2 files changed, 46 insertions, 0 deletions
diff --git a/tests/autodiff/nodiff-ptr.slang b/tests/autodiff/nodiff-ptr.slang
new file mode 100644
index 000000000..d20abddac
--- /dev/null
+++ b/tests/autodiff/nodiff-ptr.slang
@@ -0,0 +1,40 @@
+
+[Differentiable]
+float sumOfSquares(float x, float y, no_diff float4* test)
+{
+    return x * x + y * y * (test->x + test->y + test->z);
+}
+
+//TEST(compute, vulkan):COMPARE_COMPUTE_EX:-vk -compute -shaderobj -output-using-type -compile-arg -skip-spirv-validation -emit-spirv-directly
+
+//TEST_INPUT: set ptr = ubuffer(data=[1.0 2.0 3.0], stride=4)
+uniform float* ptr;
+
+//TEST_INPUT:ubuffer(data=[0.0 0.0 0.0 0.0 0.0], stride=4):out, name outputBuffer
+RWStructuredBuffer<float> outputBuffer;
+
+[shader("compute")]
+[numthreads(1, 1, 1)]
+void computeMain()
+{
+    float4* testPtr = (float4*)ptr;
+
+    let result = sumOfSquares(2.0, 3.0, testPtr);
+
+    // Use forward differentiation to compute the gradient of the output w.r.t. x only.
+    let diffX = fwd_diff(sumOfSquares)(diffPair(2.0, 1.0), diffPair(3.0, 0.0), testPtr);
+
+    // Create a differentiable pair to pass in the primal value and to receive the gradient.
+    var dpX = diffPair(2.0);
+    var dpY = diffPair(3.0);
+
+    // Propagate the gradient of the output (1.0f) to the input parameters.
+    bwd_diff(sumOfSquares)(dpX, dpY, testPtr, 1.0);
+
+    outputBuffer[0] = result;     // 2^2 + 3^2 * (1 + 2 + 3) = 58
+    outputBuffer[1] = diffX.d;    // 2*x * dx + 2*y * dy * (1 + 2 + 3) = 4
+    outputBuffer[2] = diffX.p;    // 2^2 + 3^2 * (1 + 2 + 3) = 58
+    outputBuffer[3] = dpX.d;      // 2*x = 4
+
+    outputBuffer[4] = dpY.d;      // 2*y * (1 + 2 +3) = 36
+}
diff --git a/tests/autodiff/nodiff-ptr.slang.expected.txt b/tests/autodiff/nodiff-ptr.slang.expected.txt
new file mode 100644
index 000000000..959cc68e4
--- /dev/null
+++ b/tests/autodiff/nodiff-ptr.slang.expected.txt
@@ -0,0 +1,6 @@
+type: float
+58.000000
+4.000000
+58.000000
+4.000000
+36.000000