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chore: add missing override declarations #1800

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Merged
leejet merged 1 commit into from
Jul 21, 2026
Merged

chore: add missing override declarations #1800

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20 changes: 10 additions & 10 deletions src/core/ggml_extend.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -3309,7 +3309,7 @@ class UnaryBlock : public GGMLBlock {

class Identity : public UnaryBlock {
public:
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
return x;
}
};
Expand Down Expand Up @@ -3368,7 +3368,7 @@ class Linear : public UnaryBlock {
force_prec_f32 = force_prec_f32_;
}

ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
ggml_tensor* w = params["weight"];
ggml_tensor* b = nullptr;
if (bias) {
Expand Down Expand Up @@ -3422,7 +3422,7 @@ class Embedding : public UnaryBlock {
}

ggml_tensor* forward(GGMLRunnerContext* ctx,
ggml_tensor* input_ids) {
ggml_tensor* input_ids) override {
// input_ids: [N, n_token]
auto weight = params["weight"];

Expand Down Expand Up @@ -3482,11 +3482,11 @@ class Conv2d : public UnaryBlock {
scale = scale_value;
}

std::string get_desc() {
std::string get_desc() override {
return "Conv2d";
}

ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
ggml_tensor* w = params["weight"];
ggml_tensor* b = nullptr;
if (bias) {
Expand Down Expand Up @@ -3569,11 +3569,11 @@ class Conv2d_grouped : public UnaryBlock {
scale = scale_value;
}

std::string get_desc() {
std::string get_desc() override {
return "Conv2d_grouped";
}

ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
ggml_tensor* w = params["weight"];
ggml_tensor* b = nullptr;
if (bias) {
Expand Down Expand Up @@ -3725,7 +3725,7 @@ class Conv3d : public UnaryBlock {
bias(bias),
force_prec_f32(force_prec_f32) {}

ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
ggml_tensor* w = params["weight"];
ggml_tensor* b = nullptr;
if (ctx->weight_adapter) {
Expand Down Expand Up @@ -3778,7 +3778,7 @@ class LayerNorm : public UnaryBlock {
elementwise_affine(elementwise_affine),
bias(bias) {}

ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
ggml_tensor* w = nullptr;
ggml_tensor* b = nullptr;

Expand Down Expand Up @@ -3865,7 +3865,7 @@ class RMSNorm : public UnaryBlock {
: hidden_size(hidden_size),
eps(eps) {}

ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
ggml_tensor* w = params["weight"];
if (ctx->weight_adapter) {
w = ctx->weight_adapter->patch_weight(ctx->ggml_ctx, ctx->backend, w, prefix + "weight");
Expand Down
2 changes: 1 addition & 1 deletion src/model/common/block.hpp
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Expand Up @@ -450,7 +450,7 @@ class SpatialTransformer : public GGMLBlock {
int64_t context_dim = 768; // hidden_size, 1024 for VERSION_SD2
bool use_linear = false;

void init_params(ggml_context* ctx, const String2TensorStorage& tensor_storage_map = {}, const std::string prefix = "") {
void init_params(ggml_context* ctx, const String2TensorStorage& tensor_storage_map = {}, const std::string prefix = "") override {
auto iter = tensor_storage_map.find(prefix + "proj_out.weight");
if (iter != tensor_storage_map.end()) {
int64_t inner_dim = n_head * d_head;
Expand Down
2 changes: 1 addition & 1 deletion src/model/te/llm.hpp
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Expand Up @@ -285,7 +285,7 @@ namespace LLM {
bool add_unit_offset = false)
: hidden_size(hidden_size), eps(eps), add_unit_offset(add_unit_offset) {}

ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) {
ggml_tensor* forward(GGMLRunnerContext* ctx, ggml_tensor* x) override {
ggml_tensor* w = params["weight"];
if (ctx->weight_adapter) {
w = ctx->weight_adapter->patch_weight(ctx->ggml_ctx, ctx->backend, w, prefix + "weight");
Expand Down
2 changes: 1 addition & 1 deletion src/model_io/gguf_io.h
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Expand Up @@ -21,7 +21,7 @@ bool write_gguf_file(const std::string& file_path,
class GGUFStreamingWriter : public StreamingModelWriter {
public:
GGUFStreamingWriter() = default;
~GGUFStreamingWriter();
~GGUFStreamingWriter() override;

bool write_metadata(const std::string& file_path,
const std::vector<TensorWritePlan>& tensors,
Expand Down
12 changes: 6 additions & 6 deletions src/runtime/denoiser.hpp
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Expand Up @@ -1153,9 +1153,9 @@ struct CompVisDenoiser : public Denoiser {
return {c_skip, c_out, c_in};
}

virtual sd::Tensor<float> noise_scaling(float sigma,
const sd::Tensor<float>& noise,
const sd::Tensor<float>& latent) override {
sd::Tensor<float> noise_scaling(float sigma,
const sd::Tensor<float>& noise,
const sd::Tensor<float>& latent) override {
GGML_ASSERT(noise.numel() == latent.numel());
return latent + noise * sigma;
}
Expand All @@ -1165,7 +1165,7 @@ struct CompVisDenoiser : public Denoiser {
return latent;
}

float noise_level_to_sigma(float noise_level) {
float noise_level_to_sigma(float noise_level) override {
return noise_level / (1.0f - noise_level);
}
};
Expand Down Expand Up @@ -1256,7 +1256,7 @@ struct DiscreteFlowDenoiser : public Denoiser {
return latent * (1.0f / (1.0f - sigma));
}

float noise_level_to_sigma(float noise_level) {
float noise_level_to_sigma(float noise_level) override {
return noise_level;
}
};
Expand Down Expand Up @@ -1396,7 +1396,7 @@ struct MiniT2IFlowDenoiser : public Denoiser {
return latent;
}

float noise_level_to_sigma(float noise_level) {
float noise_level_to_sigma(float noise_level) override {
SD_UNUSED(noise_level);
return 1.0f;
}
Expand Down
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