public IWeightTensor Affine(IWeightTensor m1, IWeightTensor m2, IWeightTensor mbias)
        {
            if (m1 == null)
            {
                throw new ArgumentNullException($"m1 tensor is null");
            }

            if (m2 == null)
            {
                throw new ArgumentNullException($"m2 tensor is null");
            }

            if (mbias == null)
            {
                throw new ArgumentNullException($"mbias tensor is null");
            }

            WeightTensor t1 = m1 as WeightTensor;
            WeightTensor t2 = m2 as WeightTensor;
            WeightTensor t3 = mbias as WeightTensor;

            var          n   = t1.Rows;
            var          d   = t2.Columns;
            WeightTensor res = m_weightTensorFactory.CreateWeightTensor(n, d, m_deviceId, name: $"{GetHashString(m1.Name, m2.Name, mbias.Name)}.Affine");

            VisualizeNodes(new IWeightTensor[] { m1, m2, mbias }, res);

            using (var t3WExp = t3.TWeight.Expand(n, d))
            {
                Ops.Addmm(res.TWeight, 1.0f, t3WExp, 1.0f, t1.TWeight, t2.TWeight);
            }

            if (m_needsBackprop)
            {
                Action backward = () =>
                {
                    res.ReleaseWeight();

                    using (var t3G = t3.TGradient.Expand(n, d))
                    {
                        Ops.Add(t3G, t3G, res.TGradient);
                    }

                    using (var tW2 = t2.TWeight.Transpose())
                    {
                        Ops.Addmm(t1.TGradient, 1.0f, t1.TGradient, 1.0f, res.TGradient, tW2);
                    }

                    using (var tW1 = t1.TWeight.Transpose())
                    {
                        Ops.Addmm(t2.TGradient, 1.0f, t2.TGradient, 1.0f, tW1, res.TGradient);
                    }

                    res.Dispose();
                };
                this.m_backprop.Add(backward);
            }

            return(res);
        }
Esempio n. 2
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        public IWeightMatrix MulBatch(IWeightMatrix m1, IWeightMatrix m2, int batchSize)
        {
            WeightTensor t1  = m1 as WeightTensor;
            WeightTensor t2  = m2 as WeightTensor;
            var          n   = t1.Rows;
            var          d   = t2.Columns;
            WeightTensor res = weightTensorFactory.CreateWeightTensor(n, d, deviceId);

            Tensor t1W = t1.TWeight.View(batchSize, t1.Rows / batchSize, t1.Columns);
            Tensor t2W = t2.TWeight.View(batchSize, t2.Rows / batchSize, t2.Columns);
            Tensor rW  = res.TWeight.View(batchSize, n / batchSize, d);

            Ops.AddmmBatch(rW, 0.0f, rW, 1.0f, t1W, t2W);
            rW.Dispose();

            if (this.needs_backprop)
            {
                Action backward = () =>
                {
                    res.ReleaseWeight();

                    Tensor t1G = t1.TGradient.View(batchSize, t1.Rows / batchSize, t1.Columns);
                    Tensor t2G = t2.TGradient.View(batchSize, t2.Rows / batchSize, t2.Columns);
                    Tensor rG  = res.TGradient.View(batchSize, n / batchSize, d);

                    var tW2 = t2W.Transpose(1, 2);
                    Ops.AddmmBatch(t1G, 1.0f, t1G, 1.0f, rG, tW2);

                    var tW1 = t1W.Transpose(1, 2);
                    Ops.AddmmBatch(t2G, 1.0f, t2G, 1.0f, tW1, rG);

                    tW1.Dispose();
                    tW2.Dispose();

                    t1W.Dispose();
                    t2W.Dispose();
                    t1G.Dispose();
                    t2G.Dispose();

                    rG.Dispose();

                    res.Dispose();
                };
                this.backprop.Add(backward);
            }
            else
            {
                t1W.Dispose();
                t2W.Dispose();
            }

            return(res);
        }
        public IWeightTensor MulBatch(IWeightTensor m1, IWeightTensor m2, int batchSize, float alpha = 1.0f)
        {
            WeightTensor t1  = m1 as WeightTensor;
            WeightTensor t2  = m2 as WeightTensor;
            WeightTensor res = m_weightTensorFactory.CreateWeightTensor((int)(batchSize * t1.TWeight.Sizes[1]), (int)t2.TWeight.Sizes[2], m_deviceId, name: $"{GetHashString(m1.Name, m2.Name)}.MulBatch");

            VisualizeNodes(new IWeightTensor[] { m1, m2 }, res);

            Tensor t1W = t1.TWeight;
            Tensor t2W = t2.TWeight;

            using (Tensor rW = res.TWeight.View(batchSize, t1.TWeight.Sizes[1], t2.TWeight.Sizes[2]))
            {
                Ops.AddmmBatch(rW, 0.0f, rW, alpha, t1W, t2W);
            }

            if (m_needsBackprop)
            {
                Action backward = () =>
                {
                    res.ReleaseWeight();
                    using (Tensor rG = res.TGradient.View(batchSize, t1.TWeight.Sizes[1], t2.TWeight.Sizes[2]))
                    {
                        using (Tensor t1G = t1.TGradient.View(t1.TWeight.Sizes[0], t1.TWeight.Sizes[1], t1.TWeight.Sizes[2]))
                        {
                            using (var tW2 = t2W.Transpose(1, 2))
                            {
                                Ops.AddmmBatch(t1G, 1.0f, t1G, 1.0f, rG, tW2);
                            }
                        }
                        using (Tensor t2G = t2.TGradient.View(t2.TWeight.Sizes[0], t2.TWeight.Sizes[1], t2.TWeight.Sizes[2]))
                        {
                            using (var tW1 = t1W.Transpose(1, 2))
                            {
                                Ops.AddmmBatch(t2G, 1.0f, t2G, 1.0f, tW1, rG);
                            }
                        }
                    }

                    res.Dispose();
                };
                this.m_backprop.Add(backward);
            }

            return(res);
        }
        public IWeightTensor Dropout(IWeightTensor V, int batchSize, float drop_prob, bool inPlace = false)
        {
            if (drop_prob == 0)
            {
                return(V);
            }

            // Generate noise tensor
            float  p     = 1.0f - drop_prob;
            Tensor noise = BuildRandomTensor(V.Rows, V.Columns, batchSize, p);

            var          w   = V as WeightTensor;
            WeightTensor res = null;

            if (inPlace)
            {
                res = w.CopyWeightsRef($"{GetHashString(V.Name)}.Dropout");
            }
            else
            {
                res = m_weightTensorFactory.CreateWeightTensor(w.Sizes, m_deviceId, name: $"{GetHashString(V.Name)}.Dropout");
            }
            VisualizeNodes(V, res);

            Ops.Mul(res.TWeight, w.TWeight, noise);
            if (m_needsBackprop)
            {
                Action backward = () =>
                {
                    res.ReleaseWeight();

                    if (inPlace)
                    {
                        w.TGradient = res.TGradient.CopyRef();
                    }

                    w.AddMulGradient(noise, res.TGradient, inPlace);

                    res.Dispose();
                    noise.Dispose();
                };
                this.m_backprop.Add(backward);
            }

            return(res);
        }
Esempio n. 5
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        public IWeightMatrix MulAdd(IWeightMatrix m1, IWeightMatrix m2, IWeightMatrix m3)
        {
            WeightTensor t1 = m1 as WeightTensor;
            WeightTensor t2 = m2 as WeightTensor;
            WeightTensor t3 = m3 as WeightTensor;

            var n = t1.Rows;
            var d = t2.Columns;

            WeightTensor res = weightTensorFactory.CreateWeightTensor(n, d, deviceId);

            Ops.Addmm(res.TWeight, 1.0f, t3.TWeight, 1.0f, t1.TWeight, t2.TWeight);

            if (this.needs_backprop)
            {
                Action backward = () =>
                {
                    res.ReleaseWeight();

                    //  Ops.Add(t3.TGradient, t3.TGradient, res.TGradient);

                    t3.CopyOrAddGradient(res);

                    var tW2 = t2.TWeight.Transpose();
                    Ops.Addmm(t1.TGradient, 1.0f, t1.TGradient, 1.0f, res.TGradient, tW2);


                    var tW1 = t1.TWeight.Transpose();
                    Ops.Addmm(t2.TGradient, 1.0f, t2.TGradient, 1.0f, tW1, res.TGradient);

                    tW1.Dispose();
                    tW2.Dispose();

                    res.Dispose();
                };
                this.backprop.Add(backward);
            }

            return(res);
        }
Esempio n. 6
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        public IWeightTensor MulAdd(IWeightTensor m1, IWeightTensor m2, IWeightTensor m3)
        {
            WeightTensor t1 = m1 as WeightTensor;
            WeightTensor t2 = m2 as WeightTensor;
            WeightTensor t3 = m3 as WeightTensor;

            var n = t1.Rows;
            var d = t2.Columns;

            WeightTensor res = m_weightTensorFactory.CreateWeightTensor(n, d, m_deviceId, name: $"{GetHashString(m1.Name, m2.Name, m3.Name)}.MulAdd");

            VisualizeNodes(new IWeightTensor[] { m1, m2, m3 }, res);

            Ops.Addmm(res.TWeight, 1.0f, t3.TWeight, 1.0f, t1.TWeight, t2.TWeight);
            if (this.m_needsBackprop)
            {
                Action backward = () =>
                {
                    res.ReleaseWeight();
                    t3.CopyOrAddGradient(res);

                    using (var tW2 = t2.TWeight.Transpose())
                    {
                        Ops.Addmm(t1.TGradient, 1.0f, t1.TGradient, 1.0f, res.TGradient, tW2);
                    }

                    using (var tW1 = t1.TWeight.Transpose())
                    {
                        Ops.Addmm(t2.TGradient, 1.0f, t2.TGradient, 1.0f, tW1, res.TGradient);
                    }

                    res.Dispose();
                };
                this.m_backprop.Add(backward);
            }

            return(res);
        }