public void SetInputs(ExecutionSequence executionSequence, double[] inputs)
{
if (inputs.Length != NodeCount)
{
throw new ArgumentException($"input array length ({inputs.Length}) does not match input layer size ({NodeCount})", nameof(inputs));
}
_inputs.Update(inputs, executionSequence);
}
public void SetWeights(ExecutionSequence executionSequence, double[] weights)
{
if (weights.Length != _weightLength)
{
throw new ArgumentException($"weight array length ({weights.Length}) does not match required ({_weightLength})", nameof(weights));
}
_weights.Update(weights, executionSequence);
}
public void Update_DoesntThrow()
{
var matrix = new GpuMatrix(3, 3, _testScaffold.Context);
matrix.Update(
new double[] {
1.0, 2.0, 3.0,
4.0, 5.0, 6.0,
7.0, 8.0, 9.0
},
_testScaffold.ExecutionSequence
);
}
public void UpdateRead_Works()
{
var matrix = new GpuMatrix(3, 3, _testScaffold.Context);
matrix.Update(
new double[] {
0.0, 1.0, 2.0,
3.0, 4.0, 5.0,
6.0, 7.0, 8.0
},
_testScaffold.ExecutionSequence
);
using (matrix.Read(_testScaffold.ExecutionSequence))
{
for (var i = 0; i < 9; i++)
{
matrix.InMemoryData[i].Should().Be(i);
}
}
}
public void SetTargets(ExecutionSequence executionSequence, double[] targets)
{
if (targets.Length != NodeCount)
{
throw new NerotiqException($"target value array length ({targets.Length}) does not match layer size ({NodeCount})");
}
if (_layerTargets == null)
{
try {
_layerTargets = new GpuMatrix((ushort)NodeCount, 1, executionSequence.Context);
} catch (Exception ex)
{
throw new NerotiqException($"Error allocating delta buffer", ex);
}
_layerTargets.SetKernelArg(
_backwardKernel,
11
);
}
_layerTargets.Update(targets, executionSequence);
}
public void SetOutputs(ExecutionSequence executionSequence, double[] outputs)
{
_layerOutputs.Update(outputs, executionSequence);
}
public void SetBiases(ExecutionSequence executionSequence, double[] biases)
{
_biases.Update(biases, executionSequence);
}
public void SetKernelArgs_Works()
{
var src = @"
__kernel void a(
__global double *data // 0
) {
int global_id = get_global_id(0);
data[global_id] *= data[global_id];
}
";
var srcs = SourceLoader.CreateProgramCollection(src);
var program = Cl.CreateProgramWithSource(
_testScaffold.Context.OpenClContext,
(uint)srcs.Length,
srcs,
null,
out var error
);
error.Should().Be(ErrorCode.Success);
error = Cl.BuildProgram(
program,
1,
new[] { _testScaffold.Context.Device },
string.Empty,
null,
IntPtr.Zero
);
error.Should().Be(ErrorCode.Success);
var kernel = Cl.CreateKernel(program, "a", out error);
error.Should().Be(ErrorCode.Success);
var matrix = new GpuMatrix(3, 3, _testScaffold.Context);
matrix.Update(
new double[] {
1.0, 2.0, 3.0,
4.0, 5.0, 6.0,
7.0, 8.0, 9.0
},
_testScaffold.ExecutionSequence
);
matrix.SetKernelArg(kernel, 0);
_testScaffold.ExecutionSequence.EnqueueNDRangeKernel(
kernel,
1,
null,
new IntPtr [] { new IntPtr(9) },
null
);
using (matrix.Read(_testScaffold.ExecutionSequence))
{
matrix.GetValue(0, 0).Should().Be(1.0);
matrix.GetValue(0, 1).Should().Be(4.0);
matrix.GetValue(0, 2).Should().Be(9.0);
matrix.GetValue(1, 0).Should().Be(16.0);
matrix.GetValue(1, 1).Should().Be(25.0);
matrix.GetValue(1, 2).Should().Be(36.0);
matrix.GetValue(2, 0).Should().Be(49.0);
matrix.GetValue(2, 1).Should().Be(64.0);
matrix.GetValue(2, 2).Should().Be(81.0);
}
}