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Niklas Gustafsson
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Adding nn.functional.normalize()
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‎RELEASENOTES.md‎

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@@ -10,8 +10,12 @@ The argument defaults for `torch.diagonal()` and `Tensor.diagonal()` arguments h
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__Bug Fixes__:
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#1400 There may be an error in torchvision.transforms.GaussianBlur
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#1402 diagonal() has incorrect default
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#1400 There may be an error in torchvision.transforms.GaussianBlur<br/>
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#1402 diagonal() has incorrect default<br/>
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__API Changes__:
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#1382: Add support for torch.nn.functional.normalize<br/>
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# NuGet Version 0.103.1
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‎TorchSharp.sln‎

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@@ -113,7 +113,6 @@ Global
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{CAD9DB7F-3223-3324-884D-FA2381593DA7}.Release|Any CPU.ActiveCfg = Release|x64
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{CAD9DB7F-3223-3324-884D-FA2381593DA7}.Release|x64.ActiveCfg = Release|x64
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{BB811429-0DF1-3D22-B664-09C2F5A9E0AB}.Debug|Any CPU.ActiveCfg = Debug|x64
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{BB811429-0DF1-3D22-B664-09C2F5A9E0AB}.Debug|Any CPU.Build.0 = Debug|x64
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{BB811429-0DF1-3D22-B664-09C2F5A9E0AB}.Debug|x64.ActiveCfg = Debug|x64
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{BB811429-0DF1-3D22-B664-09C2F5A9E0AB}.Release|Any CPU.ActiveCfg = Release|x64
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{BB811429-0DF1-3D22-B664-09C2F5A9E0AB}.Release|x64.ActiveCfg = Release|x64
@@ -150,7 +149,6 @@ Global
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{95493944-D1AE-414E-964B-B58AEAE672E5}.Release|x64.ActiveCfg = Release|Any CPU
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{95493944-D1AE-414E-964B-B58AEAE672E5}.Release|x64.Build.0 = Release|Any CPU
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{6D3CE8AA-F369-4D2D-BDA7-9F89D6BE1B2E}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{6D3CE8AA-F369-4D2D-BDA7-9F89D6BE1B2E}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{6D3CE8AA-F369-4D2D-BDA7-9F89D6BE1B2E}.Debug|x64.ActiveCfg = Debug|Any CPU
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{6D3CE8AA-F369-4D2D-BDA7-9F89D6BE1B2E}.Debug|x64.Build.0 = Debug|Any CPU
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{6D3CE8AA-F369-4D2D-BDA7-9F89D6BE1B2E}.Release|Any CPU.ActiveCfg = Release|Any CPU

‎src/Native/LibTorchSharp/THSNN.h‎

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@@ -289,6 +289,7 @@ EXPORT_API(void) THSNN_GroupNorm_set_weight(const NNModule module, const Ten
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EXPORT_API(NNModule) THSNN_LocalResponseNorm_ctor(const int64_t size, const double alpha, const double beta, const double k, NNAnyModule* outAsAnyModule);
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EXPORT_API(Tensor) THSNN_LocalResponseNorm_forward(const NNModule module, const Tensor tensor);
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EXPORT_API(Tensor) THSNN_normalize(const Tensor input, const double p, const int64_t dim, const double eps);
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EXPORT_API(Tensor) THSNN_batch_norm(const Tensor input, const Tensor running_mean, const Tensor running_var, const Tensor weight, const Tensor bias, const bool training, const double momentum, const double eps);
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EXPORT_API(Tensor) THSNN_group_norm(const Tensor input, int64_t num_groups, const Tensor weight, const Tensor bias, const double eps);
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EXPORT_API(Tensor) THSNN_instance_norm(const Tensor input, const Tensor running_mean, const Tensor running_var, const Tensor weight, const Tensor bias, const bool use_input_stats, const double momentum, const double eps);

‎src/TorchSharp/NN/Normalization/Functional.cs‎

Lines changed: 11 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -2,6 +2,7 @@
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using System;
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using static TorchSharp.PInvoke.NativeMethods;
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#nullable enable
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namespace TorchSharp
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{
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public static partial class torch
@@ -19,13 +20,18 @@ public static partial class functional
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/// <param name="eps">small value to avoid division by zero</param>
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public static Tensor normalize(Tensor input, double p = 2.0, long dim = 1L, double eps = 1e-12)
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{
22-
return null;
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var res = THSNN_normalize(
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input.Handle,
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p, dim, eps);
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if (res == IntPtr.Zero)
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torch.CheckForErrors();
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return new Tensor(res);
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}
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/// <summary>
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/// Applies Batch Normalization for each channel across a batch of data.
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/// </summary>
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public static Tensor batch_norm(Tensor input, Tensor running_mean, Tensor running_var, Tensor weight = null, Tensor bias = null, bool training = false, double momentum = 0.1, double eps = 1e-5)
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public static Tensor batch_norm(Tensor input, Tensor running_mean, Tensor running_var, Tensor? weight = null, Tensor? bias = null, bool training = false, double momentum = 0.1, double eps = 1e-5)
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{
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var res = THSNN_batch_norm(
3137
input.Handle,
@@ -43,7 +49,7 @@ public static Tensor batch_norm(Tensor input, Tensor running_mean, Tensor runnin
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/// <summary>
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/// Applies Group Normalization for last certain number of dimensions.
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/// </summary>
46-
public static Tensor group_norm(Tensor input, long num_groups, Tensor weight = null, Tensor bias = null, double eps = 1e-5)
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public static Tensor group_norm(Tensor input, long num_groups, Tensor? weight = null, Tensor? bias = null, double eps = 1e-5)
4753
{
4854
var res = THSNN_group_norm(
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input.Handle,
@@ -59,7 +65,7 @@ public static Tensor group_norm(Tensor input, long num_groups, Tensor weight = n
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/// <summary>
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/// Applies Instance Normalization for each channel in each data sample in a batch.
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/// </summary>
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public static Tensor instance_norm(Tensor input, Tensor running_mean = null, Tensor running_var = null, Tensor weight = null, Tensor bias = null, bool use_input_stats = true, double momentum = 0.1, double eps = 1e-5)
68+
public static Tensor instance_norm(Tensor input, Tensor? running_mean = null, Tensor? running_var = null, Tensor? weight = null, Tensor? bias = null, bool use_input_stats = true, double momentum = 0.1, double eps = 1e-5)
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{
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var res = THSNN_instance_norm(
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input.Handle,
@@ -77,7 +83,7 @@ public static Tensor instance_norm(Tensor input, Tensor running_mean = null, Ten
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/// <summary>
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/// Applies Layer Normalization for last certain number of dimensions.
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/// </summary>
80-
public static Tensor layer_norm(Tensor input, long[] normalized_shape, Tensor weight = null, Tensor bias = null, double eps = 1e-5)
86+
public static Tensor layer_norm(Tensor input, long[] normalized_shape, Tensor? weight = null, Tensor? bias = null, double eps = 1e-5)
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{
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IntPtr res;
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unsafe {

‎src/TorchSharp/PInvoke/LibTorchSharp.THSNN.cs‎

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@@ -851,6 +851,9 @@ internal static extern IntPtr THSNN_custom_module(
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[DllImport("LibTorchSharp")]
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internal static extern IntPtr THSNN_Unflatten_ctor(long dim, IntPtr shape, long shape_len, out IntPtr pBoxedModule);
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[DllImport("LibTorchSharp")]
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internal static extern IntPtr THSNN_normalize(IntPtr input, double p, long dim, double eps);
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[DllImport("LibTorchSharp")]
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internal static extern IntPtr THSNN_batch_norm(IntPtr input, IntPtr running_mean, IntPtr running_var, IntPtr weight, IntPtr bias, [MarshalAs(UnmanagedType.U1)] bool training, double momentum, double eps);
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‎test/TorchSharpTest/NN.cs‎

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@@ -1,4 +1,4 @@
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// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information.
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// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information.
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using System;
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using System.Linq;
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using System.Runtime.InteropServices;
@@ -4817,6 +4817,36 @@ private Tensor NormalizeTensor(Tensor x, Tensor x_mean, Tensor x_var, double eps
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return (x - x_mean) / torch.sqrt(eps + x_var);
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}
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4820+
[Fact]
4821+
public void TestNormalizeFunc()
4822+
{
4823+
foreach (var device in TestUtils.AvailableDevices()) {
4824+
var x = torch.from_array(new double[]
4825+
{ -1.0786, 0.3455, 1.2929, 0.5030,
4826+
-0.2930, 1.0420, -0.1082, -0.2943,
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-0.3989, -0.8311, 0.7103, -1.5878,
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0.6331, 1.0106, 0.5128, -2.2565,
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1.2044, -0.6916, -0.1242, 0.6808,
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0.1672, 0.1105, -1.7364, 0.0669
4831+
}).reshape(3,2,4);
4832+
var y = torch.nn.functional.normalize(x);
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Assert.Equal(x.shape, y.shape);
4834+
Assert.Equal(x.device_type, y.device_type);
4835+
4836+
var expected = torch.from_array(new double[]
4837+
{ -0.9650, 0.3147, 0.9965, 0.8631,
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-0.2621, 0.9492, -0.0834, -0.5050,
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-0.5331, -0.6352, 0.8108, -0.5755,
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0.8460, 0.7724, 0.5853, -0.8178,
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0.9905, -0.9875, -0.0713, 0.9952,
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0.1375, 0.1577, -0.9975, 0.0978
4843+
}).reshape(3, 2, 4);
4844+
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4846+
Assert.True(y.allclose(expected, rtol: 0.005, atol: 0.005));
4847+
}
4848+
}
4849+
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[Fact]
48214851
public void TestBatchNormFunc()
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{

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