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https://github.com/leejet/stable-diffusion.cpp.git
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feat: do not convert tensor names by default in convert mode (#1122)
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@ -9,6 +9,7 @@ CLI Options:
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--preview-interval <int> interval in denoising steps between consecutive updates of the image preview file (default is 1, meaning updating at
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every step)
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--canny apply canny preprocessor (edge detection)
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--convert-name convert tensor name (for convert mode)
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-v, --verbose print extra info
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--color colors the logging tags according to level
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--taesd-preview-only prevents usage of taesd for decoding the final image. (for use with --preview tae)
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@ -32,6 +32,7 @@ struct SDCliParams {
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bool verbose = false;
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bool canny_preprocess = false;
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bool convert_name = false;
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preview_t preview_method = PREVIEW_NONE;
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int preview_interval = 1;
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@ -69,6 +70,10 @@ struct SDCliParams {
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"--canny",
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"apply canny preprocessor (edge detection)",
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true, &canny_preprocess},
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{"",
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"--convert-name",
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"convert tensor name (for convert mode)",
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true, &canny_preprocess},
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{"-v",
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"--verbose",
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"print extra info",
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@ -174,6 +179,7 @@ struct SDCliParams {
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<< " verbose: " << (verbose ? "true" : "false") << ",\n"
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<< " color: " << (color ? "true" : "false") << ",\n"
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<< " canny_preprocess: " << (canny_preprocess ? "true" : "false") << ",\n"
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<< " convert_name: " << (convert_name ? "true" : "false") << ",\n"
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<< " preview_method: " << previews_str[preview_method] << ",\n"
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<< " preview_interval: " << preview_interval << ",\n"
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<< " preview_path: \"" << preview_path << "\",\n"
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@ -387,7 +393,8 @@ int main(int argc, const char* argv[]) {
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ctx_params.vae_path.c_str(),
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cli_params.output_path.c_str(),
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ctx_params.wtype,
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ctx_params.tensor_type_rules.c_str());
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ctx_params.tensor_type_rules.c_str(),
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cli_params.convert_name);
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if (!success) {
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LOG_ERROR("convert '%s'/'%s' to '%s' failed",
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ctx_params.model_path.c_str(),
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11
model.cpp
11
model.cpp
@ -1783,7 +1783,12 @@ int64_t ModelLoader::get_params_mem_size(ggml_backend_t backend, ggml_type type)
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return mem_size;
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}
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bool convert(const char* input_path, const char* vae_path, const char* output_path, sd_type_t output_type, const char* tensor_type_rules) {
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bool convert(const char* input_path,
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const char* vae_path,
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const char* output_path,
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sd_type_t output_type,
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const char* tensor_type_rules,
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bool convert_name) {
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ModelLoader model_loader;
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if (!model_loader.init_from_file(input_path)) {
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@ -1797,7 +1802,9 @@ bool convert(const char* input_path, const char* vae_path, const char* output_pa
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return false;
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}
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}
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model_loader.convert_tensors_name();
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if (convert_name) {
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model_loader.convert_tensors_name();
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}
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bool success = model_loader.save_to_gguf_file(output_path, (ggml_type)output_type, tensor_type_rules);
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return success;
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}
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@ -365,7 +365,8 @@ SD_API bool convert(const char* input_path,
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const char* vae_path,
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const char* output_path,
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enum sd_type_t output_type,
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const char* tensor_type_rules);
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const char* tensor_type_rules,
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bool convert_name);
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SD_API bool preprocess_canny(sd_image_t image,
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float high_threshold,
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