  the difference between the {@code epoch_size} and the current index. If the
+   *  {@code epoch_size} has been reached, returns an empty optional. */
+  public native @ByVal BatchSizeOptional next(@Cast("size_t") long batch_size);
+
+  /** Serializes the {@code StreamSampler} to the {@code archive}. */
+  public native void save(@ByRef OutputArchive archive);
+
+  /** Deserializes the {@code StreamSampler} from the {@code archive}. */
+  public native void load(@ByRef InputArchive archive);
+}