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ggml-webgpu: Enable NVIDIA self-hosted CI (#22976)

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* Enabel nvidia ci for webgpu

* Address precision issues

* fix placement

* Relax more set_rows and div

* Try relaxing all f16

* formatting and naming

* Add comment explaining max_nmse_err logic

Added comment referencing pull request for clarification.
This commit is contained in:
Reese Levine
2026-05-14 09:41:32 -07:00
committed by GitHub
parent 5ec717d125
commit 834a243664
2 changed files with 54 additions and 28 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.github/workflows/build-self-hosted.yml
+25 -26
View File
@@ -120,35 +120,34 @@ jobs:
vulkaninfo --summary
GG_BUILD_VULKAN=1 bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
# TODO: investigate slight precision issues in some operations for test-backend-ops on the WebGPU backend.
#ggml-ci-nvidia-webgpu:
# runs-on: [self-hosted, Linux, NVIDIA]
ggml-ci-nvidia-webgpu:
runs-on: [self-hosted, Linux, NVIDIA]
# steps:
# - name: Clone
# id: checkout
# uses: actions/checkout@v6
steps:
- name: Clone
id: checkout
uses: actions/checkout@v6
# - name: Dawn Dependency
# id: dawn-depends
# run: |
# DAWN_VERSION="v20260317.182325"
# DAWN_OWNER="google"
# DAWN_REPO="dawn"
# DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
# echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
# curl -L -o artifact.tar.gz \
# "https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
# mkdir dawn
# tar -xvf artifact.tar.gz -C dawn --strip-components=1
- name: Dawn Dependency
id: dawn-depends
run: |
DAWN_VERSION="v20260317.182325"
DAWN_OWNER="google"
DAWN_REPO="dawn"
DAWN_ASSET_NAME="Dawn-18eb229ef5f707c1464cc581252e7603c73a3ef0-ubuntu-latest-Release"
echo "Fetching release asset from https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
curl -L -o artifact.tar.gz \
"https://github.com/google/dawn/releases/download/${DAWN_VERSION}/${DAWN_ASSET_NAME}.tar.gz"
mkdir dawn
tar -xvf artifact.tar.gz -C dawn --strip-components=1
# - name: Test
# id: ggml-ci
# run: |
# GG_BUILD_WEBGPU=1 \
# GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
# GG_BUILD_WEBGPU_DAWN_DIR="$GITHUB_WORKSPACE/dawn/lib64/cmake/Dawn" \
# bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
- name: Test
id: ggml-ci
run: |
GG_BUILD_WEBGPU=1 \
GG_BUILD_WEBGPU_DAWN_PREFIX="$GITHUB_WORKSPACE/dawn" \
GG_BUILD_WEBGPU_DAWN_DIR="$GITHUB_WORKSPACE/dawn/lib64/cmake/Dawn" \
bash ./ci/run.sh ~/results/llama.cpp /mnt/llama.cpp
# TODO: provision AMX-compatible machine
#ggml-ci-cpu-amx:
tests/test-backend-ops.cpp
+29 -2
View File
@@ -1128,7 +1128,11 @@ struct test_case {
}
virtual double max_nmse_err(ggml_backend_t backend) {
GGML_UNUSED(backend);
ggml_backend_reg_t reg = ggml_backend_dev_backend_reg(ggml_backend_get_device(backend));
// See https://github.com/ggml-org/llama.cpp/pull/22976 for explanation.
if (contains_f16 && strcmp(ggml_backend_reg_name(reg), "WebGPU") == 0) {
return std::max(max_nmse_err(), 1e-6);
}
return max_nmse_err();
}
@@ -1205,6 +1209,18 @@ struct test_case {
std::vector<ggml_tensor *> sentinels;
std::string current_op_name;
bool contains_f16 = false;
// Used by the WebGPU backend to relax error thresholds on ops on f16 tensors
void check_for_f16_tensor(ggml_context * ctx) {
contains_f16 = false;
for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != nullptr; t = ggml_get_next_tensor(ctx, t)) {
if (t->type == GGML_TYPE_F16) {
contains_f16 = true;
break;
}
}
}
void add_sentinel(ggml_context * ctx) {
if (mode == MODE_PERF || mode == MODE_GRAD || mode == MODE_SUPPORT) {
@@ -1298,6 +1314,7 @@ struct test_case {
ggml_tensor * out = build_graph(ctx);
current_op_name = op_desc(out);
check_for_f16_tensor(ctx);
if (!matches_filter(out, op_names_filter)) {
//printf(" %s: skipping\n", op_desc(out).c_str());
@@ -1973,9 +1990,19 @@ struct test_unary : public test_case {
}
void initialize_tensors(ggml_context * ctx) override {
float min = -150.f;
float max = 150.f;
// Keep FP16 exp/expm1 inputs in-range so all backends stay finite instead of
// disagreeing on whether overflow saturates to max-F16 or produces +inf.
if (type == GGML_TYPE_F16 && (op == GGML_UNARY_OP_EXP || op == GGML_UNARY_OP_EXPM1)) {
min = -10.f;
max = 10.f;
}
for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
// test extended range of values to check for NaNs in GELU
init_tensor_uniform(t, -150.f, 150.f);
init_tensor_uniform(t, min, max);
}
}