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[Tests] Fix some slow tests (#3989)

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fix some slow tests
This commit is contained in:
Patrick von Platen
2023-07-07 15:17:57 +02:00
committed by GitHub
parent d1d0b8afce
commit 6fde5a6dd6
4 changed files with 16 additions and 5 deletions
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2
src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl.py
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@@ -183,7 +183,7 @@ class StableDiffusionXLPipeline(DiffusionPipeline, FromSingleFileMixin):
self.to("cpu", silence_dtype_warnings=True)
torch.cuda.empty_cache() # otherwise we don't see the memory savings (but they probably exist)
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.text_encoder_2, self.vae]:
cpu_offload(cpu_offloaded_model, device)
def enable_model_cpu_offload(self, gpu_id=0):

2
src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_img2img.py
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@@ -191,7 +191,7 @@ class StableDiffusionXLImg2ImgPipeline(DiffusionPipeline, FromSingleFileMixin):
self.to("cpu", silence_dtype_warnings=True)
torch.cuda.empty_cache() # otherwise we don't see the memory savings (but they probably exist)
for cpu_offloaded_model in [self.unet, self.text_encoder, self.vae]:
for cpu_offloaded_model in [self.unet, self.text_encoder, self.text_encoder_2, self.vae]:
cpu_offload(cpu_offloaded_model, device)
def enable_model_cpu_offload(self, gpu_id=0):

8
tests/pipelines/test_pipelines_common.py
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@@ -699,12 +699,16 @@ class PipelineTesterMixin:
inputs = self.get_dummy_inputs(torch_device)
output_without_offload = pipe(**inputs)[0]
output_without_offload.cpu() if torch.is_tensor(output_without_offload) else output_without_offload
output_without_offload = (
output_without_offload.cpu() if torch.is_tensor(output_without_offload) else output_without_offload
)
pipe.enable_xformers_memory_efficient_attention()
inputs = self.get_dummy_inputs(torch_device)
output_with_offload = pipe(**inputs)[0]
output_with_offload.cpu() if torch.is_tensor(output_with_offload) else output_without_offload
output_with_offload = (
output_with_offload.cpu() if torch.is_tensor(output_with_offload) else output_without_offload
)
if test_max_difference:
max_diff = np.abs(output_with_offload - output_without_offload).max()

9
tests/pipelines/text_to_video/test_text_to_video.py
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@@ -26,7 +26,7 @@ from diffusers import (
TextToVideoSDPipeline,
UNet3DConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, slow
from diffusers.utils import is_xformers_available, load_numpy, skip_mps, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from ..pipeline_params import TEXT_TO_IMAGE_BATCH_PARAMS, TEXT_TO_IMAGE_PARAMS
@@ -143,6 +143,13 @@ class TextToVideoSDPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
def test_attention_slicing_forward_pass(self):
self._test_attention_slicing_forward_pass(test_mean_pixel_difference=False, expected_max_diff=3e-3)
@unittest.skipIf(
torch_device != "cuda" or not is_xformers_available(),
reason="XFormers attention is only available with CUDA and `xformers` installed",
)
def test_xformers_attention_forwardGenerator_pass(self):
self._test_xformers_attention_forwardGenerator_pass(test_mean_pixel_difference=False, expected_max_diff=1e-2)
# (todo): sayakpaul
@unittest.skip(reason="Batching needs to be properly figured out first for this pipeline.")
def test_inference_batch_consistent(self):