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webgpu : add CONV_2D_DW (depthwise conv2d) kernel (#25847)

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* webgpu : add CONV_2D_DW (depthwise conv2d) kernel

Implement GGML_OP_CONV_2D_DW for the WebGPU backend,
ported from the Vulkan backend's conv2d_dw.comp.

Assisted-by: Claude Opus-4.8

* Remove unnecessary comments in webgpu support

* update supported ops tables, triggered by adding webgpu CONV_2D_DW
This commit is contained in:
m1el
2026-07-22 17:24:44 +09:00
committed by GitHub
parent c5a4a0bb83
commit 7347430f44
5 changed files with 2915 additions and 958 deletions
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ggml/src/ggml-webgpu/ggml-webgpu-shader-lib.hpp
+70
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@@ -355,6 +355,30 @@ struct ggml_webgpu_conv2d_pipeline_key_hash {
}
};
// Same type fields as conv2d plus the input layout (WHCN vs CWHN).
struct ggml_webgpu_conv2d_dw_pipeline_key {
ggml_type weight_type;
ggml_type input_type;
ggml_type output_type;
bool whcn;
bool operator==(const ggml_webgpu_conv2d_dw_pipeline_key & other) const {
return weight_type == other.weight_type && input_type == other.input_type && output_type == other.output_type &&
whcn == other.whcn;
}
};
struct ggml_webgpu_conv2d_dw_pipeline_key_hash {
size_t operator()(const ggml_webgpu_conv2d_dw_pipeline_key & key) const {
size_t seed = 0;
ggml_webgpu_hash_combine(seed, key.weight_type);
ggml_webgpu_hash_combine(seed, key.input_type);
ggml_webgpu_hash_combine(seed, key.output_type);
ggml_webgpu_hash_combine(seed, key.whcn);
return seed;
}
};
/** Im2Col **/
struct ggml_webgpu_im2col_pipeline_key {
ggml_type input_type;
@@ -1210,6 +1234,8 @@ class ggml_webgpu_shader_lib {
soft_max_pipelines;
std::unordered_map<ggml_webgpu_conv2d_pipeline_key, webgpu_pipeline, ggml_webgpu_conv2d_pipeline_key_hash>
conv2d_pipelines;
std::unordered_map<ggml_webgpu_conv2d_dw_pipeline_key, webgpu_pipeline, ggml_webgpu_conv2d_dw_pipeline_key_hash>
conv2d_dw_pipelines;
std::unordered_map<ggml_webgpu_im2col_pipeline_key, webgpu_pipeline, ggml_webgpu_im2col_pipeline_key_hash>
im2col_pipelines;
@@ -3172,6 +3198,50 @@ class ggml_webgpu_shader_lib {
return conv2d_pipelines[key];
}
// whcn selects the input layout: contiguous WHCN vs contiguous-channels CWHN
webgpu_pipeline get_conv2d_dw_pipeline(const ggml_webgpu_shader_lib_context & context, bool whcn) {
ggml_webgpu_conv2d_dw_pipeline_key key = {};
key.weight_type = context.src0->type;
key.input_type = context.src1->type;
key.output_type = context.dst->type;
key.whcn = whcn;
auto it = conv2d_dw_pipelines.find(key);
if (it != conv2d_dw_pipelines.end()) {
return it->second;
}
std::vector<std::string> defines;
std::string variant = whcn ? "conv_2d_dw_whcn" : "conv_2d_dw_cwhn";
auto push_type_defines = [&](const char * prefix, ggml_type type) {
std::string s_prefix = prefix;
if (type == GGML_TYPE_F32) {
defines.push_back(s_prefix + "_F32");
} else if (type == GGML_TYPE_F16) {
defines.push_back(s_prefix + "_F16");
} else {
GGML_ABORT("Unsupported type for CONV_2D_DW shader");
}
};
push_type_defines("WEIGHT", key.weight_type);
push_type_defines("INPUT", key.input_type);
push_type_defines("OUTPUT", key.output_type);
if (whcn) {
defines.push_back("WHCN");
}
defines.push_back(std::string("WG_SIZE=") + std::to_string(context.max_wg_size));
auto processed = preprocessor.preprocess(wgsl_conv2d_dw, defines);
auto decisions = std::make_shared<ggml_webgpu_generic_shader_decisions>();
decisions->wg_size = context.max_wg_size;
webgpu_pipeline pipeline = ggml_webgpu_create_pipeline(device, processed, variant);
pipeline.context = decisions;
conv2d_dw_pipelines[key] = pipeline;
return conv2d_dw_pipelines[key];
}
webgpu_pipeline get_im2col_pipeline(const ggml_webgpu_shader_lib_context & context) {
ggml_webgpu_im2col_pipeline_key key = {};
key.input_type = context.src1->type;