added test to test_pipelines_common

Author: SahilCarterr

examples/research_projects/geodiff/geodiff_molecule_conformation.ipynb

@@ -26,8 +26,7 @@
     "%load_ext autoreload\n",
     "%autoreload 2\n",
     "\n",
-    "import torch\n",
-    "from diffusers import StableDiffusionGLIGENTextImagePipeline, StableDiffusionGLIGENPipeline"
+    "from diffusers import StableDiffusionGLIGENPipeline"
    ]
   },
   {
@@ -36,16 +35,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import os\n",
+    "from transformers import CLIPTextModel, CLIPTokenizer\n",
+    "\n",
     "import diffusers\n",
     "from diffusers import (\n",
     "    AutoencoderKL,\n",
     "    DDPMScheduler,\n",
-    "    UNet2DConditionModel,\n",
-    "    UniPCMultistepScheduler,\n",
     "    EulerDiscreteScheduler,\n",
+    "    UNet2DConditionModel,\n",
     ")\n",
-    "from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer\n",
+    "\n",
+    "\n",
     "# pretrained_model_name_or_path = 'masterful/gligen-1-4-generation-text-box'\n",
     "\n",
     "pretrained_model_name_or_path = '/root/data/zhizhonghuang/checkpoints/models--masterful--gligen-1-4-generation-text-box/snapshots/d2820dc1e9ba6ca082051ce79cfd3eb468ae2c83'\n",
@@ -122,6 +122,7 @@
     "\n",
     "import numpy as np\n",
     "\n",
+    "\n",
     "boxes = np.array([x[1] for x in gen_boxes])\n",
     "boxes = boxes / 512\n",
     "boxes[:, 2] = boxes[:, 0] + boxes[:, 2]\n",

examples/research_projects/gligen/demo.ipynb

@@ -205,17 +205,6 @@ def test_flux_image_output_shape(self):
             output_height, output_width, _ = image.shape
             assert (output_height, output_width) == (expected_height, expected_width)
 
-    def test_sigmas(self):
-        pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
-        inputs = self.get_dummy_inputs(torch_device)
-
-        output_without_sigmas = pipe(**inputs).images[0]
-        inputs = self.get_dummy_inputs(torch_device)
-        inputs["sigmas"] = [0.25]
-        output_with_sigmas = pipe(**inputs).images[0]
-        max_diff = np.abs(output_without_sigmas - output_with_sigmas).max()
-        assert max_diff > 1e-4
-
 
 @slow
 @require_big_gpu_with_torch_cuda

tests/pipelines/flux/test_pipeline_flux.py

@@ -201,14 +201,3 @@ def test_flux_image_output_shape(self):
             image = pipe(**inputs).images[0]
             output_height, output_width, _ = image.shape
             assert (output_height, output_width) == (expected_height, expected_width)
-
-    def test_sigmas(self):
-        pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
-        inputs = self.get_dummy_inputs(torch_device)
-
-        output_without_sigmas = pipe(**inputs).images[0]
-        inputs = self.get_dummy_inputs(torch_device)
-        inputs["sigmas"] = [0.25]
-        output_with_sigmas = pipe(**inputs).images[0]
-        max_diff = np.abs(output_without_sigmas - output_with_sigmas).max()
-        assert max_diff > 1e-4

tests/pipelines/flux/test_pipeline_flux_control.py

@@ -166,14 +166,3 @@ def test_flux_image_output_shape(self):
             image = pipe(**inputs).images[0]
             output_height, output_width, _ = image.shape
             assert (output_height, output_width) == (expected_height, expected_width)
-
-    def test_sigmas(self):
-        pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
-        inputs = self.get_dummy_inputs(torch_device)
-
-        output_without_sigmas = pipe(**inputs).images[0]
-        inputs = self.get_dummy_inputs(torch_device)
-        inputs["sigmas"] = [0.25]
-        output_with_sigmas = pipe(**inputs).images[0]
-        max_diff = np.abs(output_without_sigmas - output_with_sigmas).max()
-        assert max_diff > 1e-4

tests/pipelines/flux/test_pipeline_flux_control_img2img.py

@@ -166,14 +166,3 @@ def test_flux_image_output_shape(self):
 
     def test_inference_batch_single_identical(self):
         self._test_inference_batch_single_identical(expected_max_diff=1e-3)
-
-    def test_sigmas(self):
-        pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
-        inputs = self.get_dummy_inputs(torch_device)
-
-        output_without_sigmas = pipe(**inputs).images[0]
-        inputs = self.get_dummy_inputs(torch_device)
-        inputs["sigmas"] = [0.25]
-        output_with_sigmas = pipe(**inputs).images[0]
-        max_diff = np.abs(output_without_sigmas - output_with_sigmas).max()
-        assert max_diff > 1e-4

tests/pipelines/flux/test_pipeline_flux_fill.py

@@ -161,14 +161,3 @@ def test_flux_image_output_shape(self):
             image = pipe(**inputs).images[0]
             output_height, output_width, _ = image.shape
             assert (output_height, output_width) == (expected_height, expected_width)
-
-    def test_sigmas(self):
-        pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
-        inputs = self.get_dummy_inputs(torch_device)
-
-        output_without_sigmas = pipe(**inputs).images[0]
-        inputs = self.get_dummy_inputs(torch_device)
-        inputs["sigmas"] = [0.25]
-        output_with_sigmas = pipe(**inputs).images[0]
-        max_diff = np.abs(output_without_sigmas - output_with_sigmas).max()
-        assert max_diff > 1e-4

tests/pipelines/flux/test_pipeline_flux_img2img.py

@@ -163,14 +163,3 @@ def test_flux_image_output_shape(self):
             image = pipe(**inputs).images[0]
             output_height, output_width, _ = image.shape
             assert (output_height, output_width) == (expected_height, expected_width)
-
-    def test_sigmas(self):
-        pipe = self.pipeline_class(**self.get_dummy_components()).to(torch_device)
-        inputs = self.get_dummy_inputs(torch_device)
-
-        output_without_sigmas = pipe(**inputs).images[0]
-        inputs = self.get_dummy_inputs(torch_device)
-        inputs["sigmas"] = [0.25]
-        output_with_sigmas = pipe(**inputs).images[0]
-        max_diff = np.abs(output_without_sigmas - output_with_sigmas).max()
-        assert max_diff > 1e-4

tests/pipelines/flux/test_pipeline_flux_inpaint.py

@@ -1718,6 +1718,27 @@ def test_cfg(self):
 
         assert out_cfg.shape == out_no_cfg.shape
 
+    def test_sigmas(self):
+        sig = inspect.signature(self.pipeline_class.__call__)
+
+        if "sigmas" not in sig.parameters:
+            return
+
+        components = self.get_dummy_components()
+        pipe = self.pipeline_class(**components)
+        pipe = pipe.to(torch_device)
+        pipe.set_progress_bar_config(disable=None)
+
+        inputs = self.get_dummy_inputs(torch_device)
+
+        output_without_sigmas = pipe(**inputs).images[0]
+
+        inputs = self.get_dummy_inputs(torch_device)
+        inputs["sigmas"] = [0.25]
+        output_with_sigmas = pipe(**inputs).images[0]
+        max_diff = np.abs(output_without_sigmas - output_with_sigmas).max()
+        assert max_diff > 1e-4
+
     def test_callback_inputs(self):
         sig = inspect.signature(self.pipeline_class.__call__)
         has_callback_tensor_inputs = "callback_on_step_end_tensor_inputs" in sig.parameters