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Add configs

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This commit is contained in:
zhoushunjie
2022-12-05 09:32:49 +00:00
parent 50dd3c3e85
commit fdea6f1454
1 changed files with 24 additions and 14 deletions
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38
examples/multimodal/stable_diffusion/cpp/main.cc
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@@ -95,6 +95,13 @@ int main() {
bool use_trt_backend = true;
bool use_fp16 = true;
int batch_size = 1;
int num_images_per_prompt = 1;
int num_inference_steps = 50;
int height = 512;
int width = 512;
constexpr int unet_inpaint_channels = 9;
constexpr int latents_channels = 4;
// 1. Init scheduler
std::unique_ptr<fastdeploy::Scheduler> dpm(
@@ -130,9 +137,9 @@ int main() {
std::unordered_map<std::string, std::vector<std::vector<int>>>
vae_encoder_dynamic_shape = {
{"sample",
{/* min_shape */ {1, 3, 512, 512},
/* opt_shape */ {2 * batch_size, 3, 512, 512},
/* max_shape */ {2 * batch_size, 3, 512, 512}}}};
{/* min_shape */ {1, 3, height, width},
/* opt_shape */ {2 * batch_size, 3, height, width},
/* max_shape */ {2 * batch_size, 3, height, width}}}};
std::string vae_encoder_model_dir = model_dir + sep + "vae_encoder";
std::string vae_encoder_model_file =
vae_encoder_model_dir + sep + "inference.pdmodel";
@@ -146,9 +153,11 @@ int main() {
std::unordered_map<std::string, std::vector<std::vector<int>>>
vae_decoder_dynamic_shape = {
{"latent_sample",
{/* min_shape */ {1, 4, 64, 64},
/* opt_shape */ {2 * batch_size, 4, 64, 64},
/* max_shape */ {2 * batch_size, 4, 64, 64}}}};
{/* min_shape */ {1, latents_channels, height / 8, width / 8},
/* opt_shape */
{2 * batch_size, latents_channels, height / 8, width / 8},
/* max_shape */
{2 * batch_size, latents_channels, height / 8, width / 8}}}};
std::string vae_decoder_model_dir = model_dir + sep + "vae_decoder";
std::string vae_decoder_model_file =
vae_decoder_model_dir + sep + "inference.pdmodel";
@@ -159,13 +168,14 @@ int main() {
use_trt_backend, use_fp16, vae_decoder_dynamic_shape);
// 5. Init unet runtime
constexpr int unet_inpaint_channels = 9;
std::unordered_map<std::string, std::vector<std::vector<int>>>
unet_dynamic_shape = {
{"sample",
{/* min_shape */ {1, unet_inpaint_channels, 64, 64},
/* opt_shape */ {2 * batch_size, unet_inpaint_channels, 64, 64},
/* max_shape */ {2 * batch_size, unet_inpaint_channels, 64, 64}}},
{/* min_shape */ {1, unet_inpaint_channels, height / 8, width / 8},
/* opt_shape */
{2 * batch_size, unet_inpaint_channels, height / 8, width / 8},
/* max_shape */
{2 * batch_size, unet_inpaint_channels, height / 8, width / 8}}},
{"timesteps", {{1}, {1}, {1}}},
{"encoder_hidden_states",
{{1, max_length, 768},
@@ -201,12 +211,12 @@ int main() {
fastdeploy::TimeCounter tc;
tc.Start();
pipe.Predict(prompts, image, mask_image, &outputs,
/* height = */ 512,
/* width = */ 512,
/* num_inference_steps = */ 50,
/* height = */ height,
/* width = */ width,
/* num_inference_steps = */ num_inference_steps,
/* guidance_scale = */ 7.5,
/* negative_prompt = */ {},
/* num_images_per_prompt = */ 1,
/* num_images_per_prompt = */ num_images_per_prompt,
/* eta = */ 1.0,
/* max_length = */ max_length,
/* latents = */ nullptr,