fix generator 2

tests/test_modeling_utils.py

@@ -22,6 +22,7 @@ import os
 from distutils.util import strtobool
 
 import torch
+import numpy as np
 
 from diffusers import GaussianDDPMScheduler, UNetModel
 from diffusers.pipeline_utils import DiffusionPipeline
@@ -35,7 +36,7 @@ torch_device = "cuda" if torch.cuda.is_available() else "cpu"
 def get_random_generator(seed):
     seed = 1234
     random.seed(seed)
-    os.environ[‘PYTHONHASHSEED’] = str(seed)
+    os.environ["PYTHONHASHSEED"] = str(seed)
     np.random.seed(seed)
     torch.manual_seed(seed)
     torch.cuda.manual_seed(seed)
@@ -176,6 +177,7 @@ class SamplerTesterMixin(unittest.TestCase):
 
         assert image.shape == (1, 3, 256, 256)
         image_slice = image[0, -1, -3:, -3:].cpu()
+        import ipdb; ipdb.set_trace()
         assert (image_slice - torch.tensor([[-0.0598, -0.0611, -0.0506], [-0.0726, 0.0220, 0.0103], [-0.0723, -0.1310, -0.2458]])).abs().sum() < 1e-3
 
     def test_sample_fast(self):
@@ -216,6 +218,7 @@ class SamplerTesterMixin(unittest.TestCase):
 
         assert image.shape == (1, 3, 256, 256)
         image_slice = image[0, -1, -3:, -3:].cpu()
+        import ipdb; ipdb.set_trace()
         assert (image_slice - torch.tensor([[0.1746, 0.5125, -0.7920], [-0.5734, -0.2910, -0.1984], [0.4090, -0.7740, -0.3941]])).abs().sum() < 1e-3