public Tensor Addmm(Tensor result, float beta, Tensor src, float alpha, Tensor m1, Tensor m2)
{
//Console.WriteLine($"src0 = {src.Sizes[0]}, src1 = {src.Sizes[1]}, m1_0 = {m1.Sizes[0]}, m1_1 = {m1.Sizes[1]}, m2_0 = {m2.Sizes[0]}, m2_1 = {m2.Sizes[1]}");
// ReSharper disable once ArrangeRedundantParentheses
if (src.ElementType != m1.ElementType || src.ElementType != m2.ElementType || (result != null && result.ElementType != src.ElementType))
{
throw new InvalidOperationException("All tensors must have the same element type");
}
if (result != null && !(result.Storage is CpuStorage))
{
throw new ArgumentException("result must be a CPU tensor", nameof(result));
}
if (!(m1.Storage is CpuStorage))
{
throw new ArgumentException("m1 must be a CPU tensor", nameof(m1));
}
if (!(m2.Storage is CpuStorage))
{
throw new ArgumentException("m2 must be a CPU tensor", nameof(m2));
}
if (src.DimensionCount != 2)
{
throw new ArgumentException("src must be a matrix", nameof(src));
}
if (m1.DimensionCount != 2)
{
throw new ArgumentException("m1 must be a matrix", nameof(m1));
}
if (m2.DimensionCount != 2)
{
throw new ArgumentException("m2 must be a matrix", nameof(m2));
}
if (src.Sizes[0] != m1.Sizes[0] || src.Sizes[1] != m2.Sizes[1] || m1.Sizes[1] != m2.Sizes[0])
{
throw new InvalidOperationException("Size mismatch");
}
var writeTarget = TensorResultBuilder.GetWriteTarget(result, src, true, src.Sizes);
if (writeTarget != src)
{
Ops.Copy(writeTarget, src);
}
MatrixMultiplication.Gemm(alpha, m1, m2, beta, writeTarget);
return(writeTarget);
}
public Tensor Addmm(Tensor result, float beta, Tensor src, float alpha, Tensor m1, Tensor m2)
{
if (src.ElementType != m1.ElementType || src.ElementType != m2.ElementType || (result != null && result.ElementType != src.ElementType))
{
throw new InvalidOperationException("All tensors must have the same element type");
}
if (result != null && !(result.Storage is CpuStorage))
{
throw new ArgumentException("result must be a CPU tensor", "result");
}
if (!(m1.Storage is CpuStorage))
{
throw new ArgumentException("m1 must be a CPU tensor", "m1");
}
if (!(m2.Storage is CpuStorage))
{
throw new ArgumentException("m2 must be a CPU tensor", "m2");
}
if (src.DimensionCount != 2)
{
throw new ArgumentException("src must be a matrix", "src");
}
if (m1.DimensionCount != 2)
{
throw new ArgumentException("m1 must be a matrix", "m1");
}
if (m2.DimensionCount != 2)
{
throw new ArgumentException("m2 must be a matrix", "m2");
}
if (src.Sizes[0] != m1.Sizes[0] || src.Sizes[1] != m2.Sizes[1] || m1.Sizes[1] != m2.Sizes[0])
{
throw new InvalidOperationException("Size mismatch");
}
var writeTarget = TensorResultBuilder.GetWriteTarget(result, src, true, src.Sizes);
if (writeTarget != src)
{
Ops.Copy(writeTarget, src);
}
MatrixMultiplication.Gemm(alpha, m1, m2, beta, writeTarget);
return(writeTarget);
}
public Tensor Dot(Tensor result, Tensor lhs, Tensor rhs)
{
if (lhs.DimensionCount == 1 && rhs.DimensionCount == 1)
{
return(MatrixMultiplication.Dot(result, lhs, rhs));
}
if (lhs.DimensionCount == 2 && rhs.DimensionCount == 1)
{
return(MatrixMultiplication.Mul_M_V(result, lhs, rhs));
}
if (lhs.DimensionCount == 2 && rhs.DimensionCount == 2)
{
return(MatrixMultiplication.Mul_M_M(result, lhs, rhs));
}
throw new NotSupportedException(string.Format("Multiplication of {0}D with {1}D tensor is not supported"));
}
public Tensor AddmmBatch(Tensor result, float beta, Tensor src, float alpha, Tensor m1, Tensor m2)
{
// ReSharper disable once ArrangeRedundantParentheses
if (src.ElementType != m1.ElementType || src.ElementType != m2.ElementType || (result != null && result.ElementType != src.ElementType))
{
throw new InvalidOperationException("All tensors must have the same element type");
}
if (result != null && !(result.Storage is CpuStorage))
{
throw new ArgumentException("result must be a CPU tensor", nameof(result));
}
if (!(m1.Storage is CpuStorage))
{
throw new ArgumentException("m1 must be a CPU tensor", nameof(m1));
}
if (!(m2.Storage is CpuStorage))
{
throw new ArgumentException("m2 must be a CPU tensor", nameof(m2));
}
if (src.DimensionCount != 3)
{
throw new ArgumentException("src must be a matrix", nameof(src));
}
if (m1.DimensionCount != 3)
{
throw new ArgumentException("m1 must be a matrix", nameof(m1));
}
if (m2.DimensionCount != 3)
{
throw new ArgumentException("m2 must be a matrix", nameof(m2));
}
if (src.Sizes[1] != m1.Sizes[1] || src.Sizes[2] != m2.Sizes[2] || m1.Sizes[2] != m2.Sizes[1])
{
throw new InvalidOperationException($"Size mismatch, srcSize0 = {src.Sizes[0]}, m1Size0 = {m1.Sizes[0]}, srcSize1 = {src.Sizes[1]}, m2Size1 = {m2.Sizes[1]}, m1Size1 = '{m1.Sizes[1]}', m2Size0 = '{m2.Sizes[0]}'");
}
var writeTarget = TensorResultBuilder.GetWriteTarget(result, src, true, src.Sizes);
if (writeTarget != src)
{
Ops.Copy(writeTarget, src);
}
var batchSize = (int)src.Sizes[0];
for (var i = 0; i < batchSize; i++)
{
var a = m1.Select(0, i); // m1.Narrow(0, i, 1).View(m1.Sizes[1], m1.Sizes[2]);
var b = m2.Select(0, i); // m2.Narrow(0, i, 1).View(m2.Sizes[1], m2.Sizes[2]);
var r = writeTarget.Select(0, i); // writeTarget.Narrow(0, i, 1).View(writeTarget.Sizes[1], writeTarget.Sizes[2]);
MatrixMultiplication.Gemm(alpha, a, b, beta, r);
}
//MatrixMultiplication.Gemm(alpha, m1, m2, beta, writeTarget);
return(writeTarget);
}
public static Tensor Addmm(Tensor result, float beta, Tensor src, float alpha, Tensor m1, Tensor m2)
{
try
{
if (src.ElementType != m1.ElementType || src.ElementType != m2.ElementType || (result != null && result.ElementType != src.ElementType))
{
throw new InvalidOperationException("All tensors must have the same element type");
}
if (result != null && !(result.Storage is CpuStorage))
{
throw new ArgumentException("result must be a CPU tensor", nameof(result));
}
if (!(m1.Storage is CpuStorage))
{
throw new ArgumentException("m1 must be a CPU tensor", nameof(m1));
}
if (!(m2.Storage is CpuStorage))
{
throw new ArgumentException("m2 must be a CPU tensor", nameof(m2));
}
if (src.DimensionCount != 2)
{
throw new ArgumentException("src must be a matrix", nameof(src));
}
if (m1.DimensionCount != 2)
{
throw new ArgumentException("m1 must be a matrix", nameof(m1));
}
if (m2.DimensionCount != 2)
{
throw new ArgumentException("m2 must be a matrix", nameof(m2));
}
if (src.Sizes[0] != m1.Sizes[0] || src.Sizes[1] != m2.Sizes[1] || m1.Sizes[1] != m2.Sizes[0])
{
throw new InvalidOperationException("Size mismatch");
}
Tensor writeTarget = TensorResultBuilder.GetWriteTarget(result, src, false, src.Sizes);
if (writeTarget != src)
{
Ops.Copy(writeTarget, src);
}
MatrixMultiplication.Gemm(alpha, m1, m2, beta, writeTarget);
return(writeTarget);
}
catch (Exception err)
{
Logger.WriteLine(Logger.Level.err, $"Exception = '{err.Message}', Call stack = '{err.StackTrace}'");
throw;
}
}
