rename schedulers

README.md

@@ -35,7 +35,7 @@ Both models and schedulers should be load- and saveable from the Hub.
 
 ```python
 import torch
-from diffusers import UNetModel, GaussianDDPMScheduler
+from diffusers import UNetModel, DDPMScheduler
 import PIL
 import numpy as np
 import tqdm
@@ -44,7 +44,7 @@ generator = torch.manual_seed(0)
 torch_device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # 1. Load models
-noise_scheduler = GaussianDDPMScheduler.from_config("fusing/ddpm-lsun-church", tensor_format="pt")
+noise_scheduler = DDPMScheduler.from_config("fusing/ddpm-lsun-church", tensor_format="pt")
 unet = UNetModel.from_pretrained("fusing/ddpm-lsun-church").to(torch_device)
 
 # 2. Sample gaussian noise

src/diffusers/__init__.py

@@ -10,8 +10,10 @@ from .models.unet_glide import GLIDESuperResUNetModel, GLIDETextToImageUNetModel
 from .models.unet_ldm import UNetLDMModel
 from .pipeline_utils import DiffusionPipeline
 from .pipelines import DDIM, DDPM, GLIDE, LatentDiffusion
+
 from .schedulers import SchedulerMixin
+from .schedulers.scheduling_ddim import DDIMScheduler
+from .schedulers.scheduling_ddpm import DDPMScheduler
+
 from .schedulers.classifier_free_guidance import ClassifierFreeGuidanceScheduler
-from .schedulers.ddim import DDIMScheduler
-from .schedulers.gaussian_ddpm import GaussianDDPMScheduler
 from .schedulers.glide_ddim import GlideDDIMScheduler

src/diffusers/pipelines/old/ddim/run_ddpm.py

 #!/usr/bin/env python3
 import torch
 
-from diffusers import GaussianDDPMScheduler, UNetModel
+from diffusers import DDPMScheduler, UNetModel
 
 
 model = UNetModel(dim=64, dim_mults=(1, 2, 4, 8))
 
-diffusion = GaussianDDPMScheduler(model, image_size=128, timesteps=1000, loss_type="l1")  # number of steps  # L1 or L2
+diffusion = DDPMScheduler(model, image_size=128, timesteps=1000, loss_type="l1")  # number of steps  # L1 or L2
 
 training_images = torch.randn(8, 3, 128, 128)  # your images need to be normalized from a range of -1 to +1
 loss = diffusion(training_images)

src/diffusers/pipelines/old/ddpm/run_ddpm.py

 #!/usr/bin/env python3
 import torch
 
-from diffusers import GaussianDDPMScheduler, UNetModel
+from diffusers import DDPMScheduler, UNetModel
 
 
 model = UNetModel(dim=64, dim_mults=(1, 2, 4, 8))
 
-diffusion = GaussianDDPMScheduler(model, image_size=128, timesteps=1000, loss_type="l1")  # number of steps  # L1 or L2
+diffusion = DDPMScheduler(model, image_size=128, timesteps=1000, loss_type="l1")  # number of steps  # L1 or L2
 
 training_images = torch.randn(8, 3, 128, 128)  # your images need to be normalized from a range of -1 to +1
 loss = diffusion(training_images)

src/diffusers/schedulers/__init__.py

@@ -16,8 +16,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from .scheduling_ddim import DDIMScheduler
+from .scheduling_ddpm import DDPMScheduler
+from .schedulers_utils import SchedulerMixin
+
 from .classifier_free_guidance import ClassifierFreeGuidanceScheduler
-from .ddim import DDIMScheduler
-from .gaussian_ddpm import GaussianDDPMScheduler
 from .glide_ddim import GlideDDIMScheduler
-from .schedulers_utils import SchedulerMixin

src/diffusers/schedulers/gaussian_ddpm.py → src/diffusers/schedulers/scheduling_ddpm.py

@@ -19,7 +19,7 @@ from ..configuration_utils import ConfigMixin
 from .schedulers_utils import SchedulerMixin, betas_for_alpha_bar, linear_beta_schedule
 
 
-class GaussianDDPMScheduler(SchedulerMixin, ConfigMixin):
+class DDPMScheduler(SchedulerMixin, ConfigMixin):
     def __init__(
         self,
         timesteps=1000,

tests/test_modeling_utils.py

@@ -19,7 +19,7 @@ import unittest
 
 import torch
 
-from diffusers import DDIM, DDPM, DDIMScheduler, GaussianDDPMScheduler, LatentDiffusion, UNetModel
+from diffusers import DDIM, DDPM, DDIMScheduler, DDPMScheduler, LatentDiffusion, UNetModel
 from diffusers.configuration_utils import ConfigMixin
 from diffusers.pipeline_utils import DiffusionPipeline
 from diffusers.testing_utils import floats_tensor, slow, torch_device
@@ -107,7 +107,7 @@ class PipelineTesterMixin(unittest.TestCase):
     def test_from_pretrained_save_pretrained(self):
         # 1. Load models
         model = UNetModel(ch=32, ch_mult=(1, 2), num_res_blocks=2, attn_resolutions=(16,), resolution=32)
-        schedular = GaussianDDPMScheduler(timesteps=10)
+        schedular = DDPMScheduler(timesteps=10)
 
         ddpm = DDPM(model, schedular)
 
@@ -147,7 +147,7 @@ class PipelineTesterMixin(unittest.TestCase):
         model_id = "fusing/ddpm-cifar10"
 
         unet = UNetModel.from_pretrained(model_id)
-        noise_scheduler = GaussianDDPMScheduler.from_config(model_id)
+        noise_scheduler = DDPMScheduler.from_config(model_id)
         noise_scheduler = noise_scheduler.set_format("pt")
 
         ddpm = DDPM(unet=unet, noise_scheduler=noise_scheduler)

tests/test_scheduler.py

@@ -20,7 +20,7 @@ import unittest
 import numpy as np
 import torch
 
-from diffusers import DDIMScheduler, GaussianDDPMScheduler
+from diffusers import DDIMScheduler, DDPMScheduler
 
 
 torch.backends.cuda.matmul.allow_tf32 = False
@@ -163,7 +163,7 @@ class SchedulerCommonTest(unittest.TestCase):
 
 
 class DDPMSchedulerTest(SchedulerCommonTest):
-    scheduler_classes = (GaussianDDPMScheduler,)
+    scheduler_classes = (DDPMScheduler,)
 
     def get_scheduler_config(self, **kwargs):
         config = {