update

Author: DN6

tests/modular_pipelines/stable_diffusion_xl/test_modular_pipeline_stable_diffusion_xl.py

@@ -14,7 +14,6 @@
 # limitations under the License.
 
 import random
-import tempfile
 import unittest
 from typing import Any, Dict
 
@@ -24,7 +23,6 @@
 
 from diffusers import (
     ClassifierFreeGuidance,
-    ModularPipeline,
     StableDiffusionXLAutoBlocks,
     StableDiffusionXLModularPipeline,
 )
@@ -381,27 +379,6 @@ def test_stable_diffusion_xl_euler(self):
     def test_inference_batch_single_identical(self):
         super().test_inference_batch_single_identical(expected_max_diff=3e-3)
 
-    def test_stable_diffusion_xl_save_from_pretrained(self):
-        pipes = []
-        sd_pipe = self.get_pipeline().to(torch_device)
-        pipes.append(sd_pipe)
-
-        with tempfile.TemporaryDirectory() as tmpdirname:
-            sd_pipe.save_pretrained(tmpdirname)
-            sd_pipe = ModularPipeline.from_pretrained(tmpdirname).to(torch_device)
-            sd_pipe.load_default_components(torch_dtype=torch.float32)
-            sd_pipe.to(torch_device)
-        pipes.append(sd_pipe)
-
-        image_slices = []
-        for pipe in pipes:
-            inputs = self.get_dummy_inputs(torch_device)
-            image = pipe(**inputs, output="images")
-
-            image_slices.append(image[0, -3:, -3:, -1].flatten())
-
-        assert np.abs(image_slices[0] - image_slices[1]).max() < 1e-3
-
 
 class SDXLImg2ImgModularPipelineFastTests(
     SDXLModularTests,

tests/modular_pipelines/test_modular_pipelines_common.py

@@ -345,7 +345,7 @@ def test_save_from_pretrained(self):
         with tempfile.TemporaryDirectory() as tmpdirname:
             base_pipe.save_pretrained(tmpdirname)
             pipe = ModularPipeline.from_pretrained(tmpdirname).to(torch_device)
-            pipe.load_default_components(torch_dtype=torch.float16)
+            pipe.load_default_components(torch_dtype=torch.float32)
             pipe.to(torch_device)
 
         pipes.append(pipe)