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ggml-webgpu: fix supports_op condition for GET_ROWS (llama/28978)

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* fix get_rows vec4 handling

* Add src strides checking to vec4_aligned of get_rows and the new test case.
This commit is contained in:
Masashi Yoshimura
2026-09-23 20:46:47 +03:00
committed by Georgi Gerganov
parent 26d6dcfce6
commit bdf289e0d7
2 changed files with 31 additions and 26 deletions
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ggml/src/ggml-webgpu/ggml-webgpu.cpp
+22 -23
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@@ -1518,15 +1518,24 @@ static webgpu_encoded_op ggml_webgpu_get_rows(webgpu_context & ctx,
shader_lib_ctx.dst = dst;
shader_lib_ctx.max_wg_size = ctx->global_ctx->capabilities.limits.maxComputeInvocationsPerWorkgroup;
webgpu_pipeline pipeline = ctx->shader_lib->get_get_rows_pipeline(shader_lib_ctx);
auto * decisions = static_cast<ggml_webgpu_generic_shader_decisions *>(pipeline.context.get());
const uint32_t offset_src = (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src) / ggml_type_size(src->type));
const uint32_t offset_dst = (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type));
const uint32_t stride_src1 = (uint32_t) (src->nb[1] / ggml_type_size(src->type));
const uint32_t stride_src2 = (uint32_t) (src->nb[2] / ggml_type_size(src->type));
const uint32_t stride_src3 = (uint32_t) (src->nb[3] / ggml_type_size(src->type));
std::vector<uint32_t> params = { (uint32_t) (ggml_webgpu_tensor_misalignment(ctx, src) / ggml_type_size(src->type)),
const bool vec4_aligned = offset_src % 4 == 0 && offset_dst % 4 == 0 && stride_src1 % 4 == 0 &&
stride_src2 % 4 == 0 && stride_src3 % 4 == 0;
webgpu_pipeline pipeline = ctx->shader_lib->get_get_rows_pipeline(shader_lib_ctx, vec4_aligned);
auto * decisions = static_cast<ggml_webgpu_get_rows_shader_decisions *>(pipeline.context.get());
std::vector<uint32_t> params = { offset_src,
(uint32_t) (ggml_webgpu_tensor_misalignment(ctx, idx) / ggml_type_size(idx->type)),
(uint32_t) (ggml_webgpu_tensor_misalignment(ctx, dst) / ggml_type_size(dst->type)),
(uint32_t) (src->nb[1] / ggml_type_size(src->type)),
(uint32_t) (src->nb[2] / ggml_type_size(src->type)),
(uint32_t) (src->nb[3] / ggml_type_size(src->type)),
offset_dst,
stride_src1,
stride_src2,
stride_src3,
(uint32_t) (idx->nb[0] / ggml_type_size(idx->type)),
(uint32_t) (idx->nb[1] / ggml_type_size(idx->type)),
(uint32_t) (idx->nb[2] / ggml_type_size(idx->type)),
@@ -1544,7 +1553,7 @@ static webgpu_encoded_op ggml_webgpu_get_rows(webgpu_context & ctx,
ggml_webgpu_make_tensor_bind_group_entry(ctx, 1, idx),
ggml_webgpu_make_tensor_bind_group_entry(ctx, 2, dst) };
uint32_t blocks_per_row = (uint32_t) (dst->ne[0] / (src->type == GGML_TYPE_F32 && dst->ne[0] % 4 == 0 ? 4 : 1));
uint32_t blocks_per_row = (uint32_t) (dst->ne[0] / (decisions->vectorized ? 4 : 1));
uint32_t total_rows = (uint32_t) (dst->ne[1] * dst->ne[2] * dst->ne[3]);
uint32_t total_threads = float_parallel ? blocks_per_row * total_rows : total_rows;
uint32_t wg_x = CEIL_DIV(total_threads, decisions->wg_size);
@@ -4333,22 +4342,12 @@ static bool ggml_backend_webgpu_device_supports_op(ggml_backend_dev_t dev, const
src0->type == GGML_TYPE_F32 && (src1->type == GGML_TYPE_I64 || src1->type == GGML_TYPE_I32));
break;
case GGML_OP_GET_ROWS:
{
const size_t storage_alignment =
ctx->webgpu_global_ctx->capabilities.limits.minStorageBufferOffsetAlignment;
const size_t src_address_unit =
src0->type == GGML_TYPE_F32 && op->ne[0] % 4 == 0 ? 4 * sizeof(float) : ggml_type_size(src0->type);
if (ggml_webgpu_tensor_misalignment(src0, storage_alignment) % src_address_unit != 0) {
break;
}
if (src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16 ||
ggml_webgpu_supported_qtype(src0->type)) {
supports_op = (op->type == GGML_TYPE_F32);
} else if (src0->type == GGML_TYPE_I32) {
supports_op = op->type == GGML_TYPE_I32;
}
break;
if (src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16 || ggml_webgpu_supported_qtype(src0->type)) {
supports_op = (op->type == GGML_TYPE_F32);
} else if (src0->type == GGML_TYPE_I32) {
supports_op = op->type == GGML_TYPE_I32;
}
break;
case GGML_OP_MUL_MAT:
{
switch (src1->type) {