From ca68ab3eefe837562982a43f4478dd1cacc292aa Mon Sep 17 00:00:00 2001 From: Randolph-zeng Date: Thu, 8 Dec 2022 00:41:07 +0800 Subject: [PATCH] Update scheduling_repaint.py (#1582) * Update scheduling_repaint.py * update the expected image Co-authored-by: anton- --- src/diffusers/schedulers/scheduling_repaint.py | 2 +- tests/pipelines/repaint/test_repaint.py | 7 +++---- 2 files changed, 4 insertions(+), 5 deletions(-) diff --git a/src/diffusers/schedulers/scheduling_repaint.py b/src/diffusers/schedulers/scheduling_repaint.py index 0b80181f43..f41a41fd49 100644 --- a/src/diffusers/schedulers/scheduling_repaint.py +++ b/src/diffusers/schedulers/scheduling_repaint.py @@ -287,7 +287,7 @@ class RePaintScheduler(SchedulerMixin, ConfigMixin): prev_unknown_part = alpha_prod_t_prev**0.5 * pred_original_sample + pred_sample_direction + variance # 8. Algorithm 1 Line 5 https://arxiv.org/pdf/2201.09865.pdf - prev_known_part = (alpha_prod_t**0.5) * original_image + ((1 - alpha_prod_t) ** 0.5) * noise + prev_known_part = (alpha_prod_t_prev**0.5) * original_image + ((1 - alpha_prod_t_prev) ** 0.5) * noise # 9. Algorithm 1 Line 8 https://arxiv.org/pdf/2201.09865.pdf pred_prev_sample = mask * prev_known_part + (1.0 - mask) * prev_unknown_part diff --git a/tests/pipelines/repaint/test_repaint.py b/tests/pipelines/repaint/test_repaint.py index 3ab0efc875..d1ecd3c06e 100644 --- a/tests/pipelines/repaint/test_repaint.py +++ b/tests/pipelines/repaint/test_repaint.py @@ -19,7 +19,7 @@ import numpy as np import torch from diffusers import RePaintPipeline, RePaintScheduler, UNet2DModel -from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device +from diffusers.utils.testing_utils import load_image, load_numpy, require_torch_gpu, slow, torch_device torch.backends.cuda.matmul.allow_tf32 = False @@ -36,11 +36,10 @@ class RepaintPipelineIntegrationTests(unittest.TestCase): mask_image = load_image( "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/repaint/mask_256.png" ) - expected_image = load_image( + expected_image = load_numpy( "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/" - "repaint/celeba_hq_256_result.png" + "repaint/celeba_hq_256_result.npy" ) - expected_image = np.array(expected_image, dtype=np.float32) / 255.0 model_id = "google/ddpm-ema-celebahq-256" unet = UNet2DModel.from_pretrained(model_id)