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authorkaizhangNV <149626564+kaizhangNV@users.noreply.github.com>2025-01-02 14:29:57 -0600
committerGitHub <noreply@github.com>2025-01-02 12:29:57 -0800
commitd48cd130aacbab34bb98d51bb237ad38ff37348c (patch)
tree9fc9643233ad0cd7ff1aa65155f9f5ca64f677f7 /tests
parente3b71cf0356692bda5f0b3a06aed9d49ad3314a4 (diff)
Correct IR generation for no-diff pointer type (#5976)
* Correct IR generation for no-diff pointer type Close #5805 There is an issue on checking whether a pointer type parameter is no_diff, we should first check whether this parameter is an Attribute type first, then check the data type. In the back-propagate pass, for the pointer type parameter, we should load this parameter to a temp variable, then pass it to the primal function call. Otherwise, the temp variable will no be initialized, which will cause the following calculation wrong.
Diffstat (limited to 'tests')
-rw-r--r--tests/autodiff/nodiff-ptr.slang40
-rw-r--r--tests/autodiff/nodiff-ptr.slang.expected.txt6
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