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sycl : support kernel type fp16 for conv2d_dw (#25653)

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This commit is contained in:
Neo Zhang
2026-07-15 10:31:10 +03:00
committed by GitHub
parent 22b208b1ca
commit ae9291e16b
1 changed files with 25 additions and 13 deletions
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ggml/src/ggml-sycl/conv2d-dw.cpp
+25 -13
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@@ -71,8 +71,8 @@ struct dw_cwhn_layout {
}
};
template <typename Layout>
static void conv2d_dw_kernel(const float * input, const float * kernel, float * output,
template <typename KernelT, typename Layout>
static void conv2d_dw_kernel(const float * input, const KernelT * kernel, float * output,
const conv2d_dw_params p, const sycl::nd_item<3> & item_ct1) {
const int global_idx = item_ct1.get_local_id(2) +
item_ct1.get_group(2) * item_ct1.get_local_range(2);
@@ -93,15 +93,15 @@ static void conv2d_dw_kernel(const float * input, const float * kernel, float *
for (int kx = bounds.x_min; kx < bounds.x_max; ++kx) {
const int in_x = dw_calculate_input_coord(out_x, kx, p.stride_x, p.dilation_x, p.padding_x);
acc += input[Layout::input_index(n, c, in_y, in_x, p)] *
kernel[Layout::kernel_index(c, ky, kx, p)];
static_cast<float>(kernel[Layout::kernel_index(c, ky, kx, p)]);
}
}
output[Layout::output_index(n, c, out_y, out_x, p)] = acc;
}
template <typename Layout>
static void conv2d_dw_sycl(const float * x_d, const float * w_d, float * y_d,
template <typename KernelT, typename Layout>
static void conv2d_dw_sycl(const float * x_d, const KernelT * w_d, float * y_d,
const conv2d_dw_params p, const queue_ptr & stream) {
const int total = p.batches * p.channels * p.out_h * p.out_w;
const int num_blocks = (total + SYCL_CONV2D_DW_BLOCK_SIZE - 1) / SYCL_CONV2D_DW_BLOCK_SIZE;
@@ -109,7 +109,7 @@ static void conv2d_dw_sycl(const float * x_d, const float * w_d, float * y_d,
const sycl::range<3> block_nums(1, 1, num_blocks);
stream->parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1) {
conv2d_dw_kernel<Layout>(x_d, w_d, y_d, p, item_ct1);
conv2d_dw_kernel<KernelT, Layout>(x_d, w_d, y_d, p, item_ct1);
});
}
@@ -119,9 +119,9 @@ void ggml_sycl_op_conv2d_dw(ggml_backend_sycl_context & ctx, ggml_tensor * dst)
const ggml_tensor * kernel = dst->src[0];
const ggml_tensor * input = dst->src[1];
GGML_ASSERT(kernel->type == GGML_TYPE_F32 && input->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32);
GGML_ASSERT((kernel->type == GGML_TYPE_F32 || kernel->type == GGML_TYPE_F16) &&
input->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32);
const float * w_d = (const float *) kernel->data;
const float * x_d = (const float *) input->data;
float * y_d = (float *) dst->data;
@@ -148,11 +148,23 @@ void ggml_sycl_op_conv2d_dw(ggml_backend_sycl_context & ctx, ggml_tensor * dst)
const queue_ptr stream = ctx.stream();
if (ggml_is_contiguous(input)) {
conv2d_dw_sycl<dw_whcn_layout>(x_d, w_d, y_d, params, stream);
} else if (ggml_is_contiguous_channels(input)) {
conv2d_dw_sycl<dw_cwhn_layout>(x_d, w_d, y_d, params, stream);
if (kernel->type == GGML_TYPE_F16) {
const sycl::half * w_d = (const sycl::half *) kernel->data;
if (ggml_is_contiguous(input)) {
conv2d_dw_sycl<sycl::half, dw_whcn_layout>(x_d, w_d, y_d, params, stream);
} else if (ggml_is_contiguous_channels(input)) {
conv2d_dw_sycl<sycl::half, dw_cwhn_layout>(x_d, w_d, y_d, params, stream);
} else {
GGML_ABORT("Unsupported memory layout for conv2d_dw");
}
} else {
GGML_ABORT("Unsupported memory layout for conv2d_dw");
const float * w_d = (const float *) kernel->data;
if (ggml_is_contiguous(input)) {
conv2d_dw_sycl<float, dw_whcn_layout>(x_d, w_d, y_d, params, stream);
} else if (ggml_is_contiguous_channels(input)) {
conv2d_dw_sycl<float, dw_cwhn_layout>(x_d, w_d, y_d, params, stream);
} else {
GGML_ABORT("Unsupported memory layout for conv2d_dw");
}
}
}