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SYCL: Add GGML_OP_MEAN operator support (#16009)

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* SYCL: Add GGML_OP_MEAN operator support

* SYCL: Fix formatting for GGML_OP_MEAN case

* Update ggml/src/ggml-sycl/ggml-sycl.cpp

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
This commit is contained in:
yael-works
2025-10-16 07:21:28 +03:00
committed by GitHub
parent 7adc79c032
commit ee50ee1ead
1 changed files with 34 additions and 0 deletions
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34
ggml/src/ggml-sycl/ggml-sycl.cpp
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@@ -2151,6 +2151,30 @@ inline void ggml_sycl_op_sum_rows(ggml_backend_sycl_context & ctx, ggml_tensor *
sum_rows_f32_sycl(src0_dd, dst_dd, ncols, nrows, main_stream); sum_rows_f32_sycl(src0_dd, dst_dd, ncols, nrows, main_stream);
} }
inline void ggml_sycl_op_mean(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
GGML_ASSERT(dst->src[0]->type == GGML_TYPE_F32);
GGML_ASSERT(dst->type == GGML_TYPE_F32);
dpct::queue_ptr main_stream = ctx.stream();
SYCL_CHECK(ggml_sycl_set_device(ctx.device));
const float * src0_dd = static_cast<const float *>(dst->src[0]->data);
float * dst_dd = static_cast<float *>(dst->data);
const int64_t ncols = dst->src[0]->ne[0];
const int64_t nrows = ggml_nrows(dst->src[0]);
sum_rows_f32_sycl(src0_dd, dst_dd, ncols, nrows, main_stream);
main_stream->parallel_for(
sycl::range<1>(nrows),
[=](sycl::id<1> row) {
dst_dd[row] /= ncols;
}
);
}
inline void ggml_sycl_op_argsort(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { inline void ggml_sycl_op_argsort(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
GGML_ASSERT(dst->src[0]->type == GGML_TYPE_F32); GGML_ASSERT(dst->src[0]->type == GGML_TYPE_F32);
GGML_ASSERT(dst->type == GGML_TYPE_I32); GGML_ASSERT(dst->type == GGML_TYPE_I32);
@@ -3535,6 +3559,12 @@ static void ggml_sycl_sum_rows(ggml_backend_sycl_context & ctx, ggml_tensor * ds
ggml_sycl_op_sum_rows(ctx, dst); ggml_sycl_op_sum_rows(ctx, dst);
} }
static void ggml_sycl_mean(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/1);
GGML_ASSERT(ggml_is_contiguous(dst->src[0]));
ggml_sycl_op_mean(ctx, dst);
}
static void ggml_sycl_argsort(ggml_backend_sycl_context & ctx, ggml_tensor * dst) { static void ggml_sycl_argsort(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/1); scope_op_debug_print scope_dbg_print(__func__, dst, /*num_src=*/1);
GGML_ASSERT(ggml_is_contiguous(dst->src[0])); GGML_ASSERT(ggml_is_contiguous(dst->src[0]));
@@ -3784,6 +3814,9 @@ static bool ggml_sycl_compute_forward(ggml_backend_sycl_context & ctx, struct gg
case GGML_OP_SUM_ROWS: case GGML_OP_SUM_ROWS:
ggml_sycl_sum_rows(ctx, dst); ggml_sycl_sum_rows(ctx, dst);
break; break;
case GGML_OP_MEAN:
ggml_sycl_mean(ctx, dst);
break;
case GGML_OP_ARGSORT: case GGML_OP_ARGSORT:
ggml_sycl_argsort(ctx, dst); ggml_sycl_argsort(ctx, dst);
break; break;
@@ -4431,6 +4464,7 @@ static bool ggml_backend_sycl_device_supports_op(ggml_backend_dev_t dev, const g
return op->src[0]->type == GGML_TYPE_F32 && op->op_params[0] == GGML_SCALE_MODE_NEAREST; return op->src[0]->type == GGML_TYPE_F32 && op->op_params[0] == GGML_SCALE_MODE_NEAREST;
case GGML_OP_SUM: case GGML_OP_SUM:
case GGML_OP_SUM_ROWS: case GGML_OP_SUM_ROWS:
case GGML_OP_MEAN:
case GGML_OP_ARGSORT: case GGML_OP_ARGSORT:
return ggml_is_contiguous(op->src[0]); return ggml_is_contiguous(op->src[0]);
case GGML_OP_POOL_2D: case GGML_OP_POOL_2D: