private static int TestReLU(float slope, bool usePackingLayout)
{
using var a = TestUtil.TestUtil.RandomMat(6, 7, 8);
using var pd = new ParamDict();
pd.Set(0, slope);//slope
using var tmp = new Mat();
var weights = new[] { tmp };
using var vector = new StdVector <Mat>(weights);
using var mb = new ModelBinFromMatArray(vector);
using var opt = new Option
{
NumThreads = 1,
UseVulkanCompute = true,
UseFP16Packed = false,
UseFP16Storage = false,
UseFP16Arithmetic = false,
UseInt8Storage = false,
UseInt8Arithmetic = false,
UsePackingLayout = usePackingLayout
};
var ret = TestUtil.TestUtil.TestLayer <ReLU>("ReLU", pd, mb, opt, a);
if (ret != 0)
{
Console.Error.WriteLine($"test_relu failed slope={slope} use_packing_layout={usePackingLayout}");
}
weights?.DisposeElement();
return(ret);
}
public static string ReturnParameter(HttpSessionStateBase Session, string ParameterName)
{
if (ParameterName.StartsWith("Order."))
{
return(getOrderParameters(Session, ParameterName));
}
if (ParameterName.StartsWith("Tax."))
{
return(getTaxParameters(Session, ParameterName));
}
Dictionary <string, string> ParamDict;
var returnDict = ReturnParameters(Session);
if (returnDict == null)
{
return(null);
}
ParamDict = (Dictionary <string, string>)returnDict;
string keyvalue;
if (ParamDict.TryGetValue(ParameterName, out keyvalue))
{
return(keyvalue);
}
else
{
return("");
}
}
/// <summary>
/// 增加查询参数,并输出参数名,参数名会根据LastParamIndex递增
/// </summary>
/// <param name="v">参数值</param>
/// <returns>返回参数名</returns>
private string AddParam(object v)
{
//这里用完 _lastParamIndex 立即加一 防止下个参数错误
var paramName = $"Sql{_lastParamIndex++}Param";
ParamDict.Add(paramName, v);
return(paramName);
}
/// <summary>
/// 增加查询参数,并输出参数名,参数名会根据LastParamIndex递增
/// </summary>
/// <param name="v">参数值</param>
/// <returns>返回参数名</returns>
private string AddParam(object v)
{
//这里用完 _lastParamIndex 立即加一 防止下个参数错误
var paramName = "SQL_P_" + _lastParamIndex++;
ParamDict.Add(paramName, v);
return(paramName);
}
public static ParamFile GetFile(string name)
{
if (!string.IsNullOrEmpty(name) && ParamDict.ContainsKey(name))
{
return(ParamDict[name]);
}
return(null);
}
public async Task <ActionResult> DeleteConfirmed(int id)
{
ParamDict paramDict = await db.ParamDict.FindAsync(id);
db.ParamDict.Remove(paramDict);
await db.SaveChangesAsync();
return(RedirectToAction("Index"));
}
public static void AddFile(ParamNode node)
{
string name = Path.GetFileNameWithoutExtension(node.AbsolutePath);
if (!ParamDict.ContainsKey(name))
{
ParamDict.Add(name, node.Param);
HandleParam(name, node.Param);
}
}
public async Task <ActionResult> Edit([Bind(Include = "Id,ParamName,SubItemName")] ParamDict paramDict)
{
if (ModelState.IsValid)
{
db.Entry(paramDict).State = EntityState.Modified;
await db.SaveChangesAsync();
return(RedirectToAction("Index"));
}
return(View(paramDict));
}
private static int TestDeconvolutionInt8(int w, int h, int c, int outch, int kernel, int dilation, int stride, int pad, int bias)
{
using var a = TestUtil.TestUtil.RandomMat(w, h, c);
using var pd = new ParamDict();
pd.Set(0, outch); // num_output
pd.Set(1, kernel); // kernel_w
pd.Set(2, dilation); // dilation_w
pd.Set(3, stride); // stride_w
pd.Set(4, pad); // pad_w
pd.Set(5, bias); // bias_term
pd.Set(6, outch * c * kernel * kernel);
pd.Set(8, 1); // int8_scale_term
var weights = new Mat[bias > 0 ? 4 : 3];
weights[0] = TestUtil.TestUtil.RandomMat(outch * c * kernel * kernel);
if (bias > 0)
{
weights[1] = TestUtil.TestUtil.RandomMat(outch);
weights[2] = TestUtil.TestUtil.RandomMat(outch);
weights[3] = TestUtil.TestUtil.RandomMat(1);
}
else
{
weights[1] = TestUtil.TestUtil.RandomMat(outch);
weights[2] = TestUtil.TestUtil.RandomMat(1);
}
using var vector = new StdVector <Mat>(weights);
using var mb = new ModelBinFromMatArray(vector);
using var opt = new Option
{
NumThreads = 1,
UseVulkanCompute = false,
UseInt8Inference = true,
UseFP16Packed = false,
UseFP16Storage = false,
UseFP16Arithmetic = false,
UseInt8Storage = false,
UseInt8Arithmetic = false,
UsePackingLayout = false
};
var ret = TestUtil.TestUtil.TestLayer <Deconvolution>("Deconvolution", pd, mb, opt, a);
if (ret != 0)
{
Console.Error.WriteLine($"test_convolution failed w={w} h={h} c={c} outch={outch} kernel={kernel} dilation={dilation} stride={stride} pad={pad} bias={bias}");
}
return(ret);
}
public async Task <ActionResult> Create([Bind(Include = "Id,ParamName,SubItemName")] ParamDict paramDict)
{
if (ModelState.IsValid)
{
db.ParamDict.Add(paramDict);
await db.SaveChangesAsync();
return(RedirectToAction("Index"));
}
return(View(paramDict));
}
public async Task <ActionResult> Details(int?id)
{
if (id == null)
{
return(new HttpStatusCodeResult(HttpStatusCode.BadRequest));
}
ParamDict paramDict = await db.ParamDict.FindAsync(id);
if (paramDict == null)
{
return(HttpNotFound());
}
return(View(paramDict));
}
static void Main(string[] args)
{
var _pd = new ParamDict();
_pd["00.01.02"] = 1;
_pd["k1"] = 1;
_pd["k2"] = 2;
_pd["k3"] = 3;
_pd["k4"] = 4;
_pd["k5"] = 5;
var _element = _pd["00.01"];
RuntimeCompiler();
}
private static int DetectShuffleNetV2(NcnnDotNet.OpenCV.Mat bgr, List <float> clsScores)
{
using (var shuffleNetV2 = new Net())
{
if (Ncnn.IsSupportVulkan)
{
shuffleNetV2.Opt.UseVulkanCompute = true;
}
// https://github.com/miaow1988/ShuffleNet_V2_pytorch_caffe
// models can be downloaded from https://github.com/miaow1988/ShuffleNet_V2_pytorch_caffe/releases
shuffleNetV2.LoadParam("shufflenet_v2_x0.5.param");
shuffleNetV2.LoadModel("shufflenet_v2_x0.5.bin");
using var @in = Mat.FromPixelsResize(bgr.Data, PixelType.Bgr, bgr.Cols, bgr.Rows, 224, 224);
var normVals = new[] { 1 / 255.0f, 1 / 255.0f, 1 / 255.0f };
@in.SubstractMeanNormalize(null, normVals);
using var ex = shuffleNetV2.CreateExtractor();
ex.Input("data", @in);
using var @out = new Mat();
ex.Extract("fc", @out);
// manually call softmax on the fc output
// convert result into probability
// skip if your model already has softmax operation
{
using var softmax = Ncnn.CreateLayer("Softmax");
using var pd = new ParamDict();
softmax.LoadParam(pd);
softmax.ForwardInplace(@out, shuffleNetV2.Opt);
}
using var @out2 = @out.Reshape(@out.W * @out.H * @out.C);
clsScores.Capacity = @out2.W;
for (var j = 0; j < @out2.W; j++)
{
clsScores.Add(@out2[j]);
}
}
return(0);
}
private static int TestConvolutionDepthWise(int w, int h, int c, int outch, int kernel, int dilation, int stride, int pad, int bias, int group, bool usePackingLayout)
{
using var a = TestUtil.TestUtil.RandomMat(w, h, c);
using var pd = new ParamDict();
pd.Set(0, outch); // num_output
pd.Set(1, kernel); // kernel_w
pd.Set(2, dilation); // dilation_w
pd.Set(3, stride); // stride_w
pd.Set(4, pad); // pad_w
pd.Set(5, bias); // bias_term
pd.Set(6, outch / group * c / group * kernel * kernel * group);
pd.Set(7, group);
var weights = new Mat[bias > 0 ? 2 : 1];
weights[0] = TestUtil.TestUtil.RandomMat(outch / group * c / group * kernel * kernel * group);
weights[1] = TestUtil.TestUtil.RandomMat(outch);
using var vector = new StdVector <Mat>(weights);
using var mb = new ModelBinFromMatArray(vector);
using var opt = new Option
{
NumThreads = 1,
UseVulkanCompute = true,
UseInt8Inference = false,
UseFP16Packed = false,
UseFP16Storage = false,
UseFP16Arithmetic = false,
UseInt8Storage = false,
UseInt8Arithmetic = false,
UsePackingLayout = usePackingLayout
};
var ret = TestUtil.TestUtil.TestLayer <ConvolutionDepthWise>("ConvolutionDepthWise", pd, mb, opt, a);
if (ret != 0)
{
Console.Error.WriteLine($"test_convolutiondepthwise failed w={w} h={h} c={c} outch={outch} kernel={kernel} dilation={dilation} stride={stride} pad={pad} bias={bias} group={group} use_packing_layout={usePackingLayout}");
}
weights?.DisposeElement();
return(ret);
}
public IFuture Curry(ParamDict paramDict)
{
return new OpenDocumentSensitivePrioritizedFuture(this.prioritizer, this.prototype.Curry(paramDict), this.openDocumentFuture);
}
public IFuture Curry(ParamDict paramDict)
{
return(this);
}
public IFuture Curry(ParamDict paramDict)
{
return(new TransparencyFuture(transparencyOptions,
antialiasedPrototype.Curry(paramDict),
exactColorPrototype.Curry(paramDict)));
}
public static int TestLayer <T>(int typeIndex, ParamDict pd, ModelBin mb, Option opt, Mat a, float epsilon = 0.001f)
where T : Layer, new()
{
using (var op = Ncnn.CreateLayer <T>(typeIndex))
{
if (!op.SupportPacking)
{
opt.UsePackingLayout = false;
}
VulkanDevice vkDev = null;
VkWeightBufferAllocator gWeightVkAllocator = null;
VkWeightStagingBufferAllocator gWeightStagingVkAllocator = null;
VkBlobBufferAllocator gBlobVkAllocator = null;
VkStagingBufferAllocator gStagingVkAllocator = null;
if (Ncnn.IsSupportVulkan)
{
vkDev = Ncnn.GetGpuDevice();
gWeightVkAllocator = new VkWeightBufferAllocator(vkDev);
gWeightStagingVkAllocator = new VkWeightStagingBufferAllocator(vkDev);
gBlobVkAllocator = new VkBlobBufferAllocator(vkDev);
gStagingVkAllocator = new VkStagingBufferAllocator(vkDev);
opt.BlobVkAllocator = gBlobVkAllocator;
opt.WorkspaceVkAllocator = gBlobVkAllocator;
opt.StagingVkAllocator = gStagingVkAllocator;
if (!vkDev.Info.SupportFP16Storage)
{
opt.UseFP16Storage = false;
}
if (!vkDev.Info.SupportFP16Packed)
{
opt.UseFP16Packed = false;
}
op.VkDev = vkDev;
}
op.LoadParam(pd);
op.LoadModel(mb);
op.CreatePipeline(opt);
if (Ncnn.IsSupportVulkan)
{
if (opt.UseVulkanCompute)
{
using var cmd = new VkTransfer(vkDev)
{
WeightVkAllocator = gWeightVkAllocator,
StagingVkAllocator = gWeightStagingVkAllocator
};
op.UploadModel(cmd, opt);
cmd.SubmitAndWait();
gWeightStagingVkAllocator?.Clear();
}
}
using var b = new Mat();
((T)op).Forward(a, b, opt);
var c = new Mat();
{
Mat a4;
if (opt.UsePackingLayout)
{
a4 = new Mat();
Ncnn.ConvertPacking(a, a4, 4, opt);
}
else
{
a4 = a;
}
var c4 = new Mat();
op.Forward(a4, c4, opt);
if (opt.UsePackingLayout)
{
Ncnn.ConvertPacking(c4, c, 1, opt);
c4.Dispose();
}
else
{
c?.Dispose();
c = c4;
}
}
Mat d = null;
try
{
if (Ncnn.IsSupportVulkan)
{
d = new Mat();
if (opt.UseVulkanCompute)
{
using var a4 = new Mat();
Mat a4_fp16 = null;
try
{
// pack
Ncnn.ConvertPacking(a, a4, 4, opt);
// fp16
if (opt.UseFP16Storage || a4.ElemPack == 4 && opt.UseFP16Packed)
{
a4_fp16 = new Mat();
Ncnn.CastFloat32ToFloat16(a4, a4_fp16, opt);
}
else
{
a4_fp16 = a4;
}
// upload
using var a4_fp16_gpu = new VkMat();
a4_fp16_gpu.CreateLike(a4_fp16, gBlobVkAllocator, gStagingVkAllocator);
a4_fp16_gpu.PrepareStagingBuffer();
a4_fp16_gpu.Upload(a4_fp16);
// forward
using var cmd = new VkCompute(vkDev);
cmd.RecordUpload(a4_fp16_gpu);
using var d4_fp16_gpu = new VkMat();
op.Forward(a4_fp16_gpu, d4_fp16_gpu, cmd, opt);
d4_fp16_gpu.PrepareStagingBuffer();
cmd.RecordDownload(d4_fp16_gpu);
cmd.SubmitAndWait();
// download
using var d4_fp16 = new Mat();
d4_fp16.CreateLike(d4_fp16_gpu);
d4_fp16_gpu.Download(d4_fp16);
// fp32
Mat d4 = null;
try
{
if (opt.UseFP16Storage || d4_fp16.ElemPack == 4 && opt.UseFP16Packed)
{
d4 = new Mat();
Ncnn.CastFloat16ToFloat32(d4_fp16, d4, opt);
}
else
{
d4 = d4_fp16;
}
// unpack
Ncnn.ConvertPacking(d4, d, 1, opt);
}
finally
{
d4?.Dispose();
}
}
finally
{
a4_fp16?.Dispose();
}
}
}
op.DestroyPipeline(opt);
// Must dispose here!!
op.Dispose();
if (Ncnn.IsSupportVulkan)
{
gBlobVkAllocator.Clear();
gStagingVkAllocator.Clear();
gWeightVkAllocator.Clear();
gBlobVkAllocator?.Dispose();
gStagingVkAllocator?.Dispose();
gWeightVkAllocator?.Dispose();
gWeightStagingVkAllocator?.Dispose();
}
if (CompareMat(b, c, epsilon) != 0)
{
Console.Error.WriteLine("test_layer failed cpu");
return(-1);
}
if (Ncnn.IsSupportVulkan)
{
if (opt.UseVulkanCompute && CompareMat(b, d, epsilon) != 0)
{
Console.Error.WriteLine("test_layer failed gpu");
return(-1);
}
}
}
finally
{
c?.Dispose();
d?.Dispose();
}
}
return(0);
}
public IFuture Curry(ParamDict paramDict)
{
return(new OpenDocumentSensitivePrioritizedFuture(prioritizer,
prototype.Curry(paramDict),
openDocumentFuture));
}
public IFuture Curry(ParamDict paramDict)
{
return new MemCacheFuture(this.cache, this.prototype.Curry(paramDict));
}
public IFuture Curry(ParamDict paramDict)
{
return this;
}
/// <summary>
/// 清除文本内容和参数内容
/// </summary>
public void Clear()
{
ParamDict.Clear();
SqlText.Remove(0, SqlText.Length);
}
public IFuture Curry(ParamDict paramDict)
{
return new TransparencyFuture(this.transparencyOptions, this.antialiasedPrototype.Curry(paramDict), this.exactColorPrototype.Curry(paramDict));
}
public IFuture Curry(ParamDict paramDict)
{
return Asynchronizer.MakeFuture(this.scheduler, this.innerPrototype.Curry(paramDict));
}
public static void Unload()
{
ParamDict.Clear();
}
public IFuture Curry(ParamDict paramDict)
{
return(new DiskCacheFuture(cache, prototype.Curry(paramDict)));
}
public IFuture Curry(ParamDict paramDict)
{
IFuture[] futureParams = Array.ConvertAll<IFuturePrototype, IFuture>(this.prototypeParams, (IFuturePrototype p) => p.Curry(paramDict));
return new ApplyFuture(this.verb, futureParams);
}
public IFuture Curry(ParamDict paramDict)
{
return new ConstantFuture(paramDict[this.name]);
}
public IFuture Curry(ParamDict paramDict)
{
return(new ConstantFuture(paramDict[name]));
}
public static int TestLayer <T>(string layerType, ParamDict pd, ModelBin mb, Option opt, Mat a, float epsilon = 0.001f)
where T : Layer, new()
{
return(TestLayer <T>(Ncnn.LayerToIndex(layerType), pd, mb, opt, a, epsilon));
}
