From 94169b01f2592e6237ab75a1f8aca1b40d29c6de Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Fri, 1 Jul 2022 14:13:47 -0700 Subject: [PATCH 01/12] First batch of work on torch.jit. --- RELEASENOTES.md | 1 + src/Native/LibTorchSharp/THSJIT.cpp | 186 ++++++++-- src/Native/LibTorchSharp/THSJIT.h | 56 ++- src/Native/LibTorchSharp/THSLinearAlgebra.cpp | 5 + src/Native/LibTorchSharp/THSTensor.h | 2 + src/Native/LibTorchSharp/Utils.h | 2 + src/TorchSharp/JIT/Module.cs | 154 -------- src/TorchSharp/JIT/ScriptModule.cs | 328 ++++++++++++++++++ src/TorchSharp/JIT/Type/DynamicType .cs | 27 +- src/TorchSharp/JIT/Type/TensorType.cs | 113 +++--- src/TorchSharp/JIT/Type/Type.cs | 231 ++++++------ src/TorchSharp/NN/Module.cs | 40 ++- src/TorchSharp/Tensor/Tensor.LinearAlgebra.cs | 9 + src/TorchSharp/Tensor/Tensor.cs | 16 + .../TorchSharpTest.WithCudaBinaries.csproj | 12 + test/TorchSharpTest/TestLoadSave.cs | 59 ++++ test/TorchSharpTest/TestTraining.cs | 22 +- test/TorchSharpTest/TorchSharpTest.csproj | 9 + test/TorchSharpTest/l1000_100_10.script.dat | Bin 0 -> 411032 bytes test/TorchSharpTest/linrelu.script.dat | Bin 0 -> 4432 bytes 20 files changed, 892 insertions(+), 380 deletions(-) delete mode 100644 src/TorchSharp/JIT/Module.cs create mode 100644 src/TorchSharp/JIT/ScriptModule.cs create mode 100644 test/TorchSharpTest/l1000_100_10.script.dat create mode 100644 test/TorchSharpTest/linrelu.script.dat diff --git a/RELEASENOTES.md b/RELEASENOTES.md index 20d05f526..a163115f5 100644 --- a/RELEASENOTES.md +++ b/RELEASENOTES.md @@ -10,6 +10,7 @@ __API Changes__: Add torch.utils.rnn
Add torchvision.io
+Add Tensor.trace() and torch.trace()
## NuGet Version 0.96.8 diff --git a/src/Native/LibTorchSharp/THSJIT.cpp b/src/Native/LibTorchSharp/THSJIT.cpp index 11531aef3..050dabfb0 100644 --- a/src/Native/LibTorchSharp/THSJIT.cpp +++ b/src/Native/LibTorchSharp/THSJIT.cpp @@ -3,9 +3,37 @@ JITModule THSJIT_load(const char* filename) { - auto res = torch::jit::load(filename); - auto copy = new torch::jit::Module(res); - return new std::shared_ptr(copy); + auto res = torch::jit::load(filename); + auto copy = new torch::jit::Module(res); + return new std::shared_ptr(copy); +} + +int THSJIT_Module_is_training(JITModule module) +{ + return (*module)->is_training(); +} + +void THSJIT_Module_train(JITModule module) +{ + (*module)->train(); +} + +void THSJIT_Module_eval(JITModule module) +{ + (*module)->eval(); +} + +void THSJIT_Module_to_device(JITModule module, int64_t device, int64_t index) +{ + c10::DeviceType dev = c10::kCPU; + if (device == 1) + dev = c10::kCUDA; + (*module)->to(torch::Device(dev, index)); +} + +void THSJIT_Module_to_dtype(JITModule module, int8_t dtype) +{ + (*module)->to((at::ScalarType)dtype); } void THSJIT_Module_modules(const JITModule module, JITModule* (*allocator)(size_t length)) @@ -35,6 +63,22 @@ void THSJIT_Module_named_modules(const JITModule module, } } +void THSJIT_Module_named_children(const JITModule module, + JITModule* (*allocator)(size_t length), + const char** (*allocator2)(size_t length)) +{ + auto modules = (*module)->named_children(); + JITModule* result = allocator(modules.size()); + const char** names = allocator2(modules.size()); + int i = 0; + for (const auto& child : modules) { + auto copy = new torch::jit::Module(child.value); + result[i] = new std::shared_ptr(copy); + names[i] = make_sharable_string(child.name); + i++; + } +} + void THSJIT_Module_parameters(const JITModule module, Tensor* (*allocator)(size_t length)) { auto parameters = (*module)->parameters(); @@ -60,6 +104,21 @@ void THSJIT_Module_named_parameters(const JITModule module, } } +void THSJIT_Module_named_buffers(const JITModule module, + Tensor* (*allocator)(size_t length), + const char** (*allocator2)(size_t length)) +{ + auto parameters = (*module)->named_buffers(); + Tensor* result = allocator(parameters.size()); + const char** names = allocator2(parameters.size()); + int i = 0; + for (const auto& child : parameters) { + result[i] = new torch::Tensor(child.value); + names[i] = make_sharable_string(child.name); + i++; + } +} + JITMethod THSJIT_Module_get_method(const JITModule module, const char* name) { auto method = (*module)->get_method(name); @@ -69,7 +128,7 @@ JITMethod THSJIT_Module_get_method(const JITModule module, const char* name) Tensor THSJIT_Module_forward(const JITModule module, const Tensor* tensorPtrs, const int length) { - return new torch::Tensor((*module)->forward(toTensors((torch::Tensor**)tensorPtrs, length)).toTensor()); + CATCH_TENSOR((*module)->forward(toTensors((torch::Tensor**)tensorPtrs, length)).toTensor()); } void THSJIT_Module_dispose(const JITModule module) @@ -87,6 +146,16 @@ int THSJIT_Method_num_inputs(const JITMethod method) return (int)(*method)->num_inputs(); } +int THSJIT_Module_num_inputs(const JITModule module) +{ + return (int)(*module)->get_method("forward").num_inputs()-1; // Don't count the 'self' argument. +} + +int THSJIT_Module_num_outputs(const JITModule module) +{ + return (int)(*module)->get_method("forward").function().getSchema().returns().size(); +} + JITFunction THSJIT_Method_function(const JITMethod method) { return new std::shared_ptr(&(*method)->function()); @@ -113,32 +182,77 @@ void THSJIT_Function_dispose(const JITFunction function) delete function; } -//void* THSJIT_typeCast(const JITType type) -//{ -// switch ((*type)->kind()) -// { -// case c10::TypeKind::TensorType: -// return new std::shared_ptr((*type)->cast()); -// case c10::TypeKind::DimensionedTensorType: -// return new std::shared_ptr((*type)->cast()); -// default: -// return NULL; -// } -//} -// -//int8_t THSJIT_typeKind(const JITType type) -//{ -// switch ((*type)->kind()) -// { -// case c10::TypeKind::TensorType: -// return (int8_t)TypeKind::TensorType; -// case c10::TypeKind::DimensionedTensorType: -// return (int8_t)TypeKind::DimensionedTensorType; -// default: -// return -1; -// } -//} -// +void THSJIT_Type_dispose(const JITType type) +{ + delete type; +} + +void THSJIT_TensorType_dispose(const JITTensorType type) +{ + delete type; +} + +void* THSJIT_Type_cast(const JITType type) +{ + switch ((*type)->kind()) + { + case c10::TypeKind::TensorType: + return new std::shared_ptr((*type)->cast()); + //case c10::TypeKind::DimensionedTensorType: + // return new std::shared_ptr((*type)->cast()); + default: + return NULL; + } +} + +int8_t THSJIT_TensorType_dtype(const JITTensorType type) +{ + auto scT = (*type)->scalarType(); + if (scT.has_value()) { + return (int8_t)scT.value(); + } + else { + return -1; + } +} + +void THSJIT_TensorType_sizes(const JITTensorType type, int64_t* (*allocator)(int64_t length)) +{ + //CATCH( + auto& t = *type; + auto dim = t->dim(); + auto res = (*type)->sizes().concrete_sizes(); + if (res.has_value()) { + const size_t sz = res.value().size(); + auto& vec = res.value(); + int64_t * result = allocator(sz); + for (size_t i = 0; i < sz; i++) + result[i] = vec[i]; + } + //); +} + +int8_t THSJIT_Type_kind(const JITType type) +{ + switch ((*type)->kind()) + { + case c10::TypeKind::TensorType: + return (int8_t)TypeKind::TensorType; + //case c10::TypeKind::DimensionedTensorType: + // return (int8_t)TypeKind::DimensionedTensorType; + default: + return -1; + } +} + +JITType THSJIT_Module_getInputType(JITModule module, int8_t index) +{ + auto typ = (*module)->type(); + c10::TypeKind kind = typ->kind(); + auto& schema = typ->getMethod("forward").getSchema(); + return new std::shared_ptr(schema.arguments()[1 + index].type()->cast()); +} + //int8_t THSJIT_getScalarFromDimensionedTensorType(const JITDimensionedTensorType type) //{ // return (int8_t)(*type)->scalarType(); @@ -159,10 +273,10 @@ void THSJIT_Function_dispose(const JITFunction function) // // return make_sharable_string(device_type); //} -// -// -//void THSJIT_typeDispose(const JITType type) -//{ -// delete type; -//} \ No newline at end of file + + +void THSJIT_typeDispose(const JITType type) +{ + delete type; +} \ No newline at end of file diff --git a/src/Native/LibTorchSharp/THSJIT.h b/src/Native/LibTorchSharp/THSJIT.h index 0f1926f41..e4232b616 100644 --- a/src/Native/LibTorchSharp/THSJIT.h +++ b/src/Native/LibTorchSharp/THSJIT.h @@ -7,38 +7,64 @@ #include "Utils.h" -//// Copied from libtorch to share the type as an int8_t. -//enum TypeKind : int8_t { -//#define DEFINE_TYPE(T) T, -// C10_FORALL_TYPES(DEFINE_TYPE) -//#undef DEFINE_TYPE -//}; -// -//// API. +// Copied from libtorch to share the type as an int8_t. +enum TypeKind : int8_t { +#define DEFINE_TYPE(T) T, + C10_FORALL_TYPES(DEFINE_TYPE) +#undef DEFINE_TYPE +}; + +// API. EXPORT_API(JITModule) THSJIT_load(const char* filename); +EXPORT_API(void) THSJIT_Module_dispose(const JITModule module); -EXPORT_API(void) THSJIT_Module_modules(const JITModule module, JITModule* (*allocator)(size_t length)); +EXPORT_API(int) THSJIT_Module_num_inputs(const JITModule method); +EXPORT_API(int) THSJIT_Module_num_outputs(const JITModule method); + +EXPORT_API(Tensor) THSJIT_Module_forward(const JITModule module, const Tensor* tensorPtrs, const int length); + +EXPORT_API(int) THSJIT_Module_is_training(JITModule module); +EXPORT_API(void) THSJIT_Module_train(JITModule module); +EXPORT_API(void) THSJIT_Module_eval(JITModule module); + +EXPORT_API(void) THSJIT_Module_to_device(JITModule module, int64_t device, int64_t index); +EXPORT_API(void) THSJIT_Module_to_dtype(JITModule module, int8_t dtype); +EXPORT_API(JITType) THSJIT_Module_getInputType(JITModule module, int8_t dtype); + +EXPORT_API(int8_t) THSJIT_Type_kind(JITType handle); +EXPORT_API(void*) THSJIT_Type_cast(const JITType type); + +EXPORT_API(int8_t) THSJIT_TensorType_dtype(const JITTensorType type); +EXPORT_API(void) THSJIT_TensorType_sizes(const JITTensorType type, int64_t* (*allocator)(int64_t length)); + +EXPORT_API(void) THSJIT_Type_dispose(const JITType type); +EXPORT_API(void) THSJIT_TensorType_dispose(const JITTensorType type); + +EXPORT_API(void) THSJIT_Module_modules(const JITModule module, JITModule* (*allocator)(size_t length)); EXPORT_API(void) THSJIT_Module_named_modules(const JITModule module, JITModule* (*allocator)(size_t length), const char** (*allocator2)(size_t length)); +EXPORT_API(void) THSJIT_Module_named_children(const JITModule module, + JITModule* (*allocator)(size_t length), + const char** (*allocator2)(size_t length)); + EXPORT_API(JITMethod) THSJIT_Module_get_method(const JITModule module, const char* name); EXPORT_API(void) THSJIT_Module_parameters(const JITModule module, Tensor* (*allocator)(size_t length)); - EXPORT_API(void) THSJIT_Module_named_parameters(const JITModule module, Tensor* (*allocator)(size_t length), const char** (*allocator2)(size_t length)); -EXPORT_API(Tensor) THSJIT_Module_forward(const JITModule module, const Tensor* tensorPtrs, const int length); - -EXPORT_API(void) THSJIT_Module_dispose(const JITModule module); - -EXPORT_API(const char*) THSJIT_Method_name(const JITMethod method); +EXPORT_API(void) THSJIT_Module_named_buffers(const JITModule module, + Tensor* (*allocator)(size_t length), + const char** (*allocator2)(size_t length)); EXPORT_API(int) THSJIT_Method_num_inputs(const JITMethod method); EXPORT_API(void) THSJIT_Method_dispose(const JITMethod method); + +EXPORT_API(const char*) THSJIT_Method_name(const JITMethod method); diff --git a/src/Native/LibTorchSharp/THSLinearAlgebra.cpp b/src/Native/LibTorchSharp/THSLinearAlgebra.cpp index d9539033b..861cbedcb 100644 --- a/src/Native/LibTorchSharp/THSLinearAlgebra.cpp +++ b/src/Native/LibTorchSharp/THSLinearAlgebra.cpp @@ -293,6 +293,11 @@ Tensor THSTensor_diag(const Tensor tensor, const int64_t diagonal) CATCH_TENSOR(tensor->diag(diagonal)); } +Tensor THSTensor_trace(const Tensor tensor) +{ + CATCH_TENSOR(tensor->trace()); +} + Tensor THSTensor_diagflat(const Tensor tensor, const int64_t offset) { CATCH_TENSOR(tensor->diagflat(offset)); diff --git a/src/Native/LibTorchSharp/THSTensor.h b/src/Native/LibTorchSharp/THSTensor.h index 7b034fac2..1e00105db 100644 --- a/src/Native/LibTorchSharp/THSTensor.h +++ b/src/Native/LibTorchSharp/THSTensor.h @@ -358,6 +358,8 @@ EXPORT_API(int) THSTensor_device_index(const Tensor tensor); EXPORT_API(Tensor) THSTensor_diag(const Tensor tensor, const int64_t diagonal); +EXPORT_API(Tensor) THSTensor_trace(const Tensor tensor); + EXPORT_API(Tensor) THSTensor_diagflat(const Tensor tensor, const int64_t offset); EXPORT_API(Tensor) THSTensor_diagonal(const Tensor tensor, const int64_t offset, const int64_t dim1, const int64_t dim2); diff --git a/src/Native/LibTorchSharp/Utils.h b/src/Native/LibTorchSharp/Utils.h index b399f4640..bbad85e41 100644 --- a/src/Native/LibTorchSharp/Utils.h +++ b/src/Native/LibTorchSharp/Utils.h @@ -20,6 +20,8 @@ typedef std::shared_ptr * JITModule; typedef std::shared_ptr* JITMethod; typedef std::shared_ptr * JITFunction; typedef std::shared_ptr * JITType; +typedef std::shared_ptr* JITTensorType; + //typedef std::shared_ptr* JITDimensionedTensorType; #define THS_API TH_API diff --git a/src/TorchSharp/JIT/Module.cs b/src/TorchSharp/JIT/Module.cs deleted file mode 100644 index d9e63b46f..000000000 --- a/src/TorchSharp/JIT/Module.cs +++ /dev/null @@ -1,154 +0,0 @@ -//// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. -//using System; -//using System.Linq; -//using System.Runtime.InteropServices; -//using static TorchSharp.torch; - -//namespace TorchSharp.JIT -//{ -// public class Module : IDisposable -// { -// /// -// /// Class wrapping PyTorch's module object reference. -// /// -// internal sealed class HType : SafeHandle -// { -// public HType(IntPtr preexistingHandle, bool ownsHandle) : base(IntPtr.Zero, ownsHandle) -// { -// SetHandle(preexistingHandle); -// } - -// public override bool IsInvalid => handle == IntPtr.Zero; - -// // This is just for marshalling -// internal HType() : base(IntPtr.Zero, true) -// { -// } - -// [DllImport("LibTorchSharp")] -// private static extern void THSJIT_moduleDispose(HType handle); - -// protected override bool ReleaseHandle() -// { -// THSJIT_moduleDispose(this); -// return true; -// } - -// protected override void Dispose(bool disposing) -// { -// if (disposing) -// { -// ReleaseHandle(); -// } -// } -// } - -// internal HType handle; - -// internal Module(IntPtr handle) -// { -// this.handle = new HType(handle, true); -// } - -// ~Module() -// { -// Dispose(false); -// } - -// /// -// /// Releases the storage. -// /// -// public void Dispose() -// { -// Dispose(true); -// GC.SuppressFinalize(this); -// } - -// /// -// /// Implements the .NET Dispose pattern. -// /// -// protected void Dispose(bool disposing) -// { -// if (disposing) -// { -// handle.Dispose(); -// handle.SetHandleAsInvalid(); -// } -// } - -// [DllImport("LibTorchSharp")] -// private static extern IntPtr THSJIT_loadModule(string filename); - -// static public Module Load(string filename) -// { -// return new Module(THSJIT_loadModule(filename)); -// } - -// [DllImport("LibTorchSharp")] -// private static extern long THSJIT_getNumModules(HType module); - -// [DllImport("LibTorchSharp")] -// private static extern int THSJIT_getNumberOfInputs(HType module); - -// public int GetNumberOfInputs() -// { -// return THSJIT_getNumberOfInputs(handle); -// } - -// [DllImport("LibTorchSharp")] -// private static extern int THSJIT_getNumberOfOutputs(HType module); - -// public int GetNumberOfOutputs() -// { -// return THSJIT_getNumberOfOutputs(handle); -// } - -// [DllImport("LibTorchSharp")] -// private static extern IntPtr THSJIT_getInputType(HType module, int index); - -// public Type GetInputType(int index) -// { -// var type = new Type(THSJIT_getInputType(handle, index)); - -// return GetType(type); -// } - -// [DllImport("LibTorchSharp")] -// private static extern IntPtr THSJIT_getOutputType(HType module, int index); - -// public Type GetOutputType(int index) -// { -// var type = new Type(THSJIT_getOutputType(handle, index)); - -// return GetType(type); -// } - -// private Type GetType(Type type) -// { -// switch (type.Kind) -// { -// case Type.TypeKind.TensorType: -// var dynamic = type.AsDynamicType(); -// type.Dispose(); -// return dynamic; -// case Type.TypeKind.DimensionedTensorType: -// var tensor = type.AsTensorType(); -// type.Dispose(); -// return tensor; -// default: -// return type; -// } -// } - -// [DllImport("LibTorchSharp")] -// private static extern IntPtr THSJIT_forward(torch.nn.Module.HType module, IntPtr tensors, int length); - -// public Tensor forward(params Tensor[] tensors) -// { -// var parray = new PinnedArray(); -// IntPtr tensorRefs = parray.CreateArray(tensors.Select(p => p.Handle).ToArray()); - -// return new Tensor(THSJIT_forward(handle, tensorRefs, parray.Array.Length)); -// } -// } -//} diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs new file mode 100644 index 000000000..beaba63c3 --- /dev/null +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -0,0 +1,328 @@ +// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. +using System; +using System.Linq; +using System.Collections.Generic; +using System.Diagnostics; +using System.Reflection; +using System.Runtime.InteropServices; +using static TorchSharp.torch; + +namespace TorchSharp +{ + public static partial class jit + { + public class ScriptModule : torch.nn.Module + { + internal ScriptModule(IntPtr handle) : base(new HType(handle, true), null) + { + } + + ~ScriptModule() + { + Dispose(false); + } + + /// + /// Implements the .NET Dispose pattern. + /// + protected override void Dispose(bool disposing) + { + if (disposing && !handle.IsInvalid) { + + //foreach (var (_, p) in named_buffers(false)) { + // p.Dispose(); + //} + //foreach (var (_, b) in named_parameters(false)) { + // b.Dispose(); + //} + + //foreach (var (_, m) in named_modules()) { + // m.Dispose(); + //} + + handle.Dispose(); + handle.SetHandleAsInvalid(); + boxedModule?.Dispose(); + } + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_parameters(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + + protected override (string name, TorchSharp.Modules.Parameter parameter)[] _named_parameters() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_parameters(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; + + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new TorchSharp.Modules.Parameter(x))).ToArray(); + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_buffers(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + + protected override (string name, Tensor buffer)[] _named_buffers() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_buffers(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; + + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new Tensor(x))).ToArray(); + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_modules(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + + public override IEnumerable<(string name, nn.Module module)> named_modules() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_modules(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; + + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)); + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_children(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + + public override IEnumerable<(string name, nn.Module module)> named_children() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_children(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; + + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)); + } + + [DllImport("LibTorchSharp")] + private static extern long THSJIT_getNumModules(HType module); + + [DllImport("LibTorchSharp")] + private static extern int THSJIT_Module_num_inputs(HType module); + + public int GetNumberOfInputs() + { + return THSJIT_Module_num_inputs(handle); + } + + [DllImport("LibTorchSharp")] + private static extern int THSJIT_Module_num_outputs(HType module); + + public int GetNumberOfOutputs() + { + return THSJIT_Module_num_outputs(handle); + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_train(HType module); + + public override void train() + { + THSJIT_Module_train(handle); + CheckForErrors(); + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_eval(HType module); + + public override void eval() + { + THSJIT_Module_eval(handle); + CheckForErrors(); + } + + [DllImport("LibTorchSharp")] + private static extern bool THSJIT_Module_is_training(HType module); + + public override bool training { + get { + var res = THSJIT_Module_is_training(handle); + CheckForErrors(); + return res; + } + } + + [DllImport("LibTorchSharp")] + static extern void THSJIT_Module_to_device(HType module, long deviceType, long deviceIndex); + + [DllImport("LibTorchSharp")] + static extern void THSJIT_Module_to_dtype(HType module, sbyte dtype); + + /// + /// Moves the parameters and buffers. + /// + /// The device type, e.g. 'CPU' or 'CUDA'. + /// The optional device index. + /// + public override nn.Module to(DeviceType deviceType, int deviceIndex = -1) + { + if (deviceType != DeviceType.CUDA) deviceIndex = -1; + + if (deviceType == DeviceType.CUDA && !torch.cuda.is_available()) throw new InvalidOperationException("CUDA is not available."); + + if (deviceType != _deviceType || deviceIndex != _deviceIndex) { + + InitializeDeviceType(deviceType); + THSJIT_Module_to_device(handle, (int)deviceType, deviceIndex); + CheckForErrors(); + + foreach (var (_, sm) in named_children()) sm.to(deviceType, deviceIndex); + + foreach (var field in GetType().GetFields(BindingFlags.NonPublic | BindingFlags.Public | BindingFlags.Instance)) { + + var fieldName = field.Name; + var value = field.GetValue(this); + + switch (value) { + // This test must come before the Tensor test + case Modules.Parameter param when deviceType == param.device_type && deviceIndex == param.device_index: + continue; + + case Modules.Parameter param: { + var t = param.to(deviceType, deviceIndex); + t.retain_grad(); + var p = new Modules.Parameter(t, param.requires_grad); + field.SetValue(this, p); + ConditionallyRegisterParameter(fieldName, p); + break; + } + + case Tensor tensor when (deviceType != tensor.device_type || deviceIndex != tensor.device_index): { + var t = tensor.to(deviceType, deviceIndex); + field.SetValue(this, t); + ConditionallyRegisterBuffer(fieldName, t); + break; + } + } + } + + _deviceType = deviceType; + _deviceIndex = deviceIndex; + } + + Debug.Assert(_deviceType == DeviceType.CUDA || _deviceIndex == -1); + + return this; + } + + private DeviceType _deviceType = DeviceType.CPU; + private int _deviceIndex = -1; + + /// + /// Convert the parameters and buffers. + /// + /// + public override nn.Module to(ScalarType dtype) + { + THSJIT_Module_to_dtype(handle, (sbyte)dtype); + CheckForErrors(); + + foreach (var (_, sm) in named_children()) sm.to(dtype); + foreach (var field in GetType().GetFields(BindingFlags.NonPublic | BindingFlags.Public | BindingFlags.Instance)) { + + var fieldName = field.Name; + var value = field.GetValue(this); + + switch (value) { + // This test must come before the Tensor test + case Modules.Parameter param when dtype == param.dtype: + continue; + + case Modules.Parameter param: { + var t = param.to(dtype); + t.retain_grad(); + var p = new Modules.Parameter(t, param.requires_grad); + field.SetValue(this, p); + ConditionallyRegisterParameter(fieldName, p); + break; + } + + case Tensor tensor when dtype == tensor.dtype: + continue; + + case Tensor tensor: { + var t = tensor.to(dtype); + field.SetValue(this, t); + ConditionallyRegisterBuffer(fieldName, t); + break; + } + } + } + + return this; + } + +#if false // These functions "work," but the native code doesn't seem to find any interesting information. + + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_Module_getInputType(HType module, int index); + + public Type GetInputType(int index) + { + var type = new Type(THSJIT_Module_getInputType(handle, index), Type.TypeKind.AnyType); + + return GetType(type); + } + + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_getOutputType(HType module, int index); + + public Type GetOutputType(int index) + { + var type = new Type(THSJIT_getOutputType(handle, index), Type.TypeKind.AnyType); + + return GetType(type); + } + + private Type GetType(Type type) + { + switch (type.Kind) { + case Type.TypeKind.TensorType: + var dynamic = type.AsTensorType(); + type.Dispose(); + return dynamic; + //case Type.TypeKind.DimensionedTensorType: + // var tensor = type.AsTensorType(); + // type.Dispose(); + // return tensor; + default: + return type; + } + } +#endif + + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_Module_forward(HType module, IntPtr tensors, int length); + + public unsafe override Tensor forward(Tensor tensor) + { + using (var parray = new PinnedArray()) { + IntPtr tensorRefs = parray.CreateArray(new [] { tensor.Handle }); + return new Tensor(THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length)); + } + } + } + + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_load(string filename); + + public static ScriptModule load(string filename) + { + return new ScriptModule(THSJIT_load(filename)); + } + + + } +} diff --git a/src/TorchSharp/JIT/Type/DynamicType .cs b/src/TorchSharp/JIT/Type/DynamicType .cs index 440d3532c..c345b2337 100644 --- a/src/TorchSharp/JIT/Type/DynamicType .cs +++ b/src/TorchSharp/JIT/Type/DynamicType .cs @@ -1,13 +1,16 @@ -//// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. -//using System; +// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. +using System; -//namespace TorchSharp.JIT -//{ -// public sealed class DynamicType : Type -// { -// internal DynamicType(IntPtr handle) : base(handle) -// { -// this.handle = new HType(handle, true); -// } -// } -//} +namespace TorchSharp +{ + public static partial class jit + { + public sealed class DynamicType : Type + { + internal DynamicType(IntPtr handle) : base(handle, Type.TypeKind.AnyType) + { + this.handle = new HType(handle, true, Type.TypeKind.AnyType); + } + } + } +} diff --git a/src/TorchSharp/JIT/Type/TensorType.cs b/src/TorchSharp/JIT/Type/TensorType.cs index 37d476c3e..152dc6e7f 100644 --- a/src/TorchSharp/JIT/Type/TensorType.cs +++ b/src/TorchSharp/JIT/Type/TensorType.cs @@ -1,45 +1,68 @@ -//// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. -//using System; -//using System.Runtime.InteropServices; - -//namespace TorchSharp.JIT -//{ -// public sealed class TensorType : Type -// { -// internal TensorType(IntPtr handle) : base(handle) -// { -// this.handle = new HType(handle, true); -// } - -// internal TensorType(Type type) : base() -// { -// handle = type.handle; -// type.handle = new HType(IntPtr.Zero, true); -// type.Dispose(); -// } - -// [DllImport("LibTorchSharp")] -// private static extern short THSJIT_getScalarFromDimensionedTensorType(HType handle); - -// public Tensor.ScalarType GetScalarType() -// { -// return (Tensor.ScalarType)THSJIT_getScalarFromDimensionedTensorType(handle); -// } - -// [DllImport("LibTorchSharp")] -// private static extern int THSJIT_getDimensionedTensorTypeDimensions(HType handle); - -// public int GetDimensions() -// { -// return THSJIT_getDimensionedTensorTypeDimensions(handle); -// } - -// [DllImport("LibTorchSharp")] -// private static extern string THSJIT_getDimensionedTensorDevice(HType handle); - -// public string GetDevice() -// { -// return THSJIT_getDimensionedTensorDevice(handle); -// } -// } -//} +// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. +using System; +using System.Runtime.InteropServices; + +namespace TorchSharp +{ + public static partial class jit + { + public sealed class TensorType : Type + { + internal TensorType(IntPtr handle) : base(handle, TypeKind.TensorType) + { + this.handle = new HType(handle, true, TypeKind.TensorType); + } + + internal TensorType(Type type) : base() + { + handle = type.handle; + type.handle = new HType(IntPtr.Zero, true, TypeKind.TensorType); + type.Dispose(); + } + + [DllImport("LibTorchSharp")] + private static extern sbyte THSJIT_TensorType_dtype(HType handle); + + public torch.ScalarType GetScalarType() + { + return (torch.ScalarType)THSJIT_TensorType_dtype(handle); + } + + + [DllImport("LibTorchSharp")] + static extern long THSJIT_TensorType_sizes(HType handle, AllocatePinnedArray allocator); + + /// + /// Retrieves the sizes of all dimensions of the tensor. + /// + public long[] size() + { + long[] ptrArray; + + using (var pa = new PinnedArray()) { + THSJIT_TensorType_sizes(handle, pa.CreateArray); + torch.CheckForErrors(); + ptrArray = pa.Array; + } + + return ptrArray; + } + + [DllImport("LibTorchSharp")] + private static extern int THSJIT_getDimensionedTensorTypeDimensions(HType handle); + + public int GetDimensions() + { + return THSJIT_getDimensionedTensorTypeDimensions(handle); + } + + [DllImport("LibTorchSharp")] + private static extern string THSJIT_getDimensionedTensorDevice(HType handle); + + public string GetDevice() + { + return THSJIT_getDimensionedTensorDevice(handle); + } + } + } +} diff --git a/src/TorchSharp/JIT/Type/Type.cs b/src/TorchSharp/JIT/Type/Type.cs index e06d40ccc..46bd923f9 100644 --- a/src/TorchSharp/JIT/Type/Type.cs +++ b/src/TorchSharp/JIT/Type/Type.cs @@ -1,108 +1,123 @@ -//// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. -//using System; -//using System.Runtime.InteropServices; - -//namespace TorchSharp.JIT -//{ -// public class Type : IDisposable -// { -// /// -// /// Class wrapping PyTorch's type object reference. -// /// -// internal sealed class HType : SafeHandle -// { -// public HType(IntPtr preexistingHandle, bool ownsHandle) : base(IntPtr.Zero, ownsHandle) -// { -// SetHandle(preexistingHandle); -// } - -// public override bool IsInvalid => handle == IntPtr.Zero; - -// // This is just for marshalling -// internal HType() : base(IntPtr.Zero, true) -// { -// } - -// [DllImport("LibTorchSharp")] -// private static extern void THSJIT_typeDispose(HType handle); - -// protected override bool ReleaseHandle() -// { -// THSJIT_typeDispose(this); -// return true; -// } - -// protected override void Dispose(bool disposing) -// { -// if (disposing) -// { -// ReleaseHandle(); -// } -// } -// } - -// internal HType handle; - -// internal Type(IntPtr handle) -// { -// this.handle = new HType(handle, true); -// } - -// protected Type() -// { -// } - -// ~Type() -// { -// Dispose(false); -// } - -// /// -// /// Releases the storage. -// /// -// public void Dispose() -// { -// Dispose(true); -// GC.SuppressFinalize(this); -// } - -// /// -// /// Implements the .NET Dispose pattern. -// /// -// protected void Dispose(bool disposing) -// { -// if (disposing) -// { -// handle.Dispose(); -// handle.SetHandleAsInvalid(); -// } -// } - -// [DllImport("LibTorchSharp")] -// private static extern sbyte THSJIT_typeKind(HType handle); - -// internal TypeKind Kind -// { -// get { return (TypeKind)THSJIT_typeKind(handle); } -// } - -// [DllImport("LibTorchSharp")] -// private static extern IntPtr THSJIT_typeCast(HType module); - -// internal TensorType AsTensorType() -// { -// return new TensorType(THSJIT_typeCast(handle)); -// } - -// internal DynamicType AsDynamicType() -// { -// return new DynamicType(THSJIT_typeCast(handle)); -// } - -// internal enum TypeKind : sbyte -// { -// TensorType = 0, -// DimensionedTensorType = 1 -// } -// } -//} +// Copyright (c) .NET Foundation and Contributors. All Rights Reserved. See LICENSE in the project root for license information. +using System; +using System.Collections; +using System.Runtime.InteropServices; + +namespace TorchSharp +{ + public static partial class jit + { + + public class Type : IDisposable + { + /// + /// Class wrapping PyTorch's type object reference. + /// + internal sealed class HType : SafeHandle + { + public HType(IntPtr preexistingHandle, bool ownsHandle, TypeKind kind) : base(IntPtr.Zero, ownsHandle) + { + SetHandle(preexistingHandle); + this.kind = kind; + } + + public override bool IsInvalid => handle == IntPtr.Zero; + + // This is just for marshalling + internal HType() : base(IntPtr.Zero, true) + { + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Type_dispose(HType handle); + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_TensorType_dispose(HType handle); + + protected override bool ReleaseHandle() + { + switch (kind) { + case TypeKind.TensorType: + THSJIT_TensorType_dispose(this); + break; + default: + THSJIT_Type_dispose(this); + break; + } + return true; + } + + protected override void Dispose(bool disposing) + { + if (disposing) { + ReleaseHandle(); + } + } + + private TypeKind kind; + } + + internal HType handle; + + internal Type(IntPtr handle, TypeKind kind) + { + this.handle = new HType(handle, true, kind); + } + + protected Type() + { + } + + ~Type() + { + Dispose(false); + } + + /// + /// Releases the storage. + /// + public void Dispose() + { + Dispose(true); + GC.SuppressFinalize(this); + } + + /// + /// Implements the .NET Dispose pattern. + /// + protected void Dispose(bool disposing) + { + if (disposing) { + handle.Dispose(); + handle.SetHandleAsInvalid(); + } + } + + [DllImport("LibTorchSharp")] + private static extern sbyte THSJIT_Type_kind(HType handle); + + internal TypeKind Kind { + get { return (TypeKind)THSJIT_Type_kind(handle); } + } + + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_Type_cast(HType module); + + internal TensorType AsTensorType() + { + return new TensorType(THSJIT_Type_cast(handle)); + } + + internal DynamicType AsDynamicType() + { + return new DynamicType(THSJIT_Type_cast(handle)); + } + + internal enum TypeKind : sbyte + { + AnyType = 0, + TensorType = 3, + } + } + } +} \ No newline at end of file diff --git a/src/TorchSharp/NN/Module.cs b/src/TorchSharp/NN/Module.cs index 53ddc465b..9a0872512 100644 --- a/src/TorchSharp/NN/Module.cs +++ b/src/TorchSharp/NN/Module.cs @@ -31,9 +31,10 @@ public class Module : IDisposable /// internal sealed class HType : SafeHandle { - public HType(IntPtr preexistingHandle, bool ownsHandle) + public HType(IntPtr preexistingHandle, bool ownsHandle, bool script = false) : base(IntPtr.Zero, ownsHandle) { + isScriptModule = script; SetHandle(preexistingHandle); } @@ -46,10 +47,18 @@ internal HType() : base(IntPtr.Zero, true) [DllImport("LibTorchSharp")] private static extern void THSNN_Module_dispose(HType handle); + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_dispose(HType handle); protected override bool ReleaseHandle() { - if (!IsInvalid) THSNN_Module_dispose(this); + if (!IsInvalid) { + if (isScriptModule) { + THSJIT_Module_dispose(this); + } else { + THSNN_Module_dispose(this); + } + } SetHandle(IntPtr.Zero); return true; } @@ -60,6 +69,8 @@ protected override void Dispose(bool disposing) ReleaseHandle(); } } + + private bool isScriptModule; } internal HType handle; @@ -75,6 +86,19 @@ internal BoxedModule BoxedModule { } } + internal Module(HType handle, IntPtr? boxedHandle) + { + this.handle = handle; + boxedModule = boxedHandle.HasValue ? new BoxedModule(boxedHandle.Value) : null; + + foreach (var (parameterName, parameter) in _named_parameters()) { + register_parameter(parameterName, parameter); + } + foreach (var (bufferName, buffer) in _named_buffers()) { + register_buffer(bufferName, buffer); + } + } + internal Module(IntPtr handle, IntPtr? boxedHandle, bool ownsHandle = true) { this.handle = new HType(handle, ownsHandle); @@ -256,8 +280,8 @@ public virtual Module to(ScalarType dtype) /// public Module to(Tensor other) { - to(other.device_type, other.device_index); - return to(other.dtype); + to(other.dtype); + return to(other.device_type, other.device_index); } /// @@ -326,7 +350,7 @@ public virtual void eval() [DllImport("LibTorchSharp")] private static extern bool THSNN_Module_is_training(HType module); - public bool training { + public virtual bool training { get { var res = THSNN_Module_is_training(handle); CheckForErrors(); @@ -464,7 +488,7 @@ public virtual (IList missing_keys, IList unexpected_keyes) load [DllImport("LibTorchSharp")] private static extern void THSNN_Module_get_named_parameters(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); - protected (string name, Parameter parameter)[] _named_parameters() + protected virtual (string name, Parameter parameter)[] _named_parameters() { using var pa = new PinnedArray(); using var sa = new PinnedArray(); @@ -479,7 +503,7 @@ public virtual (IList missing_keys, IList unexpected_keyes) load [DllImport("LibTorchSharp")] private static extern void THSNN_Module_get_named_buffers(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); - protected (string name, Tensor buffer)[] _named_buffers() + protected virtual (string name, Tensor buffer)[] _named_buffers() { using var pa = new PinnedArray(); using var sa = new PinnedArray(); @@ -799,7 +823,7 @@ public static void save_state_dict(System.IO.BinaryWriter writer, Dictionary - public Module load(string location, bool strict = true, IList skip = null) + public virtual Module load(string location, bool strict = true, IList skip = null) { var dt = _deviceType; var di = _deviceIndex; diff --git a/src/TorchSharp/Tensor/Tensor.LinearAlgebra.cs b/src/TorchSharp/Tensor/Tensor.LinearAlgebra.cs index 002a1471d..e5b6be8cf 100644 --- a/src/TorchSharp/Tensor/Tensor.LinearAlgebra.cs +++ b/src/TorchSharp/Tensor/Tensor.LinearAlgebra.cs @@ -265,6 +265,15 @@ public static Tensor det(Tensor input) return torch.linalg.det(input); } + public static Tensor diag(Tensor input, long dimension = 0) => input.diag(dimension); + + /// + /// Returns the sum of the elements of the diagonal of the input 2-D matrix. + /// + /// The input tensor + /// + public static Tensor trace(Tensor input) => input.trace(); + /// /// Returns a partial view of input with the its diagonal elements with respect to dim1 and dim2 appended as a dimension at the end of the shape. /// The argument offset controls which diagonal to consider: diff --git a/src/TorchSharp/Tensor/Tensor.cs b/src/TorchSharp/Tensor/Tensor.cs index 63e4d9c54..420dbaae0 100644 --- a/src/TorchSharp/Tensor/Tensor.cs +++ b/src/TorchSharp/Tensor/Tensor.cs @@ -2990,6 +2990,22 @@ public Tensor diag(long dimension = 0) return new Tensor(res); } + [DllImport("LibTorchSharp")] + static extern IntPtr THSTensor_trace(IntPtr tensor); + + /// + /// Returns the sum of the elements of the diagonal of the input 2-D matrix. + /// + /// + public Tensor trace() + { + if (ndim != 2) + throw new ArgumentException($"Expected a matrix, but got tensor with ndim == {ndim}"); + var res = THSTensor_trace(Handle); + if (res == IntPtr.Zero) { torch.CheckForErrors(); } + return new Tensor(res); + } + [DllImport("LibTorchSharp")] static extern IntPtr THSTensor_diagflat(IntPtr tensor, long offset); diff --git a/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj b/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj index 5acc6b627..e65ba6bf3 100644 --- a/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj +++ b/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj @@ -42,6 +42,18 @@ + + + PreserveNewest + + + + + + PreserveNewest + + + diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index 6242e4a5d..217e69a24 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -76,6 +76,65 @@ public void TestSaveLoadLinear3() } + [Fact] + public void TestLoadJIT_1() + { + // One linear layer followed by ReLU. + var m = TorchSharp.jit.load(@".\linrelu.script.dat"); + var t = m.forward(torch.ones(10)); + + var inp = m.GetNumberOfOutputs(); + + Assert.Equal(new long[] { 6 }, t.shape); + Assert.Equal(torch.float32, t.dtype); + Assert.Equal(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }, t.data().ToArray()); + + m.Dispose(); + } + + [Fact] + public void TestLoadJIT_2() + { + // Two linear layers, nested Sequential, ReLU in between. + var m = TorchSharp.jit.load(@".\l1000_100_10.script.dat"); + + var sms = m.named_modules().ToArray(); + Assert.Equal(5, sms.Length); + + var kids = m.named_children().ToArray(); + Assert.Equal(2, kids.Length); + + var t = m.forward(torch.ones(1000)); + + Assert.Equal(new long[] { 10 }, t.shape); + Assert.Equal(torch.float32, t.dtype); + Assert.Equal(new float[] { 0.564213157f, -0.04519982f, -0.005117342f, 0.395530462f, -0.3780813f, -0.004734449f, -0.3221216f, -0.289159119f, 0.268511474f, 0.180702567f }, t.data().ToArray()); + + m.Dispose(); + } + + [Fact] + public void TestSaveLoadJITCUDA() + { + if (torch.cuda.is_available()) { + + var m = TorchSharp.jit.load(@".\linrelu.script.dat"); + + m.to(DeviceType.CUDA); + var params0 = m.parameters().ToArray(); + foreach (var p in params0) + Assert.Equal(DeviceType.CUDA, p.device_type); + + var t = m.forward(torch.ones(10).cuda()).cpu(); + + Assert.Equal(new long[] { 6 }, t.shape); + Assert.Equal(torch.float32, t.dtype); + Assert.Equal(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }, t.data().ToArray()); + + m.Dispose(); + } + } + [Fact] public void TestSaveLoadConv2D() { diff --git a/test/TorchSharpTest/TestTraining.cs b/test/TorchSharpTest/TestTraining.cs index a8561d409..107ecc200 100644 --- a/test/TorchSharpTest/TestTraining.cs +++ b/test/TorchSharpTest/TestTraining.cs @@ -186,7 +186,7 @@ private static void ReInitializeLinear(Generator gen, Linear linear) } } - private static float TrainLoop(Sequential seq, Tensor x, Tensor y, optim.Optimizer optimizer) + private static float TrainLoop(Module seq, Tensor x, Tensor y, optim.Optimizer optimizer) { var loss = mse_loss(Reduction.Sum); @@ -213,7 +213,7 @@ private static float TrainLoop(Sequential seq, Tensor x, Tensor y, optim.Optimiz return finalLoss; } - private static float TrainLoop(Sequential seq, Tensor x, Tensor y, optim.Optimizer optimizer, optim.lr_scheduler.LRScheduler scheduler, bool check_lr = true) + private static float TrainLoop(Module seq, Tensor x, Tensor y, optim.Optimizer optimizer, optim.lr_scheduler.LRScheduler scheduler, bool check_lr = true) { var loss = mse_loss(Reduction.Sum); @@ -1665,6 +1665,24 @@ public void TestTrainingLBFGS_ME() //Assert.True(finalLoss < initialLoss); } + [Fact] + public void TestTrainingLoadedTorchScript() + { + var gen = new Generator(4711); + CreateDataAndLabels(gen, out var x, out var y); + + var seq = TorchSharp.jit.load(@".\l1000_100_10.script.dat"); + + double learning_rate = 0.00004f; + var optimizer = torch.optim.SGD(seq.parameters(), learning_rate); + + var loss = TrainLoop(seq, x, y, optimizer); + + LossIsClose(53.81697f, loss); + + seq.eval(); + } + [Fact] public void TestTrainingConv2d() { diff --git a/test/TorchSharpTest/TorchSharpTest.csproj b/test/TorchSharpTest/TorchSharpTest.csproj index cc9971188..b93ba1cbe 100644 --- a/test/TorchSharpTest/TorchSharpTest.csproj +++ b/test/TorchSharpTest/TorchSharpTest.csproj @@ -26,6 +26,15 @@ + + PreserveNewest + + + PreserveNewest + + + PreserveNewest + PreserveNewest diff --git a/test/TorchSharpTest/l1000_100_10.script.dat b/test/TorchSharpTest/l1000_100_10.script.dat new file mode 100644 index 0000000000000000000000000000000000000000..399c66b0aac73dfa9f04972a044fd707cee9476f GIT binary patch literal 411032 zcmZsie^|^}*v2P92uTv#Cd9Uc5NggHgV5R#8uP4MIp1^c=W~CK^Pin{MIt>t(f@h%5SfV9Zr(iB zbEV(PvDUMu8;RWhpO;1GRFd0E#l79y(Y&#POLFoNCf2ccQr1Jg>#$g4a(Qx(1?LbX zYrv$SOcVy6WXj#}ypwM~3^p~jNr77V~ z2S38;Su+{jJPB=c1&gzeh5w#9B);*-p)q^N>6VnFUGfq9q!1srC)4e<73BKB1^RPN zXDH>&bRmFWY4!Vm@C)&ulTQBzRaw6({&rn3eSr}|tjW6|I$kCniwMj+Ly?O{! zhKot`F3&D*$5D)#`<6Pwj*!u#CD`2c06CnNKpBvM?GAY)O+TQjx^SJ1d=`(CAzECS z_KCD_H$x^-ATJ^n&VK>&bzN2NC1cQL{RSNy4^o6@PuioDQmNT8(w5BQmc?Eqd(}dY z`diVpKu-Vu8%_mHr=cDm&pa30A{S{4RZTI#q>6TE9^M!0`rP2r|2j6PQ_QXL24;OTj0iA$?iP+svd)eYGp~-gAqZ*I2>vt1nl-)u^o5 zZ%m<CLUT2xkcTKnouXQ=hP^SXI`7pFolW9?=~Dx2($xb<3) z;XXP%<|TEM-sai+PhxcR2g(c{4aK6XP_>;R$y!Hd@6}2g^F>@zP$;aWNQg?`XZOBc zff3*1C^7OGAG$J%m)N!y0Ifu-q0T{LF6#YlCpk(j>b`0 zz^sX+u&~DXo zISoGYUF1A&FKnAaSbSv|^*X5`P1t9##jPydEqqD&cN4k4b`;s#KPQp-v8+z+w&d<4 zC%xrA5YYx`!-}yYq>*gT+4HdL87Q28ktMzSfU>G^M9eNmz3EHx*f5GYe(6v5KffXm zuY+X0ZaYGw(s^WEK9pbIqES8n#`Alsd6`* zA;t7_v_bC|s-=%a(Q&kV)%V$OeSJGbQR?xz(0XPT(;A)4Ow(=Q6$y0euja?4YZks)5uHLX|Luzg_Rwm z^6qEJVBTQL^m)qNU$^s$`BS03)J-*Jrvu3c9%9q?93(Pc2Ic8l+%dTVp3Y<7@s~HZ zPVL1+OUuNH?T#clW2=g|+lIj5mnmT7Q%X~Br&E6t$;#?g)-FEuGxQ5d3yZ{^9 zRfR~sF0!|L*u;D?-r(nm6jEj{rh!2vWFAelYY&IyOqxnjst~^02TYw^b9+TE4h-coeBIS?ID4ceLHQ(Go2K(kv_4+uvFejbdkKW)~xyXL#>nyT7n8rJ$ zT!!YbhK-ofofNH0$aaT425sp@9=3f^gbBiPc9C{S6JQ;xM9q$ayk&rf zT)#eKZ7Z_ap-4_nC(a>OT}eJ)Qn6UuL9%B%*qpu2v?x+b+7nG!yg{EDOT#FL$I#lb zO4y`(Q_J)!gtmXjln=Mz?(~^=%2-ztwYlZw z7LffTE=;?f6wkP|OsAW1^zH>8)w*8I#lB+c6$Z3lB zV8~6G#mnvhiz=p!v`Rti68)e@hNg^YT<=O^v0MyWWy$;90wF zuTRs^vaQru@e{7|o-@Vx

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src/TorchSharp/NN/Module.cs | 10 ++++++++-- test/TorchSharpTest/TestLoadSave.cs | 8 +++----- test/TorchSharpTest/TestTraining.cs | 2 +- 4 files changed, 14 insertions(+), 8 deletions(-) diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index beaba63c3..d87359671 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -320,6 +320,8 @@ public unsafe override Tensor forward(Tensor tensor) public static ScriptModule load(string filename) { + if (!System.IO.File.Exists(filename)) + throw new System.IO.FileNotFoundException(filename); return new ScriptModule(THSJIT_load(filename)); } diff --git a/src/TorchSharp/NN/Module.cs b/src/TorchSharp/NN/Module.cs index 9a0872512..2e949250f 100644 --- a/src/TorchSharp/NN/Module.cs +++ b/src/TorchSharp/NN/Module.cs @@ -312,9 +312,12 @@ public virtual Module apply(Action fn) [DllImport("LibTorchSharp")] static extern IntPtr THSNN_Module_load([MarshalAs(UnmanagedType.LPStr)] string location); - public static Module Load(string location) + public static Module Load(string filename) { - var handle = THSNN_Module_load(location); + if (!System.IO.File.Exists(filename)) + throw new System.IO.FileNotFoundException(filename); + + var handle = THSNN_Module_load(filename); if (handle == IntPtr.Zero) { CheckForErrors(); } return new Module(handle, IntPtr.Zero); } @@ -825,6 +828,9 @@ public static void save_state_dict(System.IO.BinaryWriter writer, Dictionary public virtual Module load(string location, bool strict = true, IList skip = null) { + if (!System.IO.File.Exists(location)) + throw new System.IO.FileNotFoundException(location); + var dt = _deviceType; var di = _deviceIndex; diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index 217e69a24..0143cc4f1 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -80,11 +80,9 @@ public void TestSaveLoadLinear3() public void TestLoadJIT_1() { // One linear layer followed by ReLU. - var m = TorchSharp.jit.load(@".\linrelu.script.dat"); + var m = TorchSharp.jit.load(@"linrelu.script.dat"); var t = m.forward(torch.ones(10)); - var inp = m.GetNumberOfOutputs(); - Assert.Equal(new long[] { 6 }, t.shape); Assert.Equal(torch.float32, t.dtype); Assert.Equal(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }, t.data().ToArray()); @@ -96,7 +94,7 @@ public void TestLoadJIT_1() public void TestLoadJIT_2() { // Two linear layers, nested Sequential, ReLU in between. - var m = TorchSharp.jit.load(@".\l1000_100_10.script.dat"); + var m = TorchSharp.jit.load(@"l1000_100_10.script.dat"); var sms = m.named_modules().ToArray(); Assert.Equal(5, sms.Length); @@ -118,7 +116,7 @@ public void TestSaveLoadJITCUDA() { if (torch.cuda.is_available()) { - var m = TorchSharp.jit.load(@".\linrelu.script.dat"); + var m = TorchSharp.jit.load(@"linrelu.script.dat"); m.to(DeviceType.CUDA); var params0 = m.parameters().ToArray(); diff --git a/test/TorchSharpTest/TestTraining.cs b/test/TorchSharpTest/TestTraining.cs index 107ecc200..251885618 100644 --- a/test/TorchSharpTest/TestTraining.cs +++ b/test/TorchSharpTest/TestTraining.cs @@ -1671,7 +1671,7 @@ public void TestTrainingLoadedTorchScript() var gen = new Generator(4711); CreateDataAndLabels(gen, out var x, out var y); - var seq = TorchSharp.jit.load(@".\l1000_100_10.script.dat"); + var seq = TorchSharp.jit.load(@"l1000_100_10.script.dat"); double learning_rate = 0.00004f; var optimizer = torch.optim.SGD(seq.parameters(), learning_rate); From e1da951070864a5f9931ae48fc1550a9cd96640f Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Fri, 1 Jul 2022 16:11:17 -0700 Subject: [PATCH 03/12] Added another JIT'd test file -- this one was scripted, not traced. --- RELEASENOTES.md | 3 ++- .../TorchSharpTest.WithCudaBinaries.csproj | 3 +++ test/TorchSharpTest/TestLoadSave.cs | 14 ++++++++++++++ test/TorchSharpTest/TorchSharpTest.csproj | 2 +- test/TorchSharpTest/scripted.script.dat | Bin 0 -> 4310 bytes 5 files changed, 20 insertions(+), 2 deletions(-) create mode 100644 test/TorchSharpTest/scripted.script.dat diff --git a/RELEASENOTES.md b/RELEASENOTES.md index a163115f5..29eee08f3 100644 --- a/RELEASENOTES.md +++ b/RELEASENOTES.md @@ -10,7 +10,8 @@ __API Changes__: Add torch.utils.rnn
Add torchvision.io
-Add Tensor.trace() and torch.trace()
+Add Tensor.trace() and torch.trace() (unrelated to torch.jit.trace)
+Add ability to load modules that were traced using torch.jit.trace() in Pytorch
## NuGet Version 0.96.8 diff --git a/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj b/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj index e65ba6bf3..8f2fc3f91 100644 --- a/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj +++ b/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj @@ -46,6 +46,9 @@ PreserveNewest + + PreserveNewest + diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index 0143cc4f1..d9465293c 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -92,6 +92,20 @@ public void TestLoadJIT_1() [Fact] public void TestLoadJIT_2() + { + // One linear layer followed by ReLU. + var m = TorchSharp.jit.load(@"scripted.script.dat"); + var t = m.forward(torch.ones(6)); + + Assert.Equal(new long[] { 6 }, t.shape); + Assert.Equal(torch.float32, t.dtype); + Assert.Equal(new float[] { 1.554085f, 1.01024628f, -1.35086036f, -1.84021854f, 0.0127189457f, 0.5994258f }, t.data().ToArray()); + + m.Dispose(); + } + + [Fact] + public void TestLoadJIT_3() { // Two linear layers, nested Sequential, ReLU in between. var m = TorchSharp.jit.load(@"l1000_100_10.script.dat"); diff --git a/test/TorchSharpTest/TorchSharpTest.csproj b/test/TorchSharpTest/TorchSharpTest.csproj index b93ba1cbe..a23b8f447 100644 --- a/test/TorchSharpTest/TorchSharpTest.csproj +++ b/test/TorchSharpTest/TorchSharpTest.csproj @@ -32,7 +32,7 @@ PreserveNewest - + PreserveNewest diff --git a/test/TorchSharpTest/scripted.script.dat b/test/TorchSharpTest/scripted.script.dat new file mode 100644 index 0000000000000000000000000000000000000000..1a769e2137add1896da7415b974c38bb1b9d6fce GIT binary patch literal 4310 zcmb7H3se)=7M%o5U;;`IXe0$e(MJ>#K8iviLC~P2AU`Dwgcy=Q0x==UM1quW3q?@` z;R!0wrNLTxU`uT&MFg~bte>KSpeVEoS`ZZl|A6{t5-JHFUmez6vohR$&bj;UbI-Z{ z44qj3psNc^c|d>wM2W=|E*oM~?CGAyK!i>u@}p_bDoUvjeiYH-&aR;OGqAcfWwxXCus>w@|1ed2f@nS@L2*=*$SgS|5XwN7lou%% z2)QhXCz6S!tZj~<1Z`u(#KH&}Jd+*Gljx`+AYCYCLqY0~pkx*k1<$dU%x3DqZ%&+C zf??=G0TL_&uwkGX7|4c!VW6Na4o55$@;Hz{ERum6q+Fhq$6X`fK%hjI6bJ=M^q7d| zASqiQ5{RNDU>4I9{>>7|SW$AJkQK@1#KyCwTozv}j+Nm2RBI6mL_D@sqCc@@vU*h_ z5qYa>uG#Uw-ua3=-3Fib5 zDPYSacrB!(#0W-W;N{L!Az|DE%9syk@o|3gNQntNOv#7@2m{Z<4#I>X1Cf9+oN7~Z z%>-Dek^o1{mCpj*G?rHIVwBWnPSJYr>nDNr3$!6K2>QB!EZcnFoL!WG1B=p*q zK0h{E&39?4u-?$In&cIj&|D)+DT%dj^V4ILo#cojF!HcGEKpOk)K3$!IJ z6^9KAvMJcq^H;}J?+(xN&&kPx)@P%!Ew6VP(S3Rx@O}izJl=zQ8}hC?e)CnTceXj? zL#Y(y&*v4U5$Lh4UlX?3#JZupnfJa}J=E;`M~d~?s?L@_K2zL@%sjSFifO?Ax3(tT z!XU)%IQdCKE^Q|&_K`_@=#Kfeo0orTYIScdE9lmIFYYL7@JQz&&pEr&=XsWl1gsNY zk2YwRl{E2p{vLqx-u>>g$D;G;oaYsZy`-h$v4u~s$FqlrWTzslM6MNy+n`;i zdUg!gcZXh>`|#VWQcm8oI*PSZc%SN!s%_Q3^af^j-v^ns18k;YmZHi&ibzBm&pwJe z`&7!c*5Y~k(^YCDhXxha;%7@1D`a0SaemBRYH=$Wd-!>zvYOpo^i!rz@r!t<(B<)GH|DljCtp?) zcUIDr;0f3MJ6Q#u+@k|2*ImrKbI7|4tX{?R?)|wb(YrV zVs;TA2iN7oIr`zCF~4zNgsw#Ppy8DnwP@{C%D-Hy#`^B2ywWW=W3_s&VMVJKLmJ># zds2q$=ksx4N1~Jm*0mk+we0QXN)<;o<4hW$`h5wyA;v56d!7^+>Rs;<{Ewf z*n1fBE1k+Srj+mBCH^2iSgYc$-pQoqG%Vi%c+6a5Nr2r4xr>sERF#S?R7saK6I)YN z%;iN{szq-j5XH$MSIb~kMYRPj;YVG3wZ9={#no~{98wwC!Z7vpaCbkkh)1%tqmJWU zVZ4+F$)zGob&1n-Vmofw))FyB0ud3pRpfIrU=olqbERFqMngTMNfs(EHS99_` zj5G1qi=L7Ewzq#*kiE61sj-{eUPNde%w#7DW7oKe_<&GEU1>FCCXQPy3=u|2maL%8BTZ_i-_L0v;eLY_jIVA3JbWryyT5k2=r4St8DM zaRGf|a=QS<-nMzo<&Obui{s7B3roTqm-sq z*|Rsq-S4vtEsOQBVPlD?2j5b(TZv|S0-A>Sa|ah zk5d}c$tEhn>i zC&xdb7|o-Yq~+ui-1~pXiB=t&9J^*lI%%10*ZT;wGsmr&gLo|mi(x^jC?X0mxAO8 Date: Fri, 1 Jul 2022 16:19:50 -0700 Subject: [PATCH 04/12] Fixed namespace issue. --- src/TorchSharp/JIT/ScriptModule.cs | 477 ++++++++++++------------ src/TorchSharp/JIT/Type/DynamicType .cs | 14 +- src/TorchSharp/JIT/Type/TensorType.cs | 89 ++--- src/TorchSharp/JIT/Type/Type.cs | 175 ++++----- test/TorchSharpTest/TestLoadSave.cs | 8 +- test/TorchSharpTest/TestTraining.cs | 2 +- 6 files changed, 389 insertions(+), 376 deletions(-) diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index d87359671..d0a693ed6 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -9,177 +9,229 @@ namespace TorchSharp { - public static partial class jit + public static partial class torch { - public class ScriptModule : torch.nn.Module + public static partial class jit { - internal ScriptModule(IntPtr handle) : base(new HType(handle, true), null) + public class ScriptModule : torch.nn.Module { - } + internal ScriptModule(IntPtr handle) : base(new HType(handle, true), null) + { + } - ~ScriptModule() - { - Dispose(false); - } + ~ScriptModule() + { + Dispose(false); + } - ///

- /// Implements the .NET Dispose pattern. - /// - protected override void Dispose(bool disposing) - { - if (disposing && !handle.IsInvalid) { - - //foreach (var (_, p) in named_buffers(false)) { - // p.Dispose(); - //} - //foreach (var (_, b) in named_parameters(false)) { - // b.Dispose(); - //} - - //foreach (var (_, m) in named_modules()) { - // m.Dispose(); - //} - - handle.Dispose(); - handle.SetHandleAsInvalid(); - boxedModule?.Dispose(); + /// + /// Implements the .NET Dispose pattern. + /// + protected override void Dispose(bool disposing) + { + if (disposing && !handle.IsInvalid) { + + //foreach (var (_, p) in named_buffers(false)) { + // p.Dispose(); + //} + //foreach (var (_, b) in named_parameters(false)) { + // b.Dispose(); + //} + + //foreach (var (_, m) in named_modules()) { + // m.Dispose(); + //} + + handle.Dispose(); + handle.SetHandleAsInvalid(); + boxedModule?.Dispose(); + } } - } - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_named_parameters(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_parameters(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); - protected override (string name, TorchSharp.Modules.Parameter parameter)[] _named_parameters() - { - using var pa = new PinnedArray(); - using var sa = new PinnedArray(); - THSJIT_Module_named_parameters(handle, pa.CreateArray, sa.CreateArray); - CheckForErrors(); - var ptrArray = pa.Array; - var strArray = sa.Array; - - return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new TorchSharp.Modules.Parameter(x))).ToArray(); - } + protected override (string name, TorchSharp.Modules.Parameter parameter)[] _named_parameters() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_parameters(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_named_buffers(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new TorchSharp.Modules.Parameter(x))).ToArray(); + } - protected override (string name, Tensor buffer)[] _named_buffers() - { - using var pa = new PinnedArray(); - using var sa = new PinnedArray(); - THSJIT_Module_named_buffers(handle, pa.CreateArray, sa.CreateArray); - CheckForErrors(); - var ptrArray = pa.Array; - var strArray = sa.Array; - - return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new Tensor(x))).ToArray(); - } + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_buffers(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_named_modules(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + protected override (string name, Tensor buffer)[] _named_buffers() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_buffers(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; - public override IEnumerable<(string name, nn.Module module)> named_modules() - { - using var pa = new PinnedArray(); - using var sa = new PinnedArray(); - THSJIT_Module_named_modules(handle, pa.CreateArray, sa.CreateArray); - CheckForErrors(); - var ptrArray = pa.Array; - var strArray = sa.Array; - - return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)); - } + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new Tensor(x))).ToArray(); + } - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_named_children(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_modules(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); - public override IEnumerable<(string name, nn.Module module)> named_children() - { - using var pa = new PinnedArray(); - using var sa = new PinnedArray(); - THSJIT_Module_named_children(handle, pa.CreateArray, sa.CreateArray); - CheckForErrors(); - var ptrArray = pa.Array; - var strArray = sa.Array; - - return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)); - } + public override IEnumerable<(string name, nn.Module module)> named_modules() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_modules(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; - [DllImport("LibTorchSharp")] - private static extern long THSJIT_getNumModules(HType module); + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)); + } - [DllImport("LibTorchSharp")] - private static extern int THSJIT_Module_num_inputs(HType module); + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_named_children(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); - public int GetNumberOfInputs() - { - return THSJIT_Module_num_inputs(handle); - } + public override IEnumerable<(string name, nn.Module module)> named_children() + { + using var pa = new PinnedArray(); + using var sa = new PinnedArray(); + THSJIT_Module_named_children(handle, pa.CreateArray, sa.CreateArray); + CheckForErrors(); + var ptrArray = pa.Array; + var strArray = sa.Array; - [DllImport("LibTorchSharp")] - private static extern int THSJIT_Module_num_outputs(HType module); + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)); + } - public int GetNumberOfOutputs() - { - return THSJIT_Module_num_outputs(handle); - } + [DllImport("LibTorchSharp")] + private static extern long THSJIT_getNumModules(HType module); - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_train(HType module); + [DllImport("LibTorchSharp")] + private static extern int THSJIT_Module_num_inputs(HType module); - public override void train() - { - THSJIT_Module_train(handle); - CheckForErrors(); - } + public int GetNumberOfInputs() + { + return THSJIT_Module_num_inputs(handle); + } - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_eval(HType module); + [DllImport("LibTorchSharp")] + private static extern int THSJIT_Module_num_outputs(HType module); - public override void eval() - { - THSJIT_Module_eval(handle); - CheckForErrors(); - } + public int GetNumberOfOutputs() + { + return THSJIT_Module_num_outputs(handle); + } - [DllImport("LibTorchSharp")] - private static extern bool THSJIT_Module_is_training(HType module); + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_train(HType module); - public override bool training { - get { - var res = THSJIT_Module_is_training(handle); + public override void train() + { + THSJIT_Module_train(handle); CheckForErrors(); - return res; } - } - [DllImport("LibTorchSharp")] - static extern void THSJIT_Module_to_device(HType module, long deviceType, long deviceIndex); + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_eval(HType module); - [DllImport("LibTorchSharp")] - static extern void THSJIT_Module_to_dtype(HType module, sbyte dtype); - - /// - /// Moves the parameters and buffers. - /// - /// The device type, e.g. 'CPU' or 'CUDA'. - /// The optional device index. - /// - public override nn.Module to(DeviceType deviceType, int deviceIndex = -1) - { - if (deviceType != DeviceType.CUDA) deviceIndex = -1; + public override void eval() + { + THSJIT_Module_eval(handle); + CheckForErrors(); + } - if (deviceType == DeviceType.CUDA && !torch.cuda.is_available()) throw new InvalidOperationException("CUDA is not available."); + [DllImport("LibTorchSharp")] + private static extern bool THSJIT_Module_is_training(HType module); - if (deviceType != _deviceType || deviceIndex != _deviceIndex) { + public override bool training { + get { + var res = THSJIT_Module_is_training(handle); + CheckForErrors(); + return res; + } + } - InitializeDeviceType(deviceType); - THSJIT_Module_to_device(handle, (int)deviceType, deviceIndex); - CheckForErrors(); + [DllImport("LibTorchSharp")] + static extern void THSJIT_Module_to_device(HType module, long deviceType, long deviceIndex); + + [DllImport("LibTorchSharp")] + static extern void THSJIT_Module_to_dtype(HType module, sbyte dtype); + + /// + /// Moves the parameters and buffers. + /// + /// The device type, e.g. 'CPU' or 'CUDA'. + /// The optional device index. + /// + public override nn.Module to(DeviceType deviceType, int deviceIndex = -1) + { + if (deviceType != DeviceType.CUDA) deviceIndex = -1; + + if (deviceType == DeviceType.CUDA && !torch.cuda.is_available()) throw new InvalidOperationException("CUDA is not available."); + + if (deviceType != _deviceType || deviceIndex != _deviceIndex) { + + InitializeDeviceType(deviceType); + THSJIT_Module_to_device(handle, (int)deviceType, deviceIndex); + CheckForErrors(); + + foreach (var (_, sm) in named_children()) sm.to(deviceType, deviceIndex); + + foreach (var field in GetType().GetFields(BindingFlags.NonPublic | BindingFlags.Public | BindingFlags.Instance)) { + + var fieldName = field.Name; + var value = field.GetValue(this); + + switch (value) { + // This test must come before the Tensor test + case Modules.Parameter param when deviceType == param.device_type && deviceIndex == param.device_index: + continue; + + case Modules.Parameter param: { + var t = param.to(deviceType, deviceIndex); + t.retain_grad(); + var p = new Modules.Parameter(t, param.requires_grad); + field.SetValue(this, p); + ConditionallyRegisterParameter(fieldName, p); + break; + } + + case Tensor tensor when (deviceType != tensor.device_type || deviceIndex != tensor.device_index): { + var t = tensor.to(deviceType, deviceIndex); + field.SetValue(this, t); + ConditionallyRegisterBuffer(fieldName, t); + break; + } + } + } + + _deviceType = deviceType; + _deviceIndex = deviceIndex; + } + + Debug.Assert(_deviceType == DeviceType.CUDA || _deviceIndex == -1); - foreach (var (_, sm) in named_children()) sm.to(deviceType, deviceIndex); + return this; + } + private DeviceType _deviceType = DeviceType.CPU; + private int _deviceIndex = -1; + + /// + /// Convert the parameters and buffers. + /// + /// + public override nn.Module to(ScalarType dtype) + { + THSJIT_Module_to_dtype(handle, (sbyte)dtype); + CheckForErrors(); + + foreach (var (_, sm) in named_children()) sm.to(dtype); foreach (var field in GetType().GetFields(BindingFlags.NonPublic | BindingFlags.Public | BindingFlags.Instance)) { var fieldName = field.Name; @@ -187,11 +239,11 @@ public override nn.Module to(DeviceType deviceType, int deviceIndex = -1) switch (value) { // This test must come before the Tensor test - case Modules.Parameter param when deviceType == param.device_type && deviceIndex == param.device_index: + case Modules.Parameter param when dtype == param.dtype: continue; case Modules.Parameter param: { - var t = param.to(deviceType, deviceIndex); + var t = param.to(dtype); t.retain_grad(); var p = new Modules.Parameter(t, param.requires_grad); field.SetValue(this, p); @@ -199,8 +251,11 @@ public override nn.Module to(DeviceType deviceType, int deviceIndex = -1) break; } - case Tensor tensor when (deviceType != tensor.device_type || deviceIndex != tensor.device_index): { - var t = tensor.to(deviceType, deviceIndex); + case Tensor tensor when dtype == tensor.dtype: + continue; + + case Tensor tensor: { + var t = tensor.to(dtype); field.SetValue(this, t); ConditionallyRegisterBuffer(fieldName, t); break; @@ -208,123 +263,71 @@ public override nn.Module to(DeviceType deviceType, int deviceIndex = -1) } } - _deviceType = deviceType; - _deviceIndex = deviceIndex; + return this; } - Debug.Assert(_deviceType == DeviceType.CUDA || _deviceIndex == -1); +#if true // These functions "work," but the native code doesn't seem to find any interesting information. - return this; - } + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_Module_getInputType(HType module, int index); - private DeviceType _deviceType = DeviceType.CPU; - private int _deviceIndex = -1; + public Type GetInputType(int index) + { + var type = new Type(THSJIT_Module_getInputType(handle, index), Type.TypeKind.AnyType); - /// - /// Convert the parameters and buffers. - /// - /// - public override nn.Module to(ScalarType dtype) - { - THSJIT_Module_to_dtype(handle, (sbyte)dtype); - CheckForErrors(); - - foreach (var (_, sm) in named_children()) sm.to(dtype); - foreach (var field in GetType().GetFields(BindingFlags.NonPublic | BindingFlags.Public | BindingFlags.Instance)) { - - var fieldName = field.Name; - var value = field.GetValue(this); - - switch (value) { - // This test must come before the Tensor test - case Modules.Parameter param when dtype == param.dtype: - continue; - - case Modules.Parameter param: { - var t = param.to(dtype); - t.retain_grad(); - var p = new Modules.Parameter(t, param.requires_grad); - field.SetValue(this, p); - ConditionallyRegisterParameter(fieldName, p); - break; - } - - case Tensor tensor when dtype == tensor.dtype: - continue; - - case Tensor tensor: { - var t = tensor.to(dtype); - field.SetValue(this, t); - ConditionallyRegisterBuffer(fieldName, t); - break; - } - } + return GetType(type); } - return this; - } - -#if false // These functions "work," but the native code doesn't seem to find any interesting information. - - [DllImport("LibTorchSharp")] - private static extern IntPtr THSJIT_Module_getInputType(HType module, int index); - - public Type GetInputType(int index) - { - var type = new Type(THSJIT_Module_getInputType(handle, index), Type.TypeKind.AnyType); + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_getOutputType(HType module, int index); - return GetType(type); - } + public Type GetOutputType(int index) + { + var type = new Type(THSJIT_getOutputType(handle, index), Type.TypeKind.AnyType); - [DllImport("LibTorchSharp")] - private static extern IntPtr THSJIT_getOutputType(HType module, int index); + return GetType(type); + } - public Type GetOutputType(int index) - { - var type = new Type(THSJIT_getOutputType(handle, index), Type.TypeKind.AnyType); + private Type GetType(Type type) + { + switch (type.Kind) { + case Type.TypeKind.TensorType: + var dynamic = type.AsTensorType(); + type.Dispose(); + return dynamic; + //case Type.TypeKind.DimensionedTensorType: + // var tensor = type.AsTensorType(); + // type.Dispose(); + // return tensor; + default: + return type; + } + } +#endif - return GetType(type); - } + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_Module_forward(HType module, IntPtr tensors, int length); - private Type GetType(Type type) - { - switch (type.Kind) { - case Type.TypeKind.TensorType: - var dynamic = type.AsTensorType(); - type.Dispose(); - return dynamic; - //case Type.TypeKind.DimensionedTensorType: - // var tensor = type.AsTensorType(); - // type.Dispose(); - // return tensor; - default: - return type; + public unsafe override Tensor forward(Tensor tensor) + { + using (var parray = new PinnedArray()) { + IntPtr tensorRefs = parray.CreateArray(new[] { tensor.Handle }); + return new Tensor(THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length)); + } } } -#endif [DllImport("LibTorchSharp")] - private static extern IntPtr THSJIT_Module_forward(HType module, IntPtr tensors, int length); + private static extern IntPtr THSJIT_load(string filename); - public unsafe override Tensor forward(Tensor tensor) + public static ScriptModule load(string filename) { - using (var parray = new PinnedArray()) { - IntPtr tensorRefs = parray.CreateArray(new [] { tensor.Handle }); - return new Tensor(THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length)); - } + if (!System.IO.File.Exists(filename)) + throw new System.IO.FileNotFoundException(filename); + return new ScriptModule(THSJIT_load(filename)); } - } - [DllImport("LibTorchSharp")] - private static extern IntPtr THSJIT_load(string filename); - public static ScriptModule load(string filename) - { - if (!System.IO.File.Exists(filename)) - throw new System.IO.FileNotFoundException(filename); - return new ScriptModule(THSJIT_load(filename)); } - - } } diff --git a/src/TorchSharp/JIT/Type/DynamicType .cs b/src/TorchSharp/JIT/Type/DynamicType .cs index c345b2337..e65a649f3 100644 --- a/src/TorchSharp/JIT/Type/DynamicType .cs +++ b/src/TorchSharp/JIT/Type/DynamicType .cs @@ -3,14 +3,18 @@ namespace TorchSharp { - public static partial class jit + public static partial class torch { - public sealed class DynamicType : Type + + public static partial class jit { - internal DynamicType(IntPtr handle) : base(handle, Type.TypeKind.AnyType) + public sealed class DynamicType : Type { - this.handle = new HType(handle, true, Type.TypeKind.AnyType); + internal DynamicType(IntPtr handle) : base(handle, Type.TypeKind.AnyType) + { + this.handle = new HType(handle, true, Type.TypeKind.AnyType); + } } } } -} +} \ No newline at end of file diff --git a/src/TorchSharp/JIT/Type/TensorType.cs b/src/TorchSharp/JIT/Type/TensorType.cs index 152dc6e7f..296a680a7 100644 --- a/src/TorchSharp/JIT/Type/TensorType.cs +++ b/src/TorchSharp/JIT/Type/TensorType.cs @@ -4,64 +4,67 @@ namespace TorchSharp { - public static partial class jit + public static partial class torch { - public sealed class TensorType : Type + public static partial class jit { - internal TensorType(IntPtr handle) : base(handle, TypeKind.TensorType) + public sealed class TensorType : Type { - this.handle = new HType(handle, true, TypeKind.TensorType); - } + internal TensorType(IntPtr handle) : base(handle, TypeKind.TensorType) + { + this.handle = new HType(handle, true, TypeKind.TensorType); + } - internal TensorType(Type type) : base() - { - handle = type.handle; - type.handle = new HType(IntPtr.Zero, true, TypeKind.TensorType); - type.Dispose(); - } + internal TensorType(Type type) : base() + { + handle = type.handle; + type.handle = new HType(IntPtr.Zero, true, TypeKind.TensorType); + type.Dispose(); + } - [DllImport("LibTorchSharp")] - private static extern sbyte THSJIT_TensorType_dtype(HType handle); + [DllImport("LibTorchSharp")] + private static extern sbyte THSJIT_TensorType_dtype(HType handle); - public torch.ScalarType GetScalarType() - { - return (torch.ScalarType)THSJIT_TensorType_dtype(handle); - } + public torch.ScalarType GetScalarType() + { + return (torch.ScalarType)THSJIT_TensorType_dtype(handle); + } - [DllImport("LibTorchSharp")] - static extern long THSJIT_TensorType_sizes(HType handle, AllocatePinnedArray allocator); + [DllImport("LibTorchSharp")] + static extern long THSJIT_TensorType_sizes(HType handle, AllocatePinnedArray allocator); - /// - /// Retrieves the sizes of all dimensions of the tensor. - /// - public long[] size() - { - long[] ptrArray; + /// + /// Retrieves the sizes of all dimensions of the tensor. + /// + public long[] size() + { + long[] ptrArray; - using (var pa = new PinnedArray()) { - THSJIT_TensorType_sizes(handle, pa.CreateArray); - torch.CheckForErrors(); - ptrArray = pa.Array; - } + using (var pa = new PinnedArray()) { + THSJIT_TensorType_sizes(handle, pa.CreateArray); + torch.CheckForErrors(); + ptrArray = pa.Array; + } - return ptrArray; - } + return ptrArray; + } - [DllImport("LibTorchSharp")] - private static extern int THSJIT_getDimensionedTensorTypeDimensions(HType handle); + [DllImport("LibTorchSharp")] + private static extern int THSJIT_getDimensionedTensorTypeDimensions(HType handle); - public int GetDimensions() - { - return THSJIT_getDimensionedTensorTypeDimensions(handle); - } + public int GetDimensions() + { + return THSJIT_getDimensionedTensorTypeDimensions(handle); + } - [DllImport("LibTorchSharp")] - private static extern string THSJIT_getDimensionedTensorDevice(HType handle); + [DllImport("LibTorchSharp")] + private static extern string THSJIT_getDimensionedTensorDevice(HType handle); - public string GetDevice() - { - return THSJIT_getDimensionedTensorDevice(handle); + public string GetDevice() + { + return THSJIT_getDimensionedTensorDevice(handle); + } } } } diff --git a/src/TorchSharp/JIT/Type/Type.cs b/src/TorchSharp/JIT/Type/Type.cs index 46bd923f9..612a09478 100644 --- a/src/TorchSharp/JIT/Type/Type.cs +++ b/src/TorchSharp/JIT/Type/Type.cs @@ -5,118 +5,121 @@ namespace TorchSharp { - public static partial class jit + public static partial class torch { - - public class Type : IDisposable + public static partial class jit { - /// - /// Class wrapping PyTorch's type object reference. - /// - internal sealed class HType : SafeHandle + + public class Type : IDisposable { - public HType(IntPtr preexistingHandle, bool ownsHandle, TypeKind kind) : base(IntPtr.Zero, ownsHandle) + /// + /// Class wrapping PyTorch's type object reference. + /// + internal sealed class HType : SafeHandle { - SetHandle(preexistingHandle); - this.kind = kind; + public HType(IntPtr preexistingHandle, bool ownsHandle, TypeKind kind) : base(IntPtr.Zero, ownsHandle) + { + SetHandle(preexistingHandle); + this.kind = kind; + } + + public override bool IsInvalid => handle == IntPtr.Zero; + + // This is just for marshalling + internal HType() : base(IntPtr.Zero, true) + { + } + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Type_dispose(HType handle); + + [DllImport("LibTorchSharp")] + private static extern void THSJIT_TensorType_dispose(HType handle); + + protected override bool ReleaseHandle() + { + switch (kind) { + case TypeKind.TensorType: + THSJIT_TensorType_dispose(this); + break; + default: + THSJIT_Type_dispose(this); + break; + } + return true; + } + + protected override void Dispose(bool disposing) + { + if (disposing) { + ReleaseHandle(); + } + } + + private TypeKind kind; } - public override bool IsInvalid => handle == IntPtr.Zero; + internal HType handle; - // This is just for marshalling - internal HType() : base(IntPtr.Zero, true) + internal Type(IntPtr handle, TypeKind kind) { + this.handle = new HType(handle, true, kind); } - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Type_dispose(HType handle); + protected Type() + { + } - [DllImport("LibTorchSharp")] - private static extern void THSJIT_TensorType_dispose(HType handle); + ~Type() + { + Dispose(false); + } - protected override bool ReleaseHandle() + /// + /// Releases the storage. + /// + public void Dispose() { - switch (kind) { - case TypeKind.TensorType: - THSJIT_TensorType_dispose(this); - break; - default: - THSJIT_Type_dispose(this); - break; - } - return true; + Dispose(true); + GC.SuppressFinalize(this); } - protected override void Dispose(bool disposing) + /// + /// Implements the .NET Dispose pattern. + /// + protected void Dispose(bool disposing) { if (disposing) { - ReleaseHandle(); + handle.Dispose(); + handle.SetHandleAsInvalid(); } } - private TypeKind kind; - } - - internal HType handle; - - internal Type(IntPtr handle, TypeKind kind) - { - this.handle = new HType(handle, true, kind); - } - - protected Type() - { - } - - ~Type() - { - Dispose(false); - } - - /// - /// Releases the storage. - /// - public void Dispose() - { - Dispose(true); - GC.SuppressFinalize(this); - } + [DllImport("LibTorchSharp")] + private static extern sbyte THSJIT_Type_kind(HType handle); - /// - /// Implements the .NET Dispose pattern. - /// - protected void Dispose(bool disposing) - { - if (disposing) { - handle.Dispose(); - handle.SetHandleAsInvalid(); + internal TypeKind Kind { + get { return (TypeKind)THSJIT_Type_kind(handle); } } - } - - [DllImport("LibTorchSharp")] - private static extern sbyte THSJIT_Type_kind(HType handle); - - internal TypeKind Kind { - get { return (TypeKind)THSJIT_Type_kind(handle); } - } - [DllImport("LibTorchSharp")] - private static extern IntPtr THSJIT_Type_cast(HType module); + [DllImport("LibTorchSharp")] + private static extern IntPtr THSJIT_Type_cast(HType module); - internal TensorType AsTensorType() - { - return new TensorType(THSJIT_Type_cast(handle)); - } + internal TensorType AsTensorType() + { + return new TensorType(THSJIT_Type_cast(handle)); + } - internal DynamicType AsDynamicType() - { - return new DynamicType(THSJIT_Type_cast(handle)); - } + internal DynamicType AsDynamicType() + { + return new DynamicType(THSJIT_Type_cast(handle)); + } - internal enum TypeKind : sbyte - { - AnyType = 0, - TensorType = 3, + internal enum TypeKind : sbyte + { + AnyType = 0, + TensorType = 3, + } } } } diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index d9465293c..b97069be9 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -80,7 +80,7 @@ public void TestSaveLoadLinear3() public void TestLoadJIT_1() { // One linear layer followed by ReLU. - var m = TorchSharp.jit.load(@"linrelu.script.dat"); + var m = torch.jit.load(@"linrelu.script.dat"); var t = m.forward(torch.ones(10)); Assert.Equal(new long[] { 6 }, t.shape); @@ -94,7 +94,7 @@ public void TestLoadJIT_1() public void TestLoadJIT_2() { // One linear layer followed by ReLU. - var m = TorchSharp.jit.load(@"scripted.script.dat"); + var m = torch.jit.load(@"scripted.script.dat"); var t = m.forward(torch.ones(6)); Assert.Equal(new long[] { 6 }, t.shape); @@ -108,7 +108,7 @@ public void TestLoadJIT_2() public void TestLoadJIT_3() { // Two linear layers, nested Sequential, ReLU in between. - var m = TorchSharp.jit.load(@"l1000_100_10.script.dat"); + var m = torch.jit.load(@"l1000_100_10.script.dat"); var sms = m.named_modules().ToArray(); Assert.Equal(5, sms.Length); @@ -130,7 +130,7 @@ public void TestSaveLoadJITCUDA() { if (torch.cuda.is_available()) { - var m = TorchSharp.jit.load(@"linrelu.script.dat"); + var m = torch.jit.load(@"linrelu.script.dat"); m.to(DeviceType.CUDA); var params0 = m.parameters().ToArray(); diff --git a/test/TorchSharpTest/TestTraining.cs b/test/TorchSharpTest/TestTraining.cs index 251885618..fbdee3492 100644 --- a/test/TorchSharpTest/TestTraining.cs +++ b/test/TorchSharpTest/TestTraining.cs @@ -1671,7 +1671,7 @@ public void TestTrainingLoadedTorchScript() var gen = new Generator(4711); CreateDataAndLabels(gen, out var x, out var y); - var seq = TorchSharp.jit.load(@"l1000_100_10.script.dat"); + var seq = torch.jit.load(@"l1000_100_10.script.dat"); double learning_rate = 0.00004f; var optimizer = torch.optim.SGD(seq.parameters(), learning_rate); From f847569c0225c1df58993f767201fb0a9f13f5a7 Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Fri, 1 Jul 2022 18:11:10 -0700 Subject: [PATCH 05/12] Update RELEASE NOTES --- RELEASENOTES.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/RELEASENOTES.md b/RELEASENOTES.md index 29eee08f3..a092d4cd1 100644 --- a/RELEASENOTES.md +++ b/RELEASENOTES.md @@ -11,7 +11,7 @@ __API Changes__: Add torch.utils.rnn
Add torchvision.io
Add Tensor.trace() and torch.trace() (unrelated to torch.jit.trace)
-Add ability to load modules that were traced using torch.jit.trace() in Pytorch
+Add ability to load TorchScript modules created using Pytorch
## NuGet Version 0.96.8 From b3d217215286e4c664a3edc22e8f33c53c2c2c69 Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Fri, 1 Jul 2022 18:12:41 -0700 Subject: [PATCH 06/12] Disabled input and output type retrieval for ScriptModule --- src/TorchSharp/JIT/ScriptModule.cs | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index d0a693ed6..afc39c229 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -266,7 +266,7 @@ public override nn.Module to(ScalarType dtype) return this; } -#if true // These functions "work," but the native code doesn't seem to find any interesting information. +#if false // These functions "work," but the native code doesn't seem to find any interesting information. [DllImport("LibTorchSharp")] private static extern IntPtr THSJIT_Module_getInputType(HType module, int index); From 5a3cc16ab8ceaef5dc28121aa83406d8af23a0f0 Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Fri, 1 Jul 2022 18:56:14 -0700 Subject: [PATCH 07/12] Fixed unit test and leftovers from debugging. --- src/TorchSharp/JIT/ScriptModule.cs | 24 ------------------------ test/TorchSharpTest/TestLoadSave.cs | 6 +++--- 2 files changed, 3 insertions(+), 27 deletions(-) diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index afc39c229..2acbbd3e9 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -24,30 +24,6 @@ internal ScriptModule(IntPtr handle) : base(new HType(handle, true), null) Dispose(false); } - /// - /// Implements the .NET Dispose pattern. - /// - protected override void Dispose(bool disposing) - { - if (disposing && !handle.IsInvalid) { - - //foreach (var (_, p) in named_buffers(false)) { - // p.Dispose(); - //} - //foreach (var (_, b) in named_parameters(false)) { - // b.Dispose(); - //} - - //foreach (var (_, m) in named_modules()) { - // m.Dispose(); - //} - - handle.Dispose(); - handle.SetHandleAsInvalid(); - boxedModule?.Dispose(); - } - } - [DllImport("LibTorchSharp")] private static extern void THSJIT_Module_named_parameters(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index b97069be9..b6268b34c 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -85,7 +85,7 @@ public void TestLoadJIT_1() Assert.Equal(new long[] { 6 }, t.shape); Assert.Equal(torch.float32, t.dtype); - Assert.Equal(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }, t.data().ToArray()); + Assert.True(torch.tensor(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }).allclose(t)); m.Dispose(); } @@ -99,7 +99,7 @@ public void TestLoadJIT_2() Assert.Equal(new long[] { 6 }, t.shape); Assert.Equal(torch.float32, t.dtype); - Assert.Equal(new float[] { 1.554085f, 1.01024628f, -1.35086036f, -1.84021854f, 0.0127189457f, 0.5994258f }, t.data().ToArray()); + Assert.True(torch.tensor(new float[] { 1.554085f, 1.01024628f, -1.35086036f, -1.84021854f, 0.0127189457f, 0.5994258f }).allclose(t)); m.Dispose(); } @@ -120,7 +120,7 @@ public void TestLoadJIT_3() Assert.Equal(new long[] { 10 }, t.shape); Assert.Equal(torch.float32, t.dtype); - Assert.Equal(new float[] { 0.564213157f, -0.04519982f, -0.005117342f, 0.395530462f, -0.3780813f, -0.004734449f, -0.3221216f, -0.289159119f, 0.268511474f, 0.180702567f }, t.data().ToArray()); + Assert.True(torch.tensor(new float[] { 0.564213157f, -0.04519982f, -0.005117342f, 0.395530462f, -0.3780813f, -0.004734449f, -0.3221216f, -0.289159119f, 0.268511474f, 0.180702567f }).allclose(t)); m.Dispose(); } From 00e3c02d3bdae74ec5938870f4821615888d613b Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Sat, 2 Jul 2022 10:34:12 -0700 Subject: [PATCH 08/12] ScriptModule.named_modules() must rule out the "" module. --- src/Native/LibTorchSharp/THSJIT.cpp | 16 ++++++++++------ src/TorchSharp/JIT/ScriptModule.cs | 8 ++++++-- src/TorchSharp/JIT/Type/Type.cs | 7 ------- test/TorchSharpTest/TestLoadSave.cs | 9 ++++++++- test/TorchSharpTest/TorchSharpTest.csproj | 3 +++ 5 files changed, 27 insertions(+), 16 deletions(-) diff --git a/src/Native/LibTorchSharp/THSJIT.cpp b/src/Native/LibTorchSharp/THSJIT.cpp index 050dabfb0..6d426a4b0 100644 --- a/src/Native/LibTorchSharp/THSJIT.cpp +++ b/src/Native/LibTorchSharp/THSJIT.cpp @@ -3,9 +3,13 @@ JITModule THSJIT_load(const char* filename) { - auto res = torch::jit::load(filename); - auto copy = new torch::jit::Module(res); - return new std::shared_ptr(copy); + CATCH( + auto res = torch::jit::load(filename); + auto copy = new torch::jit::Module(res); + return new std::shared_ptr(copy); + ); + + return nullptr; } int THSJIT_Module_is_training(JITModule module) @@ -148,7 +152,7 @@ int THSJIT_Method_num_inputs(const JITMethod method) int THSJIT_Module_num_inputs(const JITModule module) { - return (int)(*module)->get_method("forward").num_inputs()-1; // Don't count the 'self' argument. + return (int)(*module)->get_method("forward").num_inputs() - 1; // Don't count the 'self' argument. } int THSJIT_Module_num_outputs(const JITModule module) @@ -225,8 +229,8 @@ void THSJIT_TensorType_sizes(const JITTensorType type, int64_t* (*allocator)(int if (res.has_value()) { const size_t sz = res.value().size(); auto& vec = res.value(); - int64_t * result = allocator(sz); - for (size_t i = 0; i < sz; i++) + int64_t* result = allocator(sz); + for (size_t i = 0; i < sz; i++) result[i] = vec[i]; } //); diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index 2acbbd3e9..0755b27b9 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -66,7 +66,7 @@ protected override (string name, Tensor buffer)[] _named_buffers() var ptrArray = pa.Array; var strArray = sa.Array; - return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)); + return ptrArray.Select((x, i) => (Marshal.PtrToStringAnsi(strArray[i]), new ScriptModule(x) as nn.Module)).Where(m => !String.IsNullOrEmpty(m.Item1)); } [DllImport("LibTorchSharp")] @@ -300,7 +300,11 @@ public static ScriptModule load(string filename) { if (!System.IO.File.Exists(filename)) throw new System.IO.FileNotFoundException(filename); - return new ScriptModule(THSJIT_load(filename)); + + var result = THSJIT_load(filename); + if (result == IntPtr.Zero) + CheckForErrors(); + return new ScriptModule(result); } diff --git a/src/TorchSharp/JIT/Type/Type.cs b/src/TorchSharp/JIT/Type/Type.cs index 612a09478..33725a156 100644 --- a/src/TorchSharp/JIT/Type/Type.cs +++ b/src/TorchSharp/JIT/Type/Type.cs @@ -49,13 +49,6 @@ protected override bool ReleaseHandle() return true; } - protected override void Dispose(bool disposing) - { - if (disposing) { - ReleaseHandle(); - } - } - private TypeKind kind; } diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index b6268b34c..c2d693ea7 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -111,7 +111,7 @@ public void TestLoadJIT_3() var m = torch.jit.load(@"l1000_100_10.script.dat"); var sms = m.named_modules().ToArray(); - Assert.Equal(5, sms.Length); + Assert.Equal(4, sms.Length); var kids = m.named_children().ToArray(); Assert.Equal(2, kids.Length); @@ -125,6 +125,13 @@ public void TestLoadJIT_3() m.Dispose(); } + [Fact] + public void TestLoadJIT_4() + { + // Definitely not a TorchScript file. Let's see what the runtime does with it. + Assert.Throws(() => torch.jit.load(@"torch.dll")); + } + [Fact] public void TestSaveLoadJITCUDA() { diff --git a/test/TorchSharpTest/TorchSharpTest.csproj b/test/TorchSharpTest/TorchSharpTest.csproj index a23b8f447..73e7e9aba 100644 --- a/test/TorchSharpTest/TorchSharpTest.csproj +++ b/test/TorchSharpTest/TorchSharpTest.csproj @@ -32,6 +32,9 @@ PreserveNewest + + PreserveNewest + PreserveNewest From 9571402c6986a4b87506510bc65506a117a05cad Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Sat, 2 Jul 2022 11:20:48 -0700 Subject: [PATCH 09/12] Replaced a boolean flag with a more general delegate. --- src/TorchSharp/JIT/ScriptModule.cs | 5 ++- src/TorchSharp/NN/Module.cs | 14 +++----- test/TorchSharpTest/TestLoadSave.cs | 51 ++++++++++++----------------- 3 files changed, 29 insertions(+), 41 deletions(-) diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index 0755b27b9..c8485b2c5 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -15,7 +15,7 @@ public static partial class jit { public class ScriptModule : torch.nn.Module { - internal ScriptModule(IntPtr handle) : base(new HType(handle, true), null) + internal ScriptModule(IntPtr handle) : base(new HType(handle, true, THSJIT_Module_dispose), null) { } @@ -24,6 +24,9 @@ internal ScriptModule(IntPtr handle) : base(new HType(handle, true), null) Dispose(false); } + [DllImport("LibTorchSharp")] + private static extern void THSJIT_Module_dispose(HType handle); + [DllImport("LibTorchSharp")] private static extern void THSJIT_Module_named_parameters(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); diff --git a/src/TorchSharp/NN/Module.cs b/src/TorchSharp/NN/Module.cs index 2e949250f..fde92471e 100644 --- a/src/TorchSharp/NN/Module.cs +++ b/src/TorchSharp/NN/Module.cs @@ -31,10 +31,10 @@ public class Module : IDisposable /// internal sealed class HType : SafeHandle { - public HType(IntPtr preexistingHandle, bool ownsHandle, bool script = false) + public HType(IntPtr preexistingHandle, bool ownsHandle, Action dispose = null) : base(IntPtr.Zero, ownsHandle) { - isScriptModule = script; + _dispose = dispose??THSNN_Module_dispose; SetHandle(preexistingHandle); } @@ -47,17 +47,11 @@ internal HType() : base(IntPtr.Zero, true) [DllImport("LibTorchSharp")] private static extern void THSNN_Module_dispose(HType handle); - [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_dispose(HType handle); protected override bool ReleaseHandle() { if (!IsInvalid) { - if (isScriptModule) { - THSJIT_Module_dispose(this); - } else { - THSNN_Module_dispose(this); - } + _dispose(this); } SetHandle(IntPtr.Zero); return true; @@ -70,7 +64,7 @@ protected override void Dispose(bool disposing) } } - private bool isScriptModule; + private Action _dispose; } internal HType handle; diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index c2d693ea7..e2a0430c8 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -60,7 +60,7 @@ public void TestSaveLoadLinear2() public void TestSaveLoadLinear3() { if (File.Exists(".model.ts")) File.Delete(".model.ts"); - var linear = Linear(100, 10, true); + using var linear = Linear(100, 10, true); var params0 = linear.parameters(); linear.save(".model.ts"); @@ -75,40 +75,35 @@ public void TestSaveLoadLinear3() Assert.Equal(params0.Skip(1).First(), params2.Skip(1).First()); } - [Fact] public void TestLoadJIT_1() { // One linear layer followed by ReLU. - var m = torch.jit.load(@"linrelu.script.dat"); + using var m = torch.jit.load(@"linrelu.script.dat"); var t = m.forward(torch.ones(10)); Assert.Equal(new long[] { 6 }, t.shape); Assert.Equal(torch.float32, t.dtype); Assert.True(torch.tensor(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }).allclose(t)); - - m.Dispose(); } [Fact] public void TestLoadJIT_2() { // One linear layer followed by ReLU. - var m = torch.jit.load(@"scripted.script.dat"); + using var m = torch.jit.load(@"scripted.script.dat"); var t = m.forward(torch.ones(6)); Assert.Equal(new long[] { 6 }, t.shape); Assert.Equal(torch.float32, t.dtype); Assert.True(torch.tensor(new float[] { 1.554085f, 1.01024628f, -1.35086036f, -1.84021854f, 0.0127189457f, 0.5994258f }).allclose(t)); - - m.Dispose(); } [Fact] public void TestLoadJIT_3() { // Two linear layers, nested Sequential, ReLU in between. - var m = torch.jit.load(@"l1000_100_10.script.dat"); + using var m = torch.jit.load(@"l1000_100_10.script.dat"); var sms = m.named_modules().ToArray(); Assert.Equal(4, sms.Length); @@ -121,8 +116,6 @@ public void TestLoadJIT_3() Assert.Equal(new long[] { 10 }, t.shape); Assert.Equal(torch.float32, t.dtype); Assert.True(torch.tensor(new float[] { 0.564213157f, -0.04519982f, -0.005117342f, 0.395530462f, -0.3780813f, -0.004734449f, -0.3221216f, -0.289159119f, 0.268511474f, 0.180702567f }).allclose(t)); - - m.Dispose(); } [Fact] @@ -137,7 +130,7 @@ public void TestSaveLoadJITCUDA() { if (torch.cuda.is_available()) { - var m = torch.jit.load(@"linrelu.script.dat"); + using var m = torch.jit.load(@"linrelu.script.dat"); m.to(DeviceType.CUDA); var params0 = m.parameters().ToArray(); @@ -149,8 +142,6 @@ public void TestSaveLoadJITCUDA() Assert.Equal(new long[] { 6 }, t.shape); Assert.Equal(torch.float32, t.dtype); Assert.Equal(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }, t.data().ToArray()); - - m.Dispose(); } } @@ -158,10 +149,10 @@ public void TestSaveLoadJITCUDA() public void TestSaveLoadConv2D() { if (File.Exists(".model.ts")) File.Delete(".model.ts"); - var conv = Conv2d(100, 10, 5); + using var conv = Conv2d(100, 10, 5); var params0 = conv.parameters(); conv.save(".model.ts"); - var loaded = Conv2d(100, 10, 5); + using var loaded = Conv2d(100, 10, 5); loaded.load(".model.ts"); var params1 = loaded.parameters(); File.Delete(".model.ts"); @@ -172,12 +163,12 @@ public void TestSaveLoadConv2D() [Fact] public void TestSaveLoadConv2D_sd() { - var conv = Conv2d(100, 10, 5); + using var conv = Conv2d(100, 10, 5); var params0 = conv.parameters(); var sd = conv.state_dict(); - var loaded = Conv2d(100, 10, 5); + using var loaded = Conv2d(100, 10, 5); Assert.NotEqual(params0, loaded.parameters()); loaded.load_state_dict(sd); @@ -188,10 +179,10 @@ public void TestSaveLoadConv2D_sd() public void TestSaveLoadSequential() { if (File.Exists(".model.ts")) File.Delete(".model.ts"); - var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); var params0 = conv.parameters(); conv.save(".model.ts"); - var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); loaded.load(".model.ts"); var params1 = loaded.parameters(); File.Delete(".model.ts"); @@ -202,12 +193,12 @@ public void TestSaveLoadSequential() [Fact] public void TestSaveLoadSequential_sd() { - var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); var params0 = conv.parameters(); var sd = conv.state_dict(); - var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); Assert.NotEqual(params0, loaded.parameters()); loaded.load_state_dict(sd); @@ -217,13 +208,13 @@ public void TestSaveLoadSequential_sd() [Fact] public void TestSaveLoadSequential_error1() { - var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); var params0 = conv.parameters(); var sd = conv.state_dict(); sd.Remove("0.bias"); - var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); Assert.NotEqual(params0, loaded.parameters()); Assert.Throws(() => loaded.load_state_dict(sd)); @@ -232,7 +223,7 @@ public void TestSaveLoadSequential_error1() [Fact] public void TestSaveLoadSequential_error2() { - var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); var params0 = conv.parameters(); var sd = conv.state_dict(); @@ -240,7 +231,7 @@ public void TestSaveLoadSequential_error2() sd.Add("2.bias", t); - var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); Assert.NotEqual(params0, loaded.parameters()); Assert.Throws(() => loaded.load_state_dict(sd)); @@ -249,7 +240,7 @@ public void TestSaveLoadSequential_error2() [Fact] public void TestSaveLoadSequential_lax() { - var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var conv = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); var params0 = conv.parameters(); var sd = conv.state_dict(); @@ -258,7 +249,7 @@ public void TestSaveLoadSequential_lax() sd.Add("2.bias", t); - var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); + using var loaded = Sequential(Conv2d(100, 10, 5), Linear(100, 10, true)); Assert.NotEqual(params0, loaded.parameters()); var (m,u) = loaded.load_state_dict(sd, false); @@ -273,14 +264,14 @@ public void TestSaveLoadCustomWithParameters() { if (File.Exists(".model.ts")) File.Delete(".model.ts"); - var original = new TestModule1(); + using var original = new TestModule1(); Assert.True(original.has_parameter("test")); var params0 = original.parameters(); Assert.True(params0.ToArray().ToArray()[0].requires_grad); original.save(".model.ts"); - var loaded = new TestModule1(); + using var loaded = new TestModule1(); Assert.True(loaded.has_parameter("test")); var params1 = loaded.parameters(); From 59bb7c8b48b3eb3d50be79a21de31fefcb14425b Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Sat, 2 Jul 2022 12:42:23 -0700 Subject: [PATCH 10/12] Adding torch.jit.save and unit test, updated the release notes. Adding article on torchscript. --- RELEASENOTES.md | 2 +- docfx/articles/torchscript.md | 25 +++++++++++++++++++++++++ docfx/index.md | 10 +++------- src/Native/LibTorchSharp/THSJIT.cpp | 9 ++++++++- src/Native/LibTorchSharp/THSJIT.h | 2 ++ src/TorchSharp/JIT/ScriptModule.cs | 24 +++++++++++++++++++++++- test/TorchSharpTest/TestLoadSave.cs | 24 +++++++++++++++++++++++- 7 files changed, 85 insertions(+), 11 deletions(-) create mode 100644 docfx/articles/torchscript.md diff --git a/RELEASENOTES.md b/RELEASENOTES.md index a092d4cd1..0e4a9a4b5 100644 --- a/RELEASENOTES.md +++ b/RELEASENOTES.md @@ -11,7 +11,7 @@ __API Changes__: Add torch.utils.rnn
Add torchvision.io
Add Tensor.trace() and torch.trace() (unrelated to torch.jit.trace)
-Add ability to load TorchScript modules created using Pytorch
+Add ability to load and save TorchScript modules created using Pytorch
## NuGet Version 0.96.8 diff --git a/docfx/articles/torchscript.md b/docfx/articles/torchscript.md new file mode 100644 index 000000000..4a53753ba --- /dev/null +++ b/docfx/articles/torchscript.md @@ -0,0 +1,25 @@ +# Loading TorchScript Modules + +Starting with release 0.96.9, you can load TorchScript modules (but not yet TorchScript functions) that have been either traced or scripted in Pytorch. It is, however, not yet possible to create a TorchScript module from scratch using TorchSharp. Refer to the [Pytorch JIT](https://pytorch.org/docs/stable/jit.html) docs for information on how to create such a file. + +TorchScript is very powerful, because it allows you to save the logic and the weights of a model together, and it furthermore allows the module to be loaded into another program, __without any dependencies on the Python runtime.__ Thus, you can load a model that has been serialized using TorchScript and have it behave as any TorchScript module -- you can use it for training, or you can use it for inference. + +Once you have a TorchScript file, you can load it into TorchSharp using: + +```C# +var m = torch.jit.load("file-name"); +``` + +It returns a ScriptModule, which behaves just like any other TorchSharp module. You can use it for training of inference by calling either `train()` or `eval()`. ScriptModules always start out on the CPU, so you have to call `cuda()` in order to move it to a GPU. + +Note that if you used __tracing__ to create the TorchScript file in Pytorch, submodules that behave differently in training and eval modes will behave according to the mode they were traced in. + +If you use the script module to train, you may want / need to save it afterwards. + +That is easily done using `save()`: + +```C# +torch.jit.save(m, "file-name"); +``` + +While it is possible to save a modified ScriptModule from TorchSharp, it is not (yet) possible to create one _from scratch_ using either tracing or scripting. diff --git a/docfx/index.md b/docfx/index.md index 30701ffd2..e7dda7beb 100644 --- a/docfx/index.md +++ b/docfx/index.md @@ -1,10 +1,9 @@ -TorchSharp are .NET bindings to the Torch library published -here: +TorchSharp are .NET bindings to the Torch library published here: https://pytorch.org/get-started/locally/ -This surfaces the C API as a strongly-typed C# API. +This surfaces the C++ library as a strongly-typed .NET API. ## Getting Started @@ -18,7 +17,4 @@ Then, start by reading up on [creating your own modules](articles/modules.md). An intruction on how to [share model](articles/saveload.md) weights between applications, whether in Python or .NET. - -## API documentation - -The [API Documentation](api/TorchSharp.html) \ No newline at end of file +Loading existing TorchScript files is now supported and described in [Loading TorchScript](articles/torchscript.md). diff --git a/src/Native/LibTorchSharp/THSJIT.cpp b/src/Native/LibTorchSharp/THSJIT.cpp index 6d426a4b0..3485ff8a3 100644 --- a/src/Native/LibTorchSharp/THSJIT.cpp +++ b/src/Native/LibTorchSharp/THSJIT.cpp @@ -5,13 +5,20 @@ JITModule THSJIT_load(const char* filename) { CATCH( auto res = torch::jit::load(filename); - auto copy = new torch::jit::Module(res); + auto copy = new torch::jit::Module(res); return new std::shared_ptr(copy); ); return nullptr; } +void THSJIT_save(JITModule module, const char* filename) +{ + CATCH( + (*module)->save(filename); + ); +} + int THSJIT_Module_is_training(JITModule module) { return (*module)->is_training(); diff --git a/src/Native/LibTorchSharp/THSJIT.h b/src/Native/LibTorchSharp/THSJIT.h index e4232b616..a9d2b4a47 100644 --- a/src/Native/LibTorchSharp/THSJIT.h +++ b/src/Native/LibTorchSharp/THSJIT.h @@ -18,6 +18,8 @@ enum TypeKind : int8_t { EXPORT_API(JITModule) THSJIT_load(const char* filename); +EXPORT_API(void) THSJIT_save(JITModule module, const char* filename); + EXPORT_API(void) THSJIT_Module_dispose(const JITModule module); EXPORT_API(int) THSJIT_Module_num_inputs(const JITModule method); diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index c8485b2c5..22dd88088 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -291,7 +291,21 @@ public unsafe override Tensor forward(Tensor tensor) { using (var parray = new PinnedArray()) { IntPtr tensorRefs = parray.CreateArray(new[] { tensor.Handle }); - return new Tensor(THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length)); + var res = THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length); + if (res == IntPtr.Zero) + CheckForErrors(); + return new Tensor(res); + } + } + + public unsafe override Tensor forward(Tensor tensor1, Tensor tensor2) + { + using (var parray = new PinnedArray()) { + IntPtr tensorRefs = parray.CreateArray(new[] { tensor1.Handle, tensor2.Handle }); + var res = THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length); + if (res == IntPtr.Zero) + CheckForErrors(); + return new Tensor(res); } } } @@ -310,6 +324,14 @@ public static ScriptModule load(string filename) return new ScriptModule(result); } + [DllImport("LibTorchSharp")] + private static extern void THSJIT_save(nn.Module.HType handle, string filename); + + public static void save(ScriptModule module, string filename) + { + THSJIT_save(module.handle, filename); + CheckForErrors(); + } } } diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index e2a0430c8..bce9c8153 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -87,6 +87,26 @@ public void TestLoadJIT_1() Assert.True(torch.tensor(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }).allclose(t)); } + [Fact] + public void TestSaveJIT() + { + if (File.Exists(".model.ts")) File.Delete(".model.ts"); + + // One linear layer followed by ReLU. + using var m1 = torch.jit.load(@"linrelu.script.dat"); + + torch.jit.save(m1, ".model.ts"); + using var m2 = torch.jit.load(@".model.ts"); + + var t = m2.forward(torch.ones(10)); + + Assert.Equal(new long[] { 6 }, t.shape); + Assert.Equal(torch.float32, t.dtype); + Assert.True(torch.tensor(new float[] { 0.313458264f, 0, 0.9996568f, 0, 0, 0 }).allclose(t)); + + if (File.Exists(".model.ts")) File.Delete(".model.ts"); + } + [Fact] public void TestLoadJIT_2() { @@ -116,13 +136,15 @@ public void TestLoadJIT_3() Assert.Equal(new long[] { 10 }, t.shape); Assert.Equal(torch.float32, t.dtype); Assert.True(torch.tensor(new float[] { 0.564213157f, -0.04519982f, -0.005117342f, 0.395530462f, -0.3780813f, -0.004734449f, -0.3221216f, -0.289159119f, 0.268511474f, 0.180702567f }).allclose(t)); + + Assert.Throws(() => m.forward(torch.ones(100))); } [Fact] public void TestLoadJIT_4() { // Definitely not a TorchScript file. Let's see what the runtime does with it. - Assert.Throws(() => torch.jit.load(@"torch.dll")); + Assert.Throws(() => torch.jit.load(@"bug510.dat")); } [Fact] From 40cac593a2c55909a78361a24450b38ce54037ca Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Sat, 2 Jul 2022 15:12:14 -0700 Subject: [PATCH 11/12] Added more overloads for forward(). Added unit test for a script module formed from a function in Pytorch. --- docfx/articles/torchscript.md | 6 +- src/TorchSharp/JIT/ScriptModule.cs | 54 +++++++++++++++++- src/TorchSharp/NN/EmbeddingBag.cs | 2 +- src/TorchSharp/NN/Module.cs | 3 + src/TorchSharp/NN/TransformerEncoder.cs | 2 +- src/TorchSharp/NN/TransformerEncoderLayer.cs | 2 +- .../TorchSharpTest.WithCudaBinaries.csproj | 3 + test/TorchSharpTest/TestLoadSave.cs | 21 +++++++ test/TorchSharpTest/TorchSharpTest.csproj | 3 + test/TorchSharpTest/func.script.dat | Bin 0 -> 1334 bytes 10 files changed, 87 insertions(+), 9 deletions(-) create mode 100644 test/TorchSharpTest/func.script.dat diff --git a/docfx/articles/torchscript.md b/docfx/articles/torchscript.md index 4a53753ba..d86378577 100644 --- a/docfx/articles/torchscript.md +++ b/docfx/articles/torchscript.md @@ -1,6 +1,6 @@ # Loading TorchScript Modules -Starting with release 0.96.9, you can load TorchScript modules (but not yet TorchScript functions) that have been either traced or scripted in Pytorch. It is, however, not yet possible to create a TorchScript module from scratch using TorchSharp. Refer to the [Pytorch JIT](https://pytorch.org/docs/stable/jit.html) docs for information on how to create such a file. +Starting with release 0.96.9, you can load TorchScript modules and functions that have been either traced or scripted in Pytorch. It is, however, not yet possible to create a TorchScript module from scratch using TorchSharp. Refer to the [Pytorch JIT](https://pytorch.org/docs/stable/jit.html) docs for information on how to create such a file. TorchScript is very powerful, because it allows you to save the logic and the weights of a model together, and it furthermore allows the module to be loaded into another program, __without any dependencies on the Python runtime.__ Thus, you can load a model that has been serialized using TorchScript and have it behave as any TorchScript module -- you can use it for training, or you can use it for inference. @@ -10,7 +10,7 @@ Once you have a TorchScript file, you can load it into TorchSharp using: var m = torch.jit.load("file-name"); ``` -It returns a ScriptModule, which behaves just like any other TorchSharp module. You can use it for training of inference by calling either `train()` or `eval()`. ScriptModules always start out on the CPU, so you have to call `cuda()` in order to move it to a GPU. +It returns a ScriptModule, which behaves just like any other TorchSharp module. Whether the original script came from a module or a function, it is deserialized as a module. You can use it for training of inference by calling either `train()` or `eval()`. ScriptModules always start out on the CPU, so you have to call `cuda()` in order to move it to a GPU. Note that if you used __tracing__ to create the TorchScript file in Pytorch, submodules that behave differently in training and eval modes will behave according to the mode they were traced in. @@ -22,4 +22,4 @@ That is easily done using `save()`: torch.jit.save(m, "file-name"); ``` -While it is possible to save a modified ScriptModule from TorchSharp, it is not (yet) possible to create one _from scratch_ using either tracing or scripting. +While it is possible to save a modified ScriptModule from TorchSharp, it is not (yet) possible to create one _from scratch_ using either tracing or scripting. Another limitation is that the TorchSharp code assumes that the `forward()` function takes only tensors as its arguments and returns a single tensor, a limitation it shares with other TorchSharp modules. diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index 22dd88088..729a6c141 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -287,21 +287,69 @@ private Type GetType(Type type) [DllImport("LibTorchSharp")] private static extern IntPtr THSJIT_Module_forward(HType module, IntPtr tensors, int length); + /// + /// Invoke the 'forward' function of the script with one tensor as its argument + /// + /// The input tensor + /// public unsafe override Tensor forward(Tensor tensor) { using (var parray = new PinnedArray()) { IntPtr tensorRefs = parray.CreateArray(new[] { tensor.Handle }); - var res = THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length); + var res = THSJIT_Module_forward(handle, tensorRefs, 1); + if (res == IntPtr.Zero) + CheckForErrors(); + return new Tensor(res); + } + } + + /// + /// Invoke the 'forward' function of the script with two tensors as its argument + /// + /// The first input tensor + /// The second input tensor + /// + public unsafe override Tensor forward(Tensor x, Tensor y) + { + using (var parray = new PinnedArray()) { + IntPtr tensorRefs = parray.CreateArray(new[] { x.Handle, y.Handle }); + var res = THSJIT_Module_forward(handle, tensorRefs, 2); if (res == IntPtr.Zero) CheckForErrors(); return new Tensor(res); } } - public unsafe override Tensor forward(Tensor tensor1, Tensor tensor2) + /// + /// Invoke the 'forward' function of the script with three tensors as its argument + /// + /// The first input tensor + /// The second input tensor + /// The third input tensor + /// + public unsafe override Tensor forward(Tensor x, Tensor y, Tensor z) + { + using (var parray = new PinnedArray()) { + IntPtr tensorRefs = parray.CreateArray(new[] { x.Handle, y.Handle, z.Handle }); + var res = THSJIT_Module_forward(handle, tensorRefs, 3); + if (res == IntPtr.Zero) + CheckForErrors(); + return new Tensor(res); + } + } + + /// + /// Invoke the 'forward' function of the script with four or more tensors as its argument + /// + /// The first input tensor + /// The second input tensor + /// The third input tensor + /// The remaining tensors. + /// + public unsafe Tensor forward(Tensor x, Tensor y, Tensor z, params Tensor[] tensors) { using (var parray = new PinnedArray()) { - IntPtr tensorRefs = parray.CreateArray(new[] { tensor1.Handle, tensor2.Handle }); + IntPtr tensorRefs = parray.CreateArray(new[] { x, y, z }.Concat(tensors).Select(t => t.Handle).ToArray()); var res = THSJIT_Module_forward(handle, tensorRefs, parray.Array.Length); if (res == IntPtr.Zero) CheckForErrors(); diff --git a/src/TorchSharp/NN/EmbeddingBag.cs b/src/TorchSharp/NN/EmbeddingBag.cs index 122efd956..e6c0ff42d 100644 --- a/src/TorchSharp/NN/EmbeddingBag.cs +++ b/src/TorchSharp/NN/EmbeddingBag.cs @@ -32,7 +32,7 @@ internal EmbeddingBag(IntPtr handle, IntPtr boxedHandle) : base(handle, boxedHan /// If specified, per_sample_weights must have exactly the same shape as input and is treated as having the same offsets, if those are not None. /// Only supported for mode='sum'. /// - public Tensor forward(Tensor input, Tensor offsets, Tensor perSampleWeights) + public override Tensor forward(Tensor input, Tensor offsets, Tensor perSampleWeights) { if (!input.IsIntegral()) throw new ArgumentException("Embedding input must be an integral tensor."); if (!(offsets is null) && input.dtype != offsets.dtype) throw new ArgumentException("input and offsets must have the same element type."); diff --git a/src/TorchSharp/NN/Module.cs b/src/TorchSharp/NN/Module.cs index fde92471e..30d8d1934 100644 --- a/src/TorchSharp/NN/Module.cs +++ b/src/TorchSharp/NN/Module.cs @@ -748,6 +748,9 @@ public virtual Tensor forward(Tensor t) public virtual Tensor forward(Tensor x, Tensor y) => throw new NotImplementedException("forward(x,y)"); + public virtual Tensor forward(Tensor x, Tensor y, Tensor z) + => throw new NotImplementedException("forward(x,y,z)"); + /// /// Save the parameters and buffers of the module to a disk location. /// diff --git a/src/TorchSharp/NN/TransformerEncoder.cs b/src/TorchSharp/NN/TransformerEncoder.cs index 46858a39a..84b1f05a7 100644 --- a/src/TorchSharp/NN/TransformerEncoder.cs +++ b/src/TorchSharp/NN/TransformerEncoder.cs @@ -29,7 +29,7 @@ internal TransformerEncoder(IntPtr handle, IntPtr boxedHandle) : base(handle, bo /// The additive mask for the src sequence (optional). /// The ByteTensor mask for src keys per batch (optional). /// - public Tensor forward(Tensor src, Tensor src_mask, Tensor src_key_padding_mask) + public override Tensor forward(Tensor src, Tensor src_mask, Tensor src_key_padding_mask) { var res = THSNN_TransformerEncoder_forward(handle, src.Handle, diff --git a/src/TorchSharp/NN/TransformerEncoderLayer.cs b/src/TorchSharp/NN/TransformerEncoderLayer.cs index 4567599da..ae40d83d4 100644 --- a/src/TorchSharp/NN/TransformerEncoderLayer.cs +++ b/src/TorchSharp/NN/TransformerEncoderLayer.cs @@ -23,7 +23,7 @@ internal TransformerEncoderLayer(IntPtr handle, IntPtr boxedHandle) : base(handl /// The additive mask for the src sequence (optional). /// The ByteTensor mask for src keys per batch (optional). /// - public Tensor forward(Tensor src, Tensor src_mask, Tensor src_key_padding_mask) + public override Tensor forward(Tensor src, Tensor src_mask, Tensor src_key_padding_mask) { var res = THSNN_TransformerEncoderLayer_forward(handle, src.Handle, diff --git a/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj b/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj index 8f2fc3f91..eb145cbb2 100644 --- a/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj +++ b/test/TorchSharpTest.WithCudaBinaries/TorchSharpTest.WithCudaBinaries.csproj @@ -52,6 +52,9 @@ + + PreserveNewest + PreserveNewest diff --git a/test/TorchSharpTest/TestLoadSave.cs b/test/TorchSharpTest/TestLoadSave.cs index bce9c8153..f615240ac 100644 --- a/test/TorchSharpTest/TestLoadSave.cs +++ b/test/TorchSharpTest/TestLoadSave.cs @@ -75,6 +75,27 @@ public void TestSaveLoadLinear3() Assert.Equal(params0.Skip(1).First(), params2.Skip(1).First()); } + + + [Fact] + public void TestLoadJIT_Func() + { + // One linear layer followed by ReLU. + using var m = torch.jit.load(@"func.script.dat"); + + var sms = m.named_modules().ToArray(); + Assert.Empty(sms); + + var kids = m.named_children().ToArray(); + Assert.Empty(kids); + + var t = m.forward(torch.ones(10), torch.ones(10)); + + Assert.Equal(new long[] { 10 }, t.shape); + Assert.Equal(torch.float32, t.dtype); + Assert.True(torch.tensor(new float[] { 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 }).allclose(t)); + } + [Fact] public void TestLoadJIT_1() { diff --git a/test/TorchSharpTest/TorchSharpTest.csproj b/test/TorchSharpTest/TorchSharpTest.csproj index 73e7e9aba..ab3fb075b 100644 --- a/test/TorchSharpTest/TorchSharpTest.csproj +++ b/test/TorchSharpTest/TorchSharpTest.csproj @@ -29,6 +29,9 @@ PreserveNewest + + PreserveNewest + PreserveNewest diff --git a/test/TorchSharpTest/func.script.dat b/test/TorchSharpTest/func.script.dat new file mode 100644 index 0000000000000000000000000000000000000000..659837edd62d318eb55b0bd56723bbfaf39ae898 GIT binary patch literal 1334 zcmWIWW@cev;NW1u06Yw03~BlK`YDMeiFyUuIc`ou3{e=MfhjpYz9hdWIU_!vD+oo4g>E>jQ#Yq@$#3zv2dyucmK)~gF%~2UeN4o`` z{~9~l^N*Qu-{tarJ1e*I!*`(z%@4O&=NlQvE|^lld8JVQ;Kq4JdmB%`4Ozyprgq|` z$;R26#N6+^)6R8&|34s1>XCrFL5AxgCzk}h1v6`MTotv%AS2UZ7)m1$p@zl zJM)VEo#bl2{M~f*;yLcU5wE3+*3HQ}6Z(-66eiC62hIC{;c*cfCfH*~o?m%-GapA?8Nlc;uvsBh{?(_H^RAOH=byyB9?ypm!_D&|26lm;eEu#vg?oZ&!o7(f`ek=)RfSe9B;oSC0T zh4g341&Z^F^U_0^fHs40fHxzEg6B!(Ji-H#Kmo`(6rvN6hmcc}D2lEwAP=MyBS)cI zjvUhRC`Qa<#9;&?0iqj*9L9nuh8+a@7~&qJs6y9{97xVkaU1ID;tQ-3WOl_5VZi;@k7@D literal 0 HcmV?d00001 From 401d07451d9a1e4f342008c7d015e5efa1ddaece Mon Sep 17 00:00:00 2001 From: Niklas Gustafsson Date: Sat, 2 Jul 2022 16:12:01 -0700 Subject: [PATCH 12/12] Modified train() to comply with Pytorch. Added doc comments. --- src/Native/LibTorchSharp/THSJIT.cpp | 4 +-- src/Native/LibTorchSharp/THSJIT.h | 2 +- src/Native/LibTorchSharp/THSModule.cpp | 9 ++--- src/Native/LibTorchSharp/THSNN.h | 3 +- src/TorchSharp/JIT/ScriptModule.cs | 48 ++++++++++++++++++++++++-- src/TorchSharp/NN/Module.cs | 27 +++++++++++---- src/TorchSharp/NN/Sequential.cs | 16 +++++++-- test/TorchSharpTest/NN.cs | 5 +++ 8 files changed, 90 insertions(+), 24 deletions(-) diff --git a/src/Native/LibTorchSharp/THSJIT.cpp b/src/Native/LibTorchSharp/THSJIT.cpp index 3485ff8a3..8fb622b56 100644 --- a/src/Native/LibTorchSharp/THSJIT.cpp +++ b/src/Native/LibTorchSharp/THSJIT.cpp @@ -24,9 +24,9 @@ int THSJIT_Module_is_training(JITModule module) return (*module)->is_training(); } -void THSJIT_Module_train(JITModule module) +void THSJIT_Module_train(JITModule module, bool on) { - (*module)->train(); + (*module)->train(on); } void THSJIT_Module_eval(JITModule module) diff --git a/src/Native/LibTorchSharp/THSJIT.h b/src/Native/LibTorchSharp/THSJIT.h index a9d2b4a47..a1331cc73 100644 --- a/src/Native/LibTorchSharp/THSJIT.h +++ b/src/Native/LibTorchSharp/THSJIT.h @@ -28,7 +28,7 @@ EXPORT_API(int) THSJIT_Module_num_outputs(const JITModule method); EXPORT_API(Tensor) THSJIT_Module_forward(const JITModule module, const Tensor* tensorPtrs, const int length); EXPORT_API(int) THSJIT_Module_is_training(JITModule module); -EXPORT_API(void) THSJIT_Module_train(JITModule module); +EXPORT_API(void) THSJIT_Module_train(JITModule module, bool on); EXPORT_API(void) THSJIT_Module_eval(JITModule module); EXPORT_API(void) THSJIT_Module_to_device(JITModule module, int64_t device, int64_t index); diff --git a/src/Native/LibTorchSharp/THSModule.cpp b/src/Native/LibTorchSharp/THSModule.cpp index a0dc52ec6..7f81ec25c 100644 --- a/src/Native/LibTorchSharp/THSModule.cpp +++ b/src/Native/LibTorchSharp/THSModule.cpp @@ -10,14 +10,9 @@ int THSNN_Module_is_training(NNModule module) return (*module)->is_training(); } -void THSNN_Module_train(NNModule module) +void THSNN_Module_train(NNModule module, bool on) { - (*module)->train(); -} - -void THSNN_Module_eval(NNModule module) -{ - (*module)->eval(); + (*module)->train(on); } const char* THSNN_Module_name(const NNModule module) diff --git a/src/Native/LibTorchSharp/THSNN.h b/src/Native/LibTorchSharp/THSNN.h index 1932c1a9a..269f5cfd5 100644 --- a/src/Native/LibTorchSharp/THSNN.h +++ b/src/Native/LibTorchSharp/THSNN.h @@ -17,8 +17,7 @@ EXPORT_API(void) THSNN_Module_get_named_children(const NNModule module, N EXPORT_API(void) THSNN_Module_get_named_modules(const NNModule module, NNModule* (*allocator1)(size_t length), const char** (*allocator2)(size_t length)); EXPORT_API(void) THSNN_Module_get_parameters(const NNModule module, Tensor* (*allocator1)(size_t length), bool recurse); EXPORT_API(int) THSNN_Module_is_training(NNModule module); -EXPORT_API(void) THSNN_Module_train(NNModule module); -EXPORT_API(void) THSNN_Module_eval(NNModule module); +EXPORT_API(void) THSNN_Module_train(NNModule module, bool on); EXPORT_API(long) THSNN_Module_children_size(const NNModule module); EXPORT_API(NNModule) THSNN_Module_child(const NNModule module, const int index); EXPORT_API(const char*) THSNN_Module_name(const NNModule module); diff --git a/src/TorchSharp/JIT/ScriptModule.cs b/src/TorchSharp/JIT/ScriptModule.cs index 729a6c141..e91aa153f 100644 --- a/src/TorchSharp/JIT/ScriptModule.cs +++ b/src/TorchSharp/JIT/ScriptModule.cs @@ -60,6 +60,10 @@ protected override (string name, Tensor buffer)[] _named_buffers() [DllImport("LibTorchSharp")] private static extern void THSJIT_Module_named_modules(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + /// + /// Returns an enumerable of all modules in the network, yielding both the name of the module as well as the module itself. + /// + /// (string, Module) – Tuple of name and module public override IEnumerable<(string name, nn.Module module)> named_modules() { using var pa = new PinnedArray(); @@ -75,6 +79,10 @@ protected override (string name, Tensor buffer)[] _named_buffers() [DllImport("LibTorchSharp")] private static extern void THSJIT_Module_named_children(HType module, AllocatePinnedArray allocator1, AllocatePinnedArray allocator2); + /// + /// Returns an enumerable of immediate children modules, yielding both the name of the module as well as the module itself. + /// + /// (string, Module) – Tuple containing a name and child module public override IEnumerable<(string name, nn.Module module)> named_children() { using var pa = new PinnedArray(); @@ -107,17 +115,31 @@ public int GetNumberOfOutputs() } [DllImport("LibTorchSharp")] - private static extern void THSJIT_Module_train(HType module); + private static extern void THSJIT_Module_train(HType module, bool on); - public override void train() + /// + /// Sets the module in evaluation mode. + /// + /// + /// Any script module that was created using torch.jit.trace() will be unaffected. The behavior of such + /// modules will be captured when traced. + /// + public override void train(bool on = true) { - THSJIT_Module_train(handle); + THSJIT_Module_train(handle, on); CheckForErrors(); } [DllImport("LibTorchSharp")] private static extern void THSJIT_Module_eval(HType module); + /// + /// Sets the module in evaluation mode. + /// + /// + /// Any script module that was created using torch.jit.trace() will be unaffected. The behavior of such + /// modules will be captured when traced. + /// public override void eval() { THSJIT_Module_eval(handle); @@ -127,6 +149,9 @@ public override void eval() [DllImport("LibTorchSharp")] private static extern bool THSJIT_Module_is_training(HType module); + /// + /// Check whether the module is set to training or evaluation mode. + /// public override bool training { get { var res = THSJIT_Module_is_training(handle); @@ -361,6 +386,15 @@ public unsafe Tensor forward(Tensor x, Tensor y, Tensor z, params Tensor[] tenso [DllImport("LibTorchSharp")] private static extern IntPtr THSJIT_load(string filename); + /// + /// Load a ScriptModule or ScriptFunction previously saved with torch.jit.save + /// + /// + /// A ScriptModule instance, whether the script originated as a module or function. + /// + /// All previously saved modules, no matter their device, are first loaded onto CPU, and then are moved to the devices they were saved from.If this fails (e.g.because the run time system doesn’t have certain devices), an exception is raised. + /// + /// Raised if the file is not found. public static ScriptModule load(string filename) { if (!System.IO.File.Exists(filename)) @@ -375,6 +409,14 @@ public static ScriptModule load(string filename) [DllImport("LibTorchSharp")] private static extern void THSJIT_save(nn.Module.HType handle, string filename); + /// + /// Save an offline version of a previously loaded script module. + /// + /// The saved module serializes all of the methods, submodules, parameters, and attributes of this module. + /// It can be loaded into the C++ API using torch::jit::load(filename) or into the .NET API with torch.jit.load(). + /// + /// + /// public static void save(ScriptModule module, string filename) { THSJIT_save(module.handle, filename); diff --git a/src/TorchSharp/NN/Module.cs b/src/TorchSharp/NN/Module.cs index 30d8d1934..9f3ca9521 100644 --- a/src/TorchSharp/NN/Module.cs +++ b/src/TorchSharp/NN/Module.cs @@ -325,28 +325,41 @@ public virtual void Save(string modelPath) => THSNN_Module_save(handle, modelPath); [DllImport("LibTorchSharp")] - private static extern void THSNN_Module_train(HType module); + private static extern void THSNN_Module_train(HType module, bool on); - public virtual void train() + /// + /// Sets the module in training mode. + /// + /// + /// This has any effect only on certain modules.See documentations of particular modules for details of their behaviors in training/evaluation mode, if they are affected, e.g.Dropout, BatchNorm, etc. + /// + public virtual void train(bool train = true) { - THSNN_Module_train(handle); + THSNN_Module_train(handle, train); CheckForErrors(); - foreach (var (_, m) in named_children()) { m.train(); } + foreach (var (_, m) in named_children()) { m.train(train); } } [DllImport("LibTorchSharp")] private static extern void THSNN_Module_eval(HType module); + /// + /// Sets the module in evaluation mode. + /// + /// + /// This has any effect only on certain modules.See documentations of particular modules for details of their behaviors in training/evaluation mode, if they are affected, e.g.Dropout, BatchNorm, etc. + /// public virtual void eval() { - THSNN_Module_eval(handle); - CheckForErrors(); - foreach (var (_, m) in named_children()) { m.eval(); } + train(false); } [DllImport("LibTorchSharp")] private static extern bool THSNN_Module_is_training(HType module); + /// + /// Check whether the module is set to training or evaluation mode. + /// public virtual bool training { get { var res = THSNN_Module_is_training(handle); diff --git a/src/TorchSharp/NN/Sequential.cs b/src/TorchSharp/NN/Sequential.cs index a1720c82a..096d204ef 100644 --- a/src/TorchSharp/NN/Sequential.cs +++ b/src/TorchSharp/NN/Sequential.cs @@ -130,11 +130,23 @@ protected override void Dispose(bool disposing) base.Dispose(disposing); } - public override void train() + /// + /// Sets the module in training mode. + /// + /// + /// This has any effect only on certain modules.See documentations of particular modules for details of their behaviors in training/evaluation mode, if they are affected, e.g.Dropout, BatchNorm, etc. + /// + public override void train(bool on = true) { - foreach (var m in _modules) { m.train(); } + foreach (var m in _modules) { m.train(on); } } + /// + /// Sets the module in evaluation mode. + /// + /// + /// This has any effect only on certain modules.See documentations of particular modules for details of their behaviors in training/evaluation mode, if they are affected, e.g.Dropout, BatchNorm, etc. + /// public override void eval() { foreach (var m in _modules) { m.eval(); } diff --git a/test/TorchSharpTest/NN.cs b/test/TorchSharpTest/NN.cs index 8b29ea011..8090754a2 100644 --- a/test/TorchSharpTest/NN.cs +++ b/test/TorchSharpTest/NN.cs @@ -1096,6 +1096,8 @@ public void TestGradConditional() modT.train(); + Assert.True(modT.training); + var eval = modT.forward(x); var loss = mse_loss(Reduction.Sum); var output = loss(eval, y); @@ -3154,7 +3156,10 @@ public void TestMultiheadAttention() using (var K = torch.tensor(k_data, src_seq_len, batch_size, kembed_dim)) using (var V = torch.tensor(v_data, src_seq_len, batch_size, vembed_dim)) using (var Attn = torch.tensor(attn_data, batch_size, src_seq_len, src_seq_len)) { + mha.eval(); + Assert.False(mha.training); + var (att_out, att_wts) = mha.forward(Q, K, V); var t = att_wts.allclose(Attn, rtol: 0.5, atol: 0.5); Assert.True(t);