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llama.cpp
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improve debugging message

This commit is contained in:
Xuan Son Nguyen 2025-11-02 12:08:49 +01:00
parent 29330dcb55
commit b67a168f10
2 changed files with 40 additions and 17 deletions
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1
ggml/src/ggml-metal/ggml-metal-device.m
View File

@ -703,6 +703,7 @@ bool ggml_metal_device_supports_op(ggml_metal_device_t dev, const struct ggml_te
case GGML_OP_ARANGE:
return true;
case GGML_OP_FLASH_ATTN_EXT:
return false;
// for new head sizes, add checks here
if (op->src[0]->ne[0] != 32 &&
op->src[0]->ne[0] != 40 &&

56
tools/mtmd/clip.cpp
View File

@ -3209,6 +3209,7 @@ struct clip_model_loader {
struct support_info_graph {
// whether the clip_ctx.backend supports flash attention
bool fattn = true;
ggml_tensor * fattn_op = nullptr; // for debugging
std::vector<support_info_op> ops;
};
@ -3220,9 +3221,23 @@ struct clip_model_loader {
// try to enable flash attention to see if it's supported
ctx_clip.flash_attn_type = CLIP_FLASH_ATTN_TYPE_ENABLED;
info = alloc_compute_meta(ctx_clip);
if (!info.fattn) {
LOG_WRN("%s: flash attention not supported, memory usage will increase\n", __func__);
// TODO: maybe log more details about why flash attention is not supported
if (!info.fattn && info.fattn_op) {
auto op = info.fattn_op;
LOG_WRN("%s: *****************************************************************\n", __func__);
LOG_WRN("%s: WARNING: flash attention not supported by %s, memory usage will increase\n", __func__, ggml_backend_name(ctx_clip.backend));
LOG_WRN("%s: op params: \n", __func__);
static auto print_shape = [](const char * fn, const char * name, ggml_tensor * t) {
LOG_WRN("%s: %s: type = %s, ne = [%d %d %d %d], nb = [%d %d %d %d]\n", fn,
name, ggml_type_name(t->type),
t->ne[0], t->ne[1], t->ne[2], t->ne[3],
t->nb[0], t->nb[1], t->nb[2], t->nb[3]);
};
print_shape(__func__, " dst", op);
print_shape(__func__, "src0", op->src[0]);
print_shape(__func__, "src1", op->src[1]);
print_shape(__func__, "src2", op->src[2]);
LOG_WRN("%s: please report this on github as an issue\n", __func__);
LOG_WRN("%s: *****************************************************************\n", __func__);
ctx_clip.flash_attn_type = CLIP_FLASH_ATTN_TYPE_DISABLED;
alloc_compute_meta(ctx_clip);
}
@ -3238,13 +3253,28 @@ struct clip_model_loader {
// print ops that are not supported by the GPU backend (if there is one)
if (ctx_clip.backend && ctx_clip.backend != ctx_clip.backend_cpu) {
std::vector<support_info_op> unsupported_ops;
for (const auto & op : info.ops) {
if (!op.is_accel) {
LOG_WRN("%s: op %16s is not supported by the CLIP backend: type = %s, ne = [%d %d %d %d]\n", __func__,
unsupported_ops.push_back(op);
}
}
if (!unsupported_ops.empty()) {
LOG_WRN("%s: *****************************************************************\n", __func__);
LOG_WRN("%s: WARNING: the CLIP graph uses unsupported operators by the backend\n", __func__);
LOG_WRN("%s: the performance will be suboptimal \n", __func__);
LOG_WRN("%s: list of unsupported ops (backend=%s):\n", __func__, ggml_backend_name(ctx_clip.backend));
for (const auto & op : unsupported_ops) {
LOG_WRN("%s: %16s: type = %s, ne = [%d %d %d %d]\n", __func__,
ggml_op_name(op.op->op),
ggml_type_name(op.op->type),
op.op->ne[0], op.op->ne[1], op.op->ne[2], op.op->ne[3]);
}
LOG_WRN("%s: flash attention is %s\n", __func__,
(ctx_clip.flash_attn_type == CLIP_FLASH_ATTN_TYPE_ENABLED) ? "enabled" : "disabled");
LOG_WRN("%s: please report this on github as an issue\n", __func__);
LOG_WRN("%s: ref: https://github.com/ggml-org/llama.cpp/pull/16837#issuecomment-3461676118\n", __func__);
LOG_WRN("%s: *****************************************************************\n", __func__);
}
}
}
@ -3287,8 +3317,9 @@ struct clip_model_loader {
LOG_INF("%s: graph splits = %d, nodes = %d\n", __func__, n_splits, n_nodes);
support_info_graph res {
/*.fattn = */ true,
/*.ops = */ {},
/*.fattn = */ true,
/*.fattn_op = */ nullptr,
/*.ops = */ {},
};
// check op support
@ -3298,7 +3329,8 @@ struct clip_model_loader {
if (!ggml_backend_supports_op(ctx_clip.backend, node)) {
res.ops.back().is_accel = false;
if (node->op == GGML_OP_FLASH_ATTN_EXT) {
res.fattn = false;
res.fattn = false;
res.fattn_op = node;
}
}
}
@ -4576,16 +4608,6 @@ bool clip_image_batch_encode(clip_ctx * ctx, const int n_threads, const clip_ima
return false; // only support batch size of 1
}
if (ggml_backend_sched_get_n_splits(ctx->sched.get()) > 1) {
LOG_WRN("%s: *****************************************************************\n", __func__);
LOG_WRN("%s: WARNING: the CLIP graph uses unsupported operators by the backend\n", __func__);
LOG_WRN("%s: use GGML_SCHED_DEBUG=2 to determine which ops \n", __func__);
LOG_WRN("%s: the performance will be suboptimal \n", __func__);
LOG_WRN("%s: \n", __func__);
LOG_WRN("%s: ref: https://github.com/ggml-org/llama.cpp/pull/16837#issuecomment-3461676118\n", __func__);
LOG_WRN("%s: *****************************************************************\n", __func__);
}
// build the inference graph
ctx->debug_print_tensors.clear();
ggml_backend_sched_reset(ctx->sched.get());