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Add CUDA tuned models for SD variants (#814)

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This commit is contained in:
yzhang93
2023-01-16 09:38:27 -08:00
committed by GitHub
parent 48137ced19
commit dd22c65855
3 changed files with 14 additions and 6 deletions
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9
shark/examples/shark_inference/stable_diffusion/resources/model_db.json
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@@ -5,8 +5,10 @@
"stablediffusion/tuned/cuda":"gs://shark_tank/sd_tuned/cuda",
"anythingv3/untuned":"gs://shark_tank/sd_anythingv3",
"anythingv3/tuned":"gs://shark_tank/sd_tuned",
"anythingv3/tuned/cuda":"gs://shark_tank/sd_tuned/cuda",
"analogdiffusion/untuned":"gs://shark_tank/sd_analog_diffusion",
"analogdiffusion/tuned":"gs://shark_tank/sd_tuned",
"analogdiffusion/tuned/cuda":"gs://shark_tank/sd_tuned/cuda",
"openjourney/untuned":"gs://shark_tank/sd_openjourney",
"openjourney/tuned":"gs://shark_tank/sd_tuned",
"dreamlike/untuned":"gs://shark_tank/sd_dreamlike_diffusion"
@@ -14,14 +16,17 @@
{
"stablediffusion/v1_4/unet/fp16/length_77/untuned":"unet_8dec_fp16",
"stablediffusion/v1_4/unet/fp16/length_77/tuned":"unet_8dec_fp16_tuned",
"stablediffusion/v1_4/unet/fp16/length_77/tuned/cuda":"unet_8dec_fp16_cuda_tuned",
"stablediffusion/v1_4/unet/fp32/length_77/untuned":"unet_1dec_fp32",
"stablediffusion/v1_4/vae/fp16/length_77/untuned":"vae_19dec_fp16",
"stablediffusion/v1_4/vae/fp16/length_77/tuned":"vae_19dec_fp16_tuned",
"stablediffusion/v1_4/vae/fp16/length_77/tuned/cuda":"vae_19dec_fp16_cuda_tuned",
"stablediffusion/v1_4/vae/fp16/length_77/untuned/base":"vae_8dec_fp16",
"stablediffusion/v1_4/vae/fp32/length_77/untuned":"vae_1dec_fp32",
"stablediffusion/v1_4/clip/fp32/length_77/untuned":"clip_18dec_fp32",
"stablediffusion/v2_1base/unet/fp16/length_77/untuned":"unet2base_8dec_fp16",
"stablediffusion/v2_1base/unet/fp16/length_77/tuned":"unet2base_8dec_fp16_tuned_v2",
"stablediffusion/v2_1base/unet/fp16/length_77/tuned/cuda":"unet2base_8dec_fp16_cuda_tuned",
"stablediffusion/v2_1base/unet/fp16/length_64/untuned":"unet_19dec_v2p1base_fp16_64",
"stablediffusion/v2_1base/unet/fp16/length_64/tuned":"unet_19dec_v2p1base_fp16_64_tuned",
"stablediffusion/v2_1base/unet/fp16/length_64/tuned/cuda":"unet_19dec_v2p1base_fp16_64_cuda_tuned",
@@ -39,18 +44,22 @@
"stablediffusion/v2_1/clip/fp32/length_77/untuned":"clip2_18dec_fp32",
"anythingv3/v2_1base/unet/fp16/length_77/untuned":"av3_unet_19dec_fp16",
"anythingv3/v2_1base/unet/fp16/length_77/tuned":"av3_unet_19dec_fp16_tuned",
"anythingv3/v2_1base/unet/fp16/length_77/tuned/cuda":"av3_unet_19dec_fp16_cuda_tuned",
"anythingv3/v2_1base/unet/fp32/length_77/untuned":"av3_unet_19dec_fp32",
"anythingv3/v2_1base/vae/fp16/length_77/untuned":"av3_vae_19dec_fp16",
"anythingv3/v2_1base/vae/fp16/length_77/tuned":"av3_vae_19dec_fp16_tuned",
"anythingv3/v2_1base/vae/fp16/length_77/tuned/cuda":"av3_vae_19dec_fp16_cuda_tuned",
"anythingv3/v2_1base/vae/fp16/length_77/untuned/base":"av3_vaebase_22dec_fp16",
"anythingv3/v2_1base/vae/fp32/length_77/untuned":"av3_vae_19dec_fp32",
"anythingv3/v2_1base/vae/fp32/length_77/untuned/base":"av3_vaebase_22dec_fp32",
"anythingv3/v2_1base/clip/fp32/length_77/untuned":"av3_clip_19dec_fp32",
"analogdiffusion/v2_1base/unet/fp16/length_77/untuned":"ad_unet_19dec_fp16",
"analogdiffusion/v2_1base/unet/fp16/length_77/tuned":"ad_unet_19dec_fp16_tuned",
"analogdiffusion/v2_1base/unet/fp16/length_77/tuned/cuda":"ad_unet_19dec_fp16_cuda_tuned",
"analogdiffusion/v2_1base/unet/fp32/length_77/untuned":"ad_unet_19dec_fp32",
"analogdiffusion/v2_1base/vae/fp16/length_77/untuned":"ad_vae_19dec_fp16",
"analogdiffusion/v2_1base/vae/fp16/length_77/tuned":"ad_vae_19dec_fp16_tuned",
"analogdiffusion/v2_1base/vae/fp16/length_77/tuned/cuda":"ad_vae_19dec_fp16_cuda_tuned",
"analogdiffusion/v2_1base/vae/fp16/length_77/untuned/base":"ad_vaebase_22dec_fp16",
"analogdiffusion/v2_1base/vae/fp32/length_77/untuned":"ad_vae_19dec_fp32",
"analogdiffusion/v2_1base/vae/fp32/length_77/untuned/base":"ad_vaebase_22dec_fp32",

8
shark/examples/shark_inference/stable_diffusion/sd_annotation.py
View File

@@ -44,10 +44,10 @@ if args.use_winograd:
download_public_file(full_gs_url, winograd_config_dir, True)
if args.annotation_model == "unet" or device == "cuda":
if (
args.variant in ["anythingv3", "analogdiffusion"]
or args.annotation_model == "vae"
):
if args.variant in ["anythingv3", "analogdiffusion"]:
args.max_length = 77
args.version = "v1_4"
if args.annotation_model == "vae":
args.max_length = 77
config_name = f"{args.annotation_model}_{args.version}_{args.precision}_len{args.max_length}_{device}.json"
full_gs_url = config_bucket + config_name

3
shark/examples/shark_inference/stable_diffusion/utils.py
View File

@@ -205,11 +205,10 @@ def set_init_device_flags():
# Use tuned model in the case of stablediffusion/fp16 and cuda device sm_80
if (
args.variant == "stablediffusion"
args.variant in ["stablediffusion", "anythingv3", "analogdiffusion"]
and args.precision == "fp16"
and "cuda" in args.device
and get_cuda_sm_cc() == "sm_80"
and args.version == "v2_1base"
):
args.use_tuned = True