org.bytedeco.pytorch.MaxUnpool3dImpl Maven / Gradle / Ivy
// Targeted by JavaCPP version 1.5.7: 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.*;
// ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ MaxUnpool3d ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
/** Applies maxunpool over a 3-D input.
* See https://pytorch.org/docs/master/nn.html#torch.nn.MaxUnpool3d to learn
* about the exact behavior of this module.
*
* See the documentation for {@code torch::nn::MaxUnpool3dOptions} class to learn what
* constructor arguments are supported for this module.
*
* Example:
* {@code
* MaxUnpool3d model(MaxUnpool3dOptions(3).stride(2).padding(1));
* } */
// NOLINTNEXTLINE(bugprone-exception-escape)
@Namespace("torch::nn") @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
public class MaxUnpool3dImpl extends MaxUnpool3dImplBase {
static { Loader.load(); }
public MaxUnpool3dImpl(@ByVal @Cast("torch::ExpandingArray<3>*") LongPointer kernel_size) { super((Pointer)null); allocate(kernel_size); }
@NoDeallocator private native void allocate(@ByVal @Cast("torch::ExpandingArray<3>*") LongPointer kernel_size);
public MaxUnpool3dImpl(@Const @ByRef MaxUnpool3dOptions options_) { super((Pointer)null); allocate(options_); }
@NoDeallocator private native void allocate(@Const @ByRef MaxUnpool3dOptions options_);
/** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
public MaxUnpool3dImpl(Pointer p) { super(p); }
public native @ByVal Tensor forward(@Const @ByRef Tensor input, @Const @ByRef Tensor indices,
@Const @ByRef(nullValue = "c10::optional >(c10::nullopt)") LongVectorOptional output_size);
public native @ByVal Tensor forward(@Const @ByRef Tensor input, @Const @ByRef Tensor indices);
}
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