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Qing
2023-12-28 10:48:52 +08:00
parent f0b852725f
commit 9cc9bd7a88
19 changed files with 345 additions and 482 deletions
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117
lama_cleaner/tests/test_sd_model.py
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@@ -1,5 +1,7 @@
import os
from lama_cleaner.tests.utils import check_device, get_config, assert_equal
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
from pathlib import Path
@@ -8,14 +10,13 @@ import torch
from lama_cleaner.model_manager import ModelManager
from lama_cleaner.schema import HDStrategy, SDSampler, FREEUConfig
from lama_cleaner.tests.test_model import get_config, assert_equal
current_dir = Path(__file__).parent.absolute().resolve()
save_dir = current_dir / "result"
save_dir.mkdir(exist_ok=True, parents=True)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("device", ["cuda", "mps"])
@pytest.mark.parametrize(
"sampler",
[
@@ -28,25 +29,24 @@ save_dir.mkdir(exist_ok=True, parents=True)
],
)
def test_runway_sd_1_5_all_samplers(
sd_device,
device,
sampler,
):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
sd_steps = check_device(device)
model = ModelManager(
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
device=torch.device(device),
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(
HDStrategy.ORIGINAL, prompt="a fox sitting on a bench", sd_steps=sd_steps
strategy=HDStrategy.ORIGINAL,
prompt="a fox sitting on a bench",
sd_steps=sd_steps,
)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}"
name = f"device_{device}_{sampler}"
assert_equal(
model,
@@ -57,22 +57,20 @@ def test_runway_sd_1_5_all_samplers(
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
@pytest.mark.parametrize("sampler", [SDSampler.lcm])
def test_runway_sd_lcm_lora(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
def test_runway_sd_lcm_lora(device, sampler):
check_device(device)
sd_steps = 5
model = ModelManager(
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
device=torch.device(device),
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(
strategy,
strategy=HDStrategy.ORIGINAL,
prompt="face of a fox, sitting on a bench",
sd_steps=sd_steps,
sd_guidance_scale=2,
@@ -83,28 +81,24 @@ def test_runway_sd_lcm_lora(sd_device, strategy, sampler):
assert_equal(
model,
cfg,
f"runway_sd_1_5_lcm_lora.png",
f"runway_sd_1_5_lcm_lora_device_{device}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
def test_runway_sd_freeu(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
def test_runway_sd_freeu(device, sampler):
sd_steps = check_device(device)
model = ModelManager(
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
device=torch.device(device),
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(
strategy,
strategy=HDStrategy.ORIGINAL,
prompt="face of a fox, sitting on a bench",
sd_steps=sd_steps,
sd_guidance_scale=7.5,
@@ -116,85 +110,83 @@ def test_runway_sd_freeu(sd_device, strategy, sampler):
assert_equal(
model,
cfg,
f"runway_sd_1_5_freeu.png",
f"runway_sd_1_5_freeu_device_{device}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("device", ["cuda", "mps"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
def test_runway_sd_sd_strength(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
def test_runway_sd_sd_strength(device, strategy, sampler):
sd_steps = check_device(device)
model = ModelManager(
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
device=torch.device(device),
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(
strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps, sd_strength=0.8
strategy=strategy,
prompt="a fox sitting on a bench",
sd_steps=sd_steps,
sd_strength=0.8,
)
cfg.sd_sampler = sampler
assert_equal(
model,
cfg,
f"runway_sd_strength_0.8.png",
f"runway_sd_strength_0.8_device_{device}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
def test_runway_norm_sd_model(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
def test_runway_norm_sd_model(device, strategy, sampler):
sd_steps = check_device(device)
model = ModelManager(
name="runwayml/stable-diffusion-v1-5",
device=torch.device(sd_device),
device=torch.device(device),
disable_nsfw=True,
sd_cpu_textencoder=False,
)
cfg = get_config(strategy, prompt="face of a fox, sitting on a bench", sd_steps=sd_steps)
cfg = get_config(
strategy=strategy, prompt="face of a fox, sitting on a bench", sd_steps=sd_steps
)
cfg.sd_sampler = sampler
assert_equal(
model,
cfg,
f"runway_{sd_device}_norm_sd_model.png",
f"runway_{device}_norm_sd_model_device_{device}.png",
img_p=current_dir / "overture-creations-5sI6fQgYIuo.png",
mask_p=current_dir / "overture-creations-5sI6fQgYIuo_mask.png",
)
@pytest.mark.parametrize("sd_device", ["cuda"])
@pytest.mark.parametrize("device", ["cuda"])
@pytest.mark.parametrize("strategy", [HDStrategy.ORIGINAL])
@pytest.mark.parametrize("sampler", [SDSampler.k_euler_a])
def test_runway_sd_1_5_cpu_offload(sd_device, strategy, sampler):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
def test_runway_sd_1_5_cpu_offload(device, strategy, sampler):
sd_steps = check_device(device)
model = ModelManager(
name="runwayml/stable-diffusion-inpainting",
device=torch.device(sd_device),
device=torch.device(device),
disable_nsfw=True,
sd_cpu_textencoder=False,
cpu_offload=True,
)
cfg = get_config(strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps)
cfg = get_config(
strategy=strategy, prompt="a fox sitting on a bench", sd_steps=sd_steps
)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}"
name = f"device_{device}_{sampler}"
assert_equal(
model,
@@ -205,7 +197,7 @@ def test_runway_sd_1_5_cpu_offload(sd_device, strategy, sampler):
)
@pytest.mark.parametrize("sd_device", ["cuda", "mps"])
@pytest.mark.parametrize("device", ["cuda", "mps", "cpu"])
@pytest.mark.parametrize("sampler", [SDSampler.ddim])
@pytest.mark.parametrize(
"name",
@@ -215,26 +207,23 @@ def test_runway_sd_1_5_cpu_offload(sd_device, strategy, sampler):
"v1-5-pruned-emaonly.safetensors",
],
)
def test_local_file_path(sd_device, sampler, name):
if sd_device == "cuda" and not torch.cuda.is_available():
return
sd_steps = 30
def test_local_file_path(device, sampler, name):
sd_steps = check_device(device)
model = ModelManager(
name=name,
device=torch.device(sd_device),
device=torch.device(device),
disable_nsfw=True,
sd_cpu_textencoder=False,
cpu_offload=False,
)
cfg = get_config(
HDStrategy.ORIGINAL,
strategy=HDStrategy.ORIGINAL,
prompt="a fox sitting on a bench",
sd_steps=sd_steps,
)
cfg.sd_sampler = sampler
name = f"device_{sd_device}_{sampler}_{name}"
name = f"device_{device}_{sampler}_{name}"
assert_equal(
model,