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merged 4 commits into from
Oct 18, 2025
Merged

chore: add .clang-tidy configuration and apply modernize checks #902

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4880210
chore: add .clang-tidy configuration and apply modernize checks
leejet Oct 18, 2025
22e2faf
fix
leejet Oct 18, 2025
69de5ec
more fixes
leejet Oct 18, 2025
fd3ffe0
more fixes
leejet Oct 18, 2025
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10 changes: 10 additions & 0 deletions .clang-tidy
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Original file line number Diff line number Diff line change
@@ -0,0 +1,10 @@
Checks: >
modernize-make-shared,
modernize-use-nullptr,
modernize-use-override,
modernize-pass-by-value,
modernize-return-braced-init-list,
modernize-deprecated-headers,
HeaderFilterRegex: '^$'
WarningsAsErrors: ''
FormatStyle: none
36 changes: 18 additions & 18 deletions clip.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -550,7 +550,7 @@ class CLIPEmbeddings : public GGMLBlock {
int64_t num_positions;
bool force_clip_f32;

void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") {
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") override {
enum ggml_type token_wtype = GGML_TYPE_F32;
if (!force_clip_f32) {
token_wtype = get_type(prefix + "token_embedding.weight", tensor_types, GGML_TYPE_F32);
Expand Down Expand Up @@ -587,7 +587,7 @@ class CLIPEmbeddings : public GGMLBlock {

GGML_ASSERT(input_ids->ne[0] == position_embed_weight->ne[1]);
input_ids = ggml_reshape_3d(ctx, input_ids, input_ids->ne[0], 1, input_ids->ne[1]);
auto token_embedding = ggml_get_rows(ctx, custom_embed_weight != NULL ? custom_embed_weight : token_embed_weight, input_ids);
auto token_embedding = ggml_get_rows(ctx, custom_embed_weight != nullptr ? custom_embed_weight : token_embed_weight, input_ids);
token_embedding = ggml_reshape_3d(ctx, token_embedding, token_embedding->ne[0], token_embedding->ne[1], token_embedding->ne[3]);

// token_embedding + position_embedding
Expand All @@ -606,7 +606,7 @@ class CLIPVisionEmbeddings : public GGMLBlock {
int64_t image_size;
int64_t num_patches;
int64_t num_positions;
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") {
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") override {
enum ggml_type patch_wtype = GGML_TYPE_F16;
enum ggml_type class_wtype = GGML_TYPE_F32;
enum ggml_type position_wtype = GGML_TYPE_F32;
Expand Down Expand Up @@ -641,10 +641,10 @@ class CLIPVisionEmbeddings : public GGMLBlock {
// concat(patch_embedding, class_embedding) + position_embedding
struct ggml_tensor* patch_embedding;
int64_t N = pixel_values->ne[3];
patch_embedding = ggml_nn_conv_2d(ctx, pixel_values, patch_embed_weight, NULL, patch_size, patch_size); // [N, embed_dim, image_size // pacht_size, image_size // pacht_size]
patch_embedding = ggml_reshape_3d(ctx, patch_embedding, num_patches, embed_dim, N); // [N, embed_dim, num_patches]
patch_embedding = ggml_cont(ctx, ggml_permute(ctx, patch_embedding, 1, 0, 2, 3)); // [N, num_patches, embed_dim]
patch_embedding = ggml_reshape_4d(ctx, patch_embedding, 1, embed_dim, num_patches, N); // [N, num_patches, embed_dim, 1]
patch_embedding = ggml_nn_conv_2d(ctx, pixel_values, patch_embed_weight, nullptr, patch_size, patch_size); // [N, embed_dim, image_size // pacht_size, image_size // pacht_size]
patch_embedding = ggml_reshape_3d(ctx, patch_embedding, num_patches, embed_dim, N); // [N, embed_dim, num_patches]
patch_embedding = ggml_cont(ctx, ggml_permute(ctx, patch_embedding, 1, 0, 2, 3)); // [N, num_patches, embed_dim]
patch_embedding = ggml_reshape_4d(ctx, patch_embedding, 1, embed_dim, num_patches, N); // [N, num_patches, embed_dim, 1]

struct ggml_tensor* class_embedding = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, embed_dim, N);
class_embedding = ggml_repeat(ctx, class_embed_weight, class_embedding); // [N, embed_dim]
Expand All @@ -669,7 +669,7 @@ enum CLIPVersion {

class CLIPTextModel : public GGMLBlock {
protected:
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") {
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") override {
if (version == OPEN_CLIP_VIT_BIGG_14) {
enum ggml_type wtype = GGML_TYPE_F32;
params["text_projection"] = ggml_new_tensor_2d(ctx, wtype, projection_dim, hidden_size);
Expand Down Expand Up @@ -735,8 +735,8 @@ class CLIPTextModel : public GGMLBlock {
if (return_pooled) {
auto text_projection = params["text_projection"];
ggml_tensor* pooled = ggml_view_1d(ctx, x, hidden_size, x->nb[1] * max_token_idx);
if (text_projection != NULL) {
pooled = ggml_nn_linear(ctx, pooled, text_projection, NULL);
if (text_projection != nullptr) {
pooled = ggml_nn_linear(ctx, pooled, text_projection, nullptr);
} else {
LOG_DEBUG("identity projection");
}
Expand Down Expand Up @@ -814,7 +814,7 @@ class CLIPProjection : public UnaryBlock {
int64_t out_features;
bool transpose_weight;

void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") {
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, const std::string prefix = "") override {
enum ggml_type wtype = get_type(prefix + "weight", tensor_types, GGML_TYPE_F32);
if (transpose_weight) {
params["weight"] = ggml_new_tensor_2d(ctx, wtype, out_features, in_features);
Expand All @@ -831,12 +831,12 @@ class CLIPProjection : public UnaryBlock {
out_features(out_features),
transpose_weight(transpose_weight) {}

struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x) {
struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x) override {
struct ggml_tensor* w = params["weight"];
if (transpose_weight) {
w = ggml_cont(ctx, ggml_transpose(ctx, w));
}
return ggml_nn_linear(ctx, x, w, NULL);
return ggml_nn_linear(ctx, x, w, nullptr);
}
};

Expand Down Expand Up @@ -894,7 +894,7 @@ struct CLIPTextModelRunner : public GGMLRunner {
model.init(params_ctx, tensor_types, prefix);
}

std::string get_desc() {
std::string get_desc() override {
return "clip";
}

Expand All @@ -921,17 +921,17 @@ struct CLIPTextModelRunner : public GGMLRunner {

struct ggml_cgraph* build_graph(struct ggml_tensor* input_ids,
int num_custom_embeddings = 0,
void* custom_embeddings_data = NULL,
void* custom_embeddings_data = nullptr,
size_t max_token_idx = 0,
bool return_pooled = false,
int clip_skip = -1) {
struct ggml_cgraph* gf = ggml_new_graph(compute_ctx);

input_ids = to_backend(input_ids);

struct ggml_tensor* embeddings = NULL;
struct ggml_tensor* embeddings = nullptr;

if (num_custom_embeddings > 0 && custom_embeddings_data != NULL) {
if (num_custom_embeddings > 0 && custom_embeddings_data != nullptr) {
auto token_embed_weight = model.get_token_embed_weight();
auto custom_embeddings = ggml_new_tensor_2d(compute_ctx,
token_embed_weight->type,
Expand All @@ -958,7 +958,7 @@ struct CLIPTextModelRunner : public GGMLRunner {
bool return_pooled,
int clip_skip,
ggml_tensor** output,
ggml_context* output_ctx = NULL) {
ggml_context* output_ctx = nullptr) {
auto get_graph = [&]() -> struct ggml_cgraph* {
return build_graph(input_ids, num_custom_embeddings, custom_embeddings_data, max_token_idx, return_pooled, clip_skip);
};
Expand Down
14 changes: 7 additions & 7 deletions common.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -121,7 +121,7 @@ class ResBlock : public GGMLBlock {
}
}

virtual struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x, struct ggml_tensor* emb = NULL) {
virtual struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x, struct ggml_tensor* emb = nullptr) {
// For dims==3, we reduce dimension from 5d to 4d by merging h and w, in order not to change ggml
// [N, c, t, h, w] => [N, c, t, h * w]
// x: [N, channels, h, w] if dims == 2 else [N, channels, t, h, w]
Expand All @@ -131,7 +131,7 @@ class ResBlock : public GGMLBlock {
auto out_layers_0 = std::dynamic_pointer_cast<GroupNorm32>(blocks["out_layers.0"]);
auto out_layers_3 = std::dynamic_pointer_cast<UnaryBlock>(blocks["out_layers.3"]);

if (emb == NULL) {
if (emb == nullptr) {
GGML_ASSERT(skip_t_emb);
}

Expand Down Expand Up @@ -182,7 +182,7 @@ class GEGLU : public UnaryBlock {
int64_t dim_in;
int64_t dim_out;

void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, std::string prefix = "") {
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, std::string prefix = "") override {
enum ggml_type wtype = get_type(prefix + "proj.weight", tensor_types, GGML_TYPE_F32);
enum ggml_type bias_wtype = GGML_TYPE_F32;
params["proj.weight"] = ggml_new_tensor_2d(ctx, wtype, dim_in, dim_out * 2);
Expand All @@ -193,7 +193,7 @@ class GEGLU : public UnaryBlock {
GEGLU(int64_t dim_in, int64_t dim_out)
: dim_in(dim_in), dim_out(dim_out) {}

struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x) {
struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x) override {
// x: [ne3, ne2, ne1, dim_in]
// return: [ne3, ne2, ne1, dim_out]
struct ggml_tensor* w = params["proj.weight"];
Expand Down Expand Up @@ -222,7 +222,7 @@ class GELU : public UnaryBlock {
blocks["proj"] = std::shared_ptr<GGMLBlock>(new Linear(dim_in, dim_out, bias));
}

struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x) {
struct ggml_tensor* forward(struct ggml_context* ctx, struct ggml_tensor* x) override {
// x: [ne3, ne2, ne1, dim_in]
// return: [ne3, ne2, ne1, dim_out]
auto proj = std::dynamic_pointer_cast<Linear>(blocks["proj"]);
Expand Down Expand Up @@ -325,7 +325,7 @@ class CrossAttention : public GGMLBlock {
auto k = to_k->forward(ctx, context); // [N, n_context, inner_dim]
auto v = to_v->forward(ctx, context); // [N, n_context, inner_dim]

x = ggml_nn_attention_ext(ctx, backend, q, k, v, n_head, NULL, false, false, flash_attn); // [N, n_token, inner_dim]
x = ggml_nn_attention_ext(ctx, backend, q, k, v, n_head, nullptr, false, false, flash_attn); // [N, n_token, inner_dim]

x = to_out_0->forward(ctx, x); // [N, n_token, query_dim]
return x;
Expand Down Expand Up @@ -483,7 +483,7 @@ class SpatialTransformer : public GGMLBlock {

class AlphaBlender : public GGMLBlock {
protected:
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, std::string prefix = "") {
void init_params(struct ggml_context* ctx, const String2GGMLType& tensor_types = {}, std::string prefix = "") override {
// Get the type of the "mix_factor" tensor from the input tensors map with the specified prefix
enum ggml_type wtype = GGML_TYPE_F32;
params["mix_factor"] = ggml_new_tensor_1d(ctx, wtype, 1);
Expand Down
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