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[Revision] Don't recommend using revision (#1764)

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Patrick von Platen 2022-12-19 16:25:41 +01:00 committed by GitHub
parent b267d28566
commit ce1c27adc8
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20 changed files with 45 additions and 84 deletions
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7
docs/source/api/pipelines/overview.mdx
View File

@ -139,9 +139,9 @@ from diffusers import StableDiffusionImg2ImgPipeline
# load the pipeline
device = "cuda"
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", revision="fp16", torch_dtype=torch.float16
).to(device)
pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to(
device
)
# let's download an initial image
url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"
@ -189,7 +189,6 @@ mask_image = download_image(mask_url).resize((512, 512))
pipe = StableDiffusionInpaintPipeline.from_pretrained(
"runwayml/stable-diffusion-inpainting",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")

2
docs/source/api/pipelines/stable_diffusion_2.mdx
View File

@ -113,7 +113,7 @@ import torch
# load model and scheduler
model_id = "stabilityai/stable-diffusion-x4-upscaler"
pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, revision="fp16", torch_dtype=torch.float16)
pipeline = StableDiffusionUpscalePipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipeline = pipeline.to("cuda")
# let's download an image

13
docs/source/optimization/fp16.mdx
View File

@ -79,7 +79,7 @@ To save more GPU memory and get even more speed, you can load and run the model
```Python
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")
@ -107,7 +107,7 @@ from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")
@ -134,7 +134,7 @@ from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")
@ -159,7 +159,7 @@ from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")
@ -179,7 +179,7 @@ from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")
@ -234,7 +234,6 @@ def generate_inputs():
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
).to("cuda")
unet = pipe.unet
@ -298,7 +297,6 @@ class UNet2DConditionOutput:
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
).to("cuda")
@ -349,7 +347,6 @@ import torch
pipe = StableDiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
).to("cuda")

7
docs/source/using-diffusers/custom_pipeline_examples.mdx
View File

@ -58,7 +58,6 @@ guided_pipeline = DiffusionPipeline.from_pretrained(
custom_pipeline="clip_guided_stable_diffusion",
clip_model=clip_model,
feature_extractor=feature_extractor,
revision="fp16",
torch_dtype=torch.float16,
)
guided_pipeline.enable_attention_slicing()
@ -113,7 +112,6 @@ import torch
pipe = DiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4",
revision="fp16",
torch_dtype=torch.float16,
safety_checker=None, # Very important for videos...lots of false positives while interpolating
custom_pipeline="interpolate_stable_diffusion",
@ -159,7 +157,6 @@ pipe = DiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4",
custom_pipeline="stable_diffusion_mega",
torch_dtype=torch.float16,
revision="fp16",
)
pipe.to("cuda")
pipe.enable_attention_slicing()
@ -204,7 +201,7 @@ from diffusers import DiffusionPipeline
import torch
pipe = DiffusionPipeline.from_pretrained(
"hakurei/waifu-diffusion", custom_pipeline="lpw_stable_diffusion", revision="fp16", torch_dtype=torch.float16
"hakurei/waifu-diffusion", custom_pipeline="lpw_stable_diffusion", torch_dtype=torch.float16
)
pipe = pipe.to("cuda")
@ -268,7 +265,7 @@ diffuser_pipeline = DiffusionPipeline.from_pretrained(
custom_pipeline="speech_to_image_diffusion",
speech_model=model,
speech_processor=processor,
revision="fp16",
torch_dtype=torch.float16,
)

6
docs/source/using-diffusers/img2img.mdx
View File

@ -24,9 +24,9 @@ from diffusers import StableDiffusionImg2ImgPipeline
# load the pipeline
device = "cuda"
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5", revision="fp16", torch_dtype=torch.float16
).to(device)
pipe = StableDiffusionImg2ImgPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16).to(
device
)
# let's download an initial image
url = "https://raw.githubusercontent.com/CompVis/stable-diffusion/main/assets/stable-samples/img2img/sketch-mountains-input.jpg"

1
docs/source/using-diffusers/inpaint.mdx
View File

@ -42,7 +42,6 @@ mask_image = download_image(mask_url).resize((512, 512))
pipe = StableDiffusionInpaintPipeline.from_pretrained(
"runwayml/stable-diffusion-inpainting",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")

12
examples/community/README.md
View File

@ -57,7 +57,7 @@ guided_pipeline = DiffusionPipeline.from_pretrained(
custom_pipeline="clip_guided_stable_diffusion",
clip_model=clip_model,
feature_extractor=feature_extractor,
revision="fp16",
torch_dtype=torch.float16,
)
guided_pipeline.enable_attention_slicing()
@ -208,7 +208,7 @@ import torch
pipe = DiffusionPipeline.from_pretrained(
'hakurei/waifu-diffusion',
custom_pipeline="lpw_stable_diffusion",
revision="fp16",
torch_dtype=torch.float16
)
pipe=pipe.to("cuda")
@ -275,7 +275,7 @@ diffuser_pipeline = DiffusionPipeline.from_pretrained(
custom_pipeline="speech_to_image_diffusion",
speech_model=model,
speech_processor=processor,
revision="fp16",
torch_dtype=torch.float16,
)
@ -333,7 +333,7 @@ import torch
pipe = DiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4",
custom_pipeline="wildcard_stable_diffusion",
revision="fp16",
torch_dtype=torch.float16,
)
prompt = "__animal__ sitting on a __object__ wearing a __clothing__"
@ -567,7 +567,7 @@ diffuser_pipeline = DiffusionPipeline.from_pretrained(
detection_pipeline=language_detection_pipeline,
translation_model=trans_model,
translation_tokenizer=trans_tokenizer,
revision="fp16",
torch_dtype=torch.float16,
)
@ -615,7 +615,7 @@ mask_image = PIL.Image.open(mask_path).convert("RGB").resize((512, 512))
pipe = DiffusionPipeline.from_pretrained(
"runwayml/stable-diffusion-inpainting",
custom_pipeline="img2img_inpainting",
revision="fp16",
torch_dtype=torch.float16
)
pipe = pipe.to("cuda")

2
examples/community/wildcard_stable_diffusion.py
View File

@ -68,7 +68,7 @@ class WildcardStableDiffusionPipeline(DiffusionPipeline):
Example Usage:
pipe = WildcardStableDiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4",
revision="fp16",
torch_dtype=torch.float16,
)
prompt = "__animal__ sitting on a __object__ wearing a __clothing__"

2
src/diffusers/pipelines/README.md
View File

@ -113,7 +113,6 @@ from diffusers import StableDiffusionImg2ImgPipeline
device = "cuda"
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
"runwayml/stable-diffusion-v1-5",
revision="fp16",
torch_dtype=torch.float16,
).to(device)
@ -161,7 +160,6 @@ mask_image = download_image(mask_url).resize((512, 512))
pipe = StableDiffusionInpaintPipeline.from_pretrained(
"runwayml/stable-diffusion-inpainting",
revision="fp16",
torch_dtype=torch.float16,
)
pipe = pipe.to("cuda")

4
tests/pipelines/altdiffusion/test_alt_diffusion.py
View File

@ -248,9 +248,7 @@ class AltDiffusionPipelineIntegrationTests(unittest.TestCase):
def test_alt_diffusion_text2img_pipeline_fp16(self):
torch.cuda.reset_peak_memory_stats()
model_id = "BAAI/AltDiffusion"
pipe = AltDiffusionPipeline.from_pretrained(
model_id, revision="fp16", torch_dtype=torch.float16, safety_checker=None
)
pipe = AltDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)

28
tests/pipelines/stable_diffusion/test_stable_diffusion.py
View File

@ -527,9 +527,7 @@ class StableDiffusionPipelineSlowTests(unittest.TestCase):
def test_stable_diffusion_attention_slicing(self):
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -555,9 +553,7 @@ class StableDiffusionPipelineSlowTests(unittest.TestCase):
def test_stable_diffusion_vae_slicing(self):
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
pipe.enable_attention_slicing()
@ -588,9 +584,7 @@ class StableDiffusionPipelineSlowTests(unittest.TestCase):
assert np.abs(image_sliced - image).max() < 4e-3
def test_stable_diffusion_fp16_vs_autocast(self):
pipe = StableDiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -629,9 +623,7 @@ class StableDiffusionPipelineSlowTests(unittest.TestCase):
callback_fn.has_been_called = False
pipe = StableDiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
pipe.enable_attention_slicing()
@ -645,16 +637,12 @@ class StableDiffusionPipelineSlowTests(unittest.TestCase):
pipeline_id = "CompVis/stable-diffusion-v1-4"
start_time = time.time()
pipeline_low_cpu_mem_usage = StableDiffusionPipeline.from_pretrained(
pipeline_id, revision="fp16", torch_dtype=torch.float16
)
pipeline_low_cpu_mem_usage = StableDiffusionPipeline.from_pretrained(pipeline_id, torch_dtype=torch.float16)
pipeline_low_cpu_mem_usage.to(torch_device)
low_cpu_mem_usage_time = time.time() - start_time
start_time = time.time()
_ = StableDiffusionPipeline.from_pretrained(
pipeline_id, revision="fp16", torch_dtype=torch.float16, low_cpu_mem_usage=False
)
_ = StableDiffusionPipeline.from_pretrained(pipeline_id, torch_dtype=torch.float16, low_cpu_mem_usage=False)
normal_load_time = time.time() - start_time
assert 2 * low_cpu_mem_usage_time < normal_load_time
@ -664,9 +652,7 @@ class StableDiffusionPipelineSlowTests(unittest.TestCase):
torch.cuda.reset_max_memory_allocated()
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4", revision="fp16", torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", torch_dtype=torch.float16)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
pipe.enable_attention_slicing(1)

4
tests/pipelines/stable_diffusion/test_stable_diffusion_img2img.py
View File

@ -303,7 +303,7 @@ class StableDiffusionImg2ImgPipelineSlowTests(unittest.TestCase):
callback_fn.has_been_called = False
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4", safety_checker=None, revision="fp16", torch_dtype=torch.float16
"CompVis/stable-diffusion-v1-4", safety_checker=None, torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -320,7 +320,7 @@ class StableDiffusionImg2ImgPipelineSlowTests(unittest.TestCase):
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
"CompVis/stable-diffusion-v1-4", safety_checker=None, revision="fp16", torch_dtype=torch.float16
"CompVis/stable-diffusion-v1-4", safety_checker=None, torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)

4
tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint.py
View File

@ -212,7 +212,7 @@ class StableDiffusionInpaintPipelineSlowTests(unittest.TestCase):
def test_stable_diffusion_inpaint_fp16(self):
pipe = StableDiffusionInpaintPipeline.from_pretrained(
"runwayml/stable-diffusion-inpainting", revision="fp16", torch_dtype=torch.float16, safety_checker=None
"runwayml/stable-diffusion-inpainting", torch_dtype=torch.float16, safety_checker=None
)
pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -266,7 +266,7 @@ class StableDiffusionInpaintPipelineSlowTests(unittest.TestCase):
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionInpaintPipeline.from_pretrained(
"runwayml/stable-diffusion-inpainting", safety_checker=None, revision="fp16", torch_dtype=torch.float16
"runwayml/stable-diffusion-inpainting", safety_checker=None, torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)

2
tests/pipelines/stable_diffusion/test_stable_diffusion_inpaint_legacy.py
View File

@ -425,7 +425,7 @@ class StableDiffusionInpaintLegacyPipelineSlowTests(unittest.TestCase):
callback_fn.has_been_called = False
pipe = StableDiffusionInpaintPipelineLegacy.from_pretrained(
"CompVis/stable-diffusion-v1-4", safety_checker=None, revision="fp16", torch_dtype=torch.float16
"CompVis/stable-diffusion-v1-4", safety_checker=None, torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)

6
tests/pipelines/stable_diffusion_2/test_stable_diffusion.py
View File

@ -304,7 +304,7 @@ class StableDiffusion2PipelineSlowTests(unittest.TestCase):
def test_stable_diffusion_attention_slicing(self):
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-base", revision="fp16", torch_dtype=torch.float16
"stabilityai/stable-diffusion-2-base", torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -352,7 +352,7 @@ class StableDiffusion2PipelineSlowTests(unittest.TestCase):
callback_fn.has_been_called = False
pipe = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-base", revision="fp16", torch_dtype=torch.float16
"stabilityai/stable-diffusion-2-base", torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -369,7 +369,7 @@ class StableDiffusion2PipelineSlowTests(unittest.TestCase):
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-base", revision="fp16", torch_dtype=torch.float16
"stabilityai/stable-diffusion-2-base", torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)

4
tests/pipelines/stable_diffusion_2/test_stable_diffusion_depth.py
View File

@ -484,7 +484,7 @@ class StableDiffusionDepth2ImgPipelineSlowTests(unittest.TestCase):
callback_fn.has_been_called = False
pipe = StableDiffusionDepth2ImgPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-depth", safety_checker=None, revision="fp16", torch_dtype=torch.float16
"stabilityai/stable-diffusion-2-depth", safety_checker=None, torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -501,7 +501,7 @@ class StableDiffusionDepth2ImgPipelineSlowTests(unittest.TestCase):
torch.cuda.reset_peak_memory_stats()
pipe = StableDiffusionDepth2ImgPipeline.from_pretrained(
"stabilityai/stable-diffusion-2-depth", safety_checker=None, revision="fp16", torch_dtype=torch.float16
"stabilityai/stable-diffusion-2-depth", safety_checker=None, torch_dtype=torch.float16
)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)

2
tests/pipelines/stable_diffusion_2/test_stable_diffusion_inpaint.py
View File

@ -188,7 +188,6 @@ class StableDiffusionInpaintPipelineIntegrationTests(unittest.TestCase):
model_id = "stabilityai/stable-diffusion-2-inpainting"
pipe = StableDiffusionInpaintPipeline.from_pretrained(
model_id,
revision="fp16",
torch_dtype=torch.float16,
safety_checker=None,
)
@ -231,7 +230,6 @@ class StableDiffusionInpaintPipelineIntegrationTests(unittest.TestCase):
safety_checker=None,
scheduler=pndm,
device_map="auto",
revision="fp16",
torch_dtype=torch.float16,
)
pipe.to(torch_device)

2
tests/pipelines/stable_diffusion_2/test_stable_diffusion_upscale.py
View File

@ -306,7 +306,6 @@ class StableDiffusionUpscalePipelineIntegrationTests(unittest.TestCase):
model_id = "stabilityai/stable-diffusion-x4-upscaler"
pipe = StableDiffusionUpscalePipeline.from_pretrained(
model_id,
revision="fp16",
torch_dtype=torch.float16,
)
pipe.to(torch_device)
@ -340,7 +339,6 @@ class StableDiffusionUpscalePipelineIntegrationTests(unittest.TestCase):
model_id = "stabilityai/stable-diffusion-x4-upscaler"
pipe = StableDiffusionUpscalePipeline.from_pretrained(
model_id,
revision="fp16",
torch_dtype=torch.float16,
)
pipe.to(torch_device)

20
tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py
View File

@ -329,7 +329,7 @@ class StableDiffusion2VPredictionPipelineIntegrationTests(unittest.TestCase):
def test_stable_diffusion_attention_slicing_v_pred(self):
torch.cuda.reset_peak_memory_stats()
model_id = "stabilityai/stable-diffusion-2"
pipe = StableDiffusionPipeline.from_pretrained(model_id, revision="fp16", torch_dtype=torch.float16)
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -389,9 +389,7 @@ class StableDiffusion2VPredictionPipelineIntegrationTests(unittest.TestCase):
"sd2-text2img/astronaut_riding_a_horse_v_pred_fp16.npy"
)
pipe = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-2", revision="fp16", torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2", torch_dtype=torch.float16)
pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
@ -430,9 +428,7 @@ class StableDiffusion2VPredictionPipelineIntegrationTests(unittest.TestCase):
test_callback_fn.has_been_called = False
pipe = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-2", revision="fp16", torch_dtype=torch.float16
)
pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2", torch_dtype=torch.float16)
pipe = pipe.to(torch_device)
pipe.set_progress_bar_config(disable=None)
pipe.enable_attention_slicing()
@ -456,16 +452,12 @@ class StableDiffusion2VPredictionPipelineIntegrationTests(unittest.TestCase):
pipeline_id = "stabilityai/stable-diffusion-2"
start_time = time.time()
pipeline_low_cpu_mem_usage = StableDiffusionPipeline.from_pretrained(
pipeline_id, revision="fp16", torch_dtype=torch.float16
)
pipeline_low_cpu_mem_usage = StableDiffusionPipeline.from_pretrained(pipeline_id, torch_dtype=torch.float16)
pipeline_low_cpu_mem_usage.to(torch_device)
low_cpu_mem_usage_time = time.time() - start_time
start_time = time.time()
_ = StableDiffusionPipeline.from_pretrained(
pipeline_id, revision="fp16", torch_dtype=torch.float16, low_cpu_mem_usage=False
)
_ = StableDiffusionPipeline.from_pretrained(pipeline_id, torch_dtype=torch.float16, low_cpu_mem_usage=False)
normal_load_time = time.time() - start_time
assert 2 * low_cpu_mem_usage_time < normal_load_time
@ -478,7 +470,7 @@ class StableDiffusion2VPredictionPipelineIntegrationTests(unittest.TestCase):
pipeline_id = "stabilityai/stable-diffusion-2"
prompt = "Andromeda galaxy in a bottle"
pipeline = StableDiffusionPipeline.from_pretrained(pipeline_id, revision="fp16", torch_dtype=torch.float16)
pipeline = StableDiffusionPipeline.from_pretrained(pipeline_id, torch_dtype=torch.float16)
pipeline = pipeline.to(torch_device)
pipeline.enable_attention_slicing(1)
pipeline.enable_sequential_cpu_offload()

1
tests/test_pipelines.py
View File

@ -286,7 +286,6 @@ class CustomPipelineTests(unittest.TestCase):
clip_model=clip_model,
feature_extractor=feature_extractor,
torch_dtype=torch.float16,
revision="fp16",
)
pipeline.enable_attention_slicing()
pipeline = pipeline.to(torch_device)