[PyTorch] Update to 2.1

pytorch/README.md

@@ -9,7 +9,7 @@ Introduction
 ------------
 This directory contains the JavaCPP Presets module for:
 
- * PyTorch 2.0.1  https://pytorch.org/
+ * PyTorch 2.1.0  https://pytorch.org/
 
 Please refer to the parent README.md file for more detailed information about the JavaCPP Presets.
 
@@ -48,14 +48,14 @@ We can use [Maven 3](http://maven.apache.org/) to download and install automatic
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>pytorch-platform</artifactId>
-            <version>2.0.1-1.5.10-SNAPSHOT</version>
+            <version>2.1.0-1.5.10-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies required to use CUDA, cuDNN, and NCCL -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>pytorch-platform-gpu</artifactId>
-            <version>2.0.1-1.5.10-SNAPSHOT</version>
+            <version>2.1.0-1.5.10-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies to use bundled CUDA, cuDNN, and NCCL -->
@@ -93,9 +93,9 @@ public class SimpleMNIST {
     static class Net extends Module {
         Net() {
             // Construct and register two Linear submodules.
-            fc1 = register_module("fc1", new LinearImpl(784, 64));
-            fc2 = register_module("fc2", new LinearImpl(64, 32));
-            fc3 = register_module("fc3", new LinearImpl(32, 10));
+            register_module("fc1", fc1 = new LinearImpl(784, 64));
+            register_module("fc2", fc2 = new LinearImpl(64, 32));
+            register_module("fc3", fc3 = new LinearImpl(32, 10));
         }
 
         // Implement the Net's algorithm.
@@ -109,7 +109,7 @@ public class SimpleMNIST {
         }
 
         // Use one of many "standard library" modules.
-        LinearImpl fc1 = null, fc2 = null, fc3 = null;
+        final LinearImpl fc1, fc2, fc3;
     }
 
     public static void main(String[] args) throws Exception {

pytorch/cppbuild.sh

@@ -27,15 +27,15 @@ if [[ "$EXTENSION" == *gpu ]]; then
     export USE_CUDNN=1
     export USE_FAST_NVCC=0
     export CUDA_SEPARABLE_COMPILATION=OFF
-    export TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0+PTX"
+    export TORCH_CUDA_ARCH_LIST="5.0;6.0;7.0;8.0;9.0"
 fi
 
 export PYTHON_BIN_PATH=$(which python3)
 if [[ $PLATFORM == windows* ]]; then
     export PYTHON_BIN_PATH=$(which python.exe)
 fi
 
-PYTORCH_VERSION=2.0.1
+PYTORCH_VERSION=2.1.0
 
 mkdir -p "$PLATFORM$EXTENSION"
 cd "$PLATFORM$EXTENSION"

pytorch/include_list.pl

@@ -0,0 +1,65 @@
+#!/bin/perl
+
+# Must be run at from javacpp-presets/pytorch after cppbuild.sh has been run 
+# for linux-x86_64-gpu
+
+# Generate the lists of includes to parse, in order, from the output
+# of g++ -H
+# Used to update src/main/resources/org/bytedeco/pytorch/presets/*
+
+use strict;
+use warnings;
+
+my %incs;
+my @inc_per_depth;
+
+sub flush($) {
+    my $min_depth = shift;
+    for (my $d = @inc_per_depth - 1; $d >= $min_depth; $d--) {
+        if ($inc_per_depth[$d]) {
+            foreach my $i (@{$inc_per_depth[$d]}) {
+                print "#include \"$i\"\n";
+                $incs{$i} = 1;
+            }
+            undef $inc_per_depth[$d];
+        }
+    }
+}
+
+sub go {
+    my $path = join ' ', @_;
+
+    my @inc = `g++ -I torch/csrc/api/include/ -I. -H $path -E 2>&1 > /dev/null`;
+    foreach my $i (@inc) {
+        chomp $i;
+        my ($depth, $f) = $i =~ /^(\.+)\s(.*\.h)$/;
+        next unless $depth;
+        $depth = length($depth);
+        $f =~ s#^\./##;
+        next if $f =~ m#^/
+  |^ATen/ops/\w+_native\.h$
+  |^ATen/ops/\w+_meta\.h$
+  |^ATen/ops/\w+_ops\.h$
+  |^ATen/ops/_\w+\.h$#x
+            or $incs{$f};
+        flush($depth);
+        my $incs = $inc_per_depth[$depth];
+        $incs = $inc_per_depth[$depth] = [] unless $incs;
+        push @$incs, $f;
+    }
+    flush(0);
+}
+
+chdir "cppbuild/linux-x86_64-gpu/pytorch/torch/include";
+
+go('torch/csrc/api/include/torch/torch.h', 'torch/script.h');
+
+print <<EOF;
+
+// Included by
+// ATen/cudnn/Descriptors.h
+// ATen/cudnn/Types.h
+// c10/cuda/CUDAGuard.h
+EOF
+
+go('ATen/cudnn/Descriptors.h', 'ATen/cudnn/Types.h', 'c10/cuda/CUDAGuard.h', '-I/opt/cuda/targets/x86_64-linux/include/');

pytorch/platform/gpu/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>pytorch-platform-gpu</artifactId>
-  <version>2.0.1-${project.parent.version}</version>
+  <version>2.1.0-${project.parent.version}</version>
   <name>JavaCPP Presets Platform GPU for PyTorch</name>
 
   <properties>

pytorch/platform/pom.xml

@@ -12,7 +12,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>pytorch-platform</artifactId>
-  <version>2.0.1-${project.parent.version}</version>
+  <version>2.1.0-${project.parent.version}</version>
   <name>JavaCPP Presets Platform for PyTorch</name>
 
   <properties>

pytorch/pom.xml

@@ -11,7 +11,7 @@
 
   <groupId>org.bytedeco</groupId>
   <artifactId>pytorch</artifactId>
-  <version>2.0.1-${project.parent.version}</version>
+  <version>2.1.0-${project.parent.version}</version>
   <name>JavaCPP Presets for PyTorch</name>
 
   <dependencies>

pytorch/samples/pom.xml

@@ -12,14 +12,14 @@
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>pytorch-platform</artifactId>
-            <version>2.0.1-1.5.10-SNAPSHOT</version>
+            <version>2.1.0-1.5.10-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies required to use CUDA, cuDNN, and NCCL -->
         <dependency>
             <groupId>org.bytedeco</groupId>
             <artifactId>pytorch-platform-gpu</artifactId>
-            <version>2.0.1-1.5.10-SNAPSHOT</version>
+            <version>2.1.0-1.5.10-SNAPSHOT</version>
         </dependency>
 
         <!-- Additional dependencies to use bundled CUDA, cuDNN, and NCCL -->

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

@@ -52,7 +52,7 @@ public class Allocator extends Pointer {
   // is guaranteed to return a unique_ptr with this deleter attached;
   // it means the rawAllocate and rawDeallocate APIs are safe to use.
   // This function MUST always return the same BoundDeleter.
-  public native @Cast("c10::DeleterFnPtr") PointerConsumer raw_deleter();
+  public native PointerConsumer raw_deleter();
   public native Pointer raw_allocate(@Cast("size_t") long n);
   public native void raw_deallocate(Pointer ptr);
 }

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

@@ -227,6 +227,8 @@ public class AnyModule extends Pointer {
   private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::ReplicationPad1dImpl>"}) ReplicationPad1dImpl module);
   public AnyModule(ConstantPad1dImpl module) { super((Pointer)null); allocate(module); }
   private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::ConstantPad1dImpl>"}) ConstantPad1dImpl module);
+  public AnyModule(ZeroPad1dImpl module) { super((Pointer)null); allocate(module); }
+  private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::ZeroPad1dImpl>"}) ZeroPad1dImpl module);
   public AnyModule(AvgPool1dImpl module) { super((Pointer)null); allocate(module); }
   private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::AvgPool1dImpl>"}) AvgPool1dImpl module);
   public AnyModule(MaxPool1dImpl module) { super((Pointer)null); allocate(module); }
@@ -267,6 +269,8 @@ public class AnyModule extends Pointer {
   private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::ReplicationPad3dImpl>"}) ReplicationPad3dImpl module);
   public AnyModule(ConstantPad3dImpl module) { super((Pointer)null); allocate(module); }
   private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::ConstantPad3dImpl>"}) ConstantPad3dImpl module);
+  public AnyModule(ZeroPad3dImpl module) { super((Pointer)null); allocate(module); }
+  private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::ZeroPad3dImpl>"}) ZeroPad3dImpl module);
   public AnyModule(AvgPool3dImpl module) { super((Pointer)null); allocate(module); }
   private native void allocate(@SharedPtr @Cast({"", "std::shared_ptr<torch::nn::AvgPool3dImpl>"}) AvgPool3dImpl module);
   public AnyModule(MaxPool3dImpl module) { super((Pointer)null); allocate(module); }

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

@@ -38,18 +38,10 @@ public class ArgumentDef extends Pointer {
         return new ArgumentDef((Pointer)this).offsetAddress(i);
     }
 
-  public static class GetTypeFn extends FunctionPointer {
-      static { Loader.load(); }
-      /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
-      public    GetTypeFn(Pointer p) { super(p); }
-      protected GetTypeFn() { allocate(); }
-      private native void allocate();
-      public native @ByVal Type.TypePtr call();
-  }
-  public native GetTypeFn getTypeFn(); public native ArgumentDef getTypeFn(GetTypeFn setter);
-  public native GetTypeFn getFakeTypeFn(); public native ArgumentDef getFakeTypeFn(GetTypeFn setter);
+  public native TypeSupplier getTypeFn(); public native ArgumentDef getTypeFn(TypeSupplier setter);
+  public native TypeSupplier getFakeTypeFn(); public native ArgumentDef getFakeTypeFn(TypeSupplier setter);
   public ArgumentDef() { super((Pointer)null); allocate(); }
   private native void allocate();
-  public ArgumentDef(GetTypeFn getTypeFn, GetTypeFn getFakeTypeFn) { super((Pointer)null); allocate(getTypeFn, getFakeTypeFn); }
-  private native void allocate(GetTypeFn getTypeFn, GetTypeFn getFakeTypeFn);
+  public ArgumentDef(TypeSupplier getTypeFn, TypeSupplier getFakeTypeFn) { super((Pointer)null); allocate(getTypeFn, getFakeTypeFn); }
+  private native void allocate(TypeSupplier getTypeFn, TypeSupplier getFakeTypeFn);
 }

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

@@ -71,6 +71,12 @@ public class AutogradMeta extends AutogradMetaInterface {
 
 
 
+  // The post_acc_grad_hooks_ field stores only Python hooks
+  // (PyFunctionTensorPostAccGradHooks) that are called after the
+  // .grad field has been accumulated into. This is less complicated
+  // than the hooks_ field, which encapsulates a lot more.
+  public native @UniquePtr @Cast({"", "", "std::unique_ptr<torch::autograd::PostAccumulateGradHook>&&"}) PostAccumulateGradHook post_acc_grad_hooks_(); public native AutogradMeta post_acc_grad_hooks_(PostAccumulateGradHook setter);
+
   // Only meaningful on leaf variables (must be false otherwise)
   public native @Cast("bool") boolean requires_grad_(); public native AutogradMeta requires_grad_(boolean setter);
 

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

@@ -46,7 +46,7 @@ private native void allocate(
 
   public native void set_inference_mode(@Cast("bool") boolean enabled);
 
-  public native void set_multithreading_enabled(@Cast("bool") boolean mulithreading_enabled);
+  public native void set_multithreading_enabled(@Cast("bool") boolean multithreading_enabled);
 
   public native void set_view_replay_enabled(@Cast("bool") boolean view_replay_enabled);
 

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

@@ -0,0 +1,49 @@
+// Targeted by JavaCPP version 1.5.10-SNAPSHOT: DO NOT EDIT THIS FILE
+
+package org.bytedeco.pytorch;
+
+import org.bytedeco.pytorch.Allocator;
+import org.bytedeco.pytorch.Function;
+import org.bytedeco.pytorch.functions.*;
+import org.bytedeco.pytorch.Module;
+import org.bytedeco.javacpp.annotation.Cast;
+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.*;
+
+
+// For ease of copy pasting
+// #if 0
+// #endif
+
+/**
+ * This structure is intended to hold additional metadata of the specific device
+ * backend.
+ **/
+@Namespace("c10") @Properties(inherit = org.bytedeco.pytorch.presets.torch.class)
+public class BackendMeta extends Pointer {
+    static { Loader.load(); }
+    /** Default native constructor. */
+    public BackendMeta() { super((Pointer)null); allocate(); }
+    /** Native array allocator. Access with {@link Pointer#position(long)}. */
+    public BackendMeta(long size) { super((Pointer)null); allocateArray(size); }
+    /** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
+    public BackendMeta(Pointer p) { super(p); }
+    private native void allocate();
+    private native void allocateArray(long size);
+    @Override public BackendMeta position(long position) {
+        return (BackendMeta)super.position(position);
+    }
+    @Override public BackendMeta getPointer(long i) {
+        return new BackendMeta((Pointer)this).offsetAddress(i);
+    }
+
+  public native @ByVal BackendMetaRef clone(
+        @Const @ByRef BackendMetaRef ptr);
+}