upstream-archive/stable-diffusion.cpp
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feat: overriding quant types for specific tensors on model conversion (#724)

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This commit is contained in:
Wagner Bruna
2025-07-07 13:11:38 -03:00
committed by GitHub
parent dafc32d0dd
commit 6d84a30c66
4 changed files with 71 additions and 14 deletions
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14
examples/cli/main.cpp
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@@ -87,6 +87,7 @@ struct SDParams {
std::string stacked_id_embeddings_path;
std::string input_id_images_path;
sd_type_t wtype = SD_TYPE_COUNT;
std::string tensor_type_rules;
std::string lora_model_dir;
std::string output_path = "output.png";
std::string input_path;
@@ -223,6 +224,7 @@ void print_usage(int argc, const char* argv[]) {
printf(" --upscale-repeats Run the ESRGAN upscaler this many times (default 1)\n");
printf(" --type [TYPE] weight type (examples: f32, f16, q4_0, q4_1, q5_0, q5_1, q8_0, q2_K, q3_K, q4_K)\n");
printf(" If not specified, the default is the type of the weight file\n");
printf(" --tensor-type-rules [EXPRESSION] weight type per tensor pattern (example: \"^vae\\.=f16,model\\.=q8_0\")\n");
printf(" --lora-model-dir [DIR] lora model directory\n");
printf(" -i, --init-img [IMAGE] path to the input image, required by img2img\n");
printf(" --mask [MASK] path to the mask image, required by img2img with mask\n");
@@ -404,6 +406,12 @@ void parse_args(int argc, const char** argv, SDParams& params) {
valid_types.c_str());
exit(1);
}
} else if (arg == "--tensor-type-rules") {
if (++i >= argc) {
invalid_arg = true;
break;
}
params.tensor_type_rules = argv[i];
} else if (arg == "--lora-model-dir") {
if (++i >= argc) {
invalid_arg = true;
@@ -733,6 +741,10 @@ void parse_args(int argc, const char** argv, SDParams& params) {
exit(1);
}
if (params.mode != CONVERT && params.tensor_type_rules.size() > 0) {
fprintf(stderr, "warning: --tensor-type-rules is currently supported only for conversion\n");
}
if (params.seed < 0) {
srand((int)time(NULL));
params.seed = rand();
@@ -845,7 +857,7 @@ int main(int argc, const char* argv[]) {
}
if (params.mode == CONVERT) {
bool success = convert(params.model_path.c_str(), params.vae_path.c_str(), params.output_path.c_str(), params.wtype);
bool success = convert(params.model_path.c_str(), params.vae_path.c_str(), params.output_path.c_str(), params.wtype, params.tensor_type_rules.c_str());
if (!success) {
fprintf(stderr,
"convert '%s'/'%s' to '%s' failed\n",