upstream-archive/stable-diffusion.cpp
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refactor: unify the naming style of ggml extension functions (#921)

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leejet
2025-10-28 23:26:48 +08:00
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parent 77eb95f8e4
commit dd75fc081c
20 changed files with 600 additions and 601 deletions
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6
upscaler.cpp
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@@ -82,7 +82,7 @@ struct UpscalerGGML {
}
// LOG_DEBUG("upscale work buffer size: %.2f MB", params.mem_size / 1024.f / 1024.f);
ggml_tensor* input_image_tensor = ggml_new_tensor_4d(upscale_ctx, GGML_TYPE_F32, input_image.width, input_image.height, 3, 1);
sd_image_to_tensor(input_image, input_image_tensor);
sd_image_to_ggml_tensor(input_image, input_image_tensor);
ggml_tensor* upscaled = ggml_new_tensor_4d(upscale_ctx, GGML_TYPE_F32, output_width, output_height, 3, 1);
auto on_tiling = [&](ggml_tensor* in, ggml_tensor* out, bool init) {
@@ -91,8 +91,8 @@ struct UpscalerGGML {
int64_t t0 = ggml_time_ms();
sd_tiling(input_image_tensor, upscaled, esrgan_upscaler->scale, esrgan_upscaler->tile_size, 0.25f, on_tiling);
esrgan_upscaler->free_compute_buffer();
ggml_tensor_clamp(upscaled, 0.f, 1.f);
uint8_t* upscaled_data = sd_tensor_to_image(upscaled);
ggml_ext_tensor_clamp_inplace(upscaled, 0.f, 1.f);
uint8_t* upscaled_data = ggml_tensor_to_sd_image(upscaled);
ggml_free(upscale_ctx);
int64_t t3 = ggml_time_ms();
LOG_INFO("input_image_tensor upscaled, taking %.2fs", (t3 - t0) / 1000.0f);