pix2pix tests no write to fs (#2497)

* attend and excite batch test causing timeouts

* pix2pix tests, no write to fs

src/diffusers/utils/testing_utils.py

@@ -209,6 +209,13 @@ def load_numpy(arry: Union[str, np.ndarray], local_path: Optional[str] = None) -
     return arry
 
 
+def load_pt(url: str):
+    response = requests.get(url)
+    response.raise_for_status()
+    arry = torch.load(BytesIO(response.content))
+    return arry
+
+
 def load_image(image: Union[str, PIL.Image.Image]) -> PIL.Image.Image:
     """
     Args:

tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py

@@ -17,9 +17,7 @@ import gc
 import unittest
 
 import numpy as np
-import requests
 import torch
-from PIL import Image
 from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
 
 from diffusers import (
@@ -33,7 +31,7 @@ from diffusers import (
     UNet2DConditionModel,
 )
 from diffusers.utils import load_numpy, slow, torch_device
-from diffusers.utils.testing_utils import require_torch_gpu, skip_mps
+from diffusers.utils.testing_utils import load_image, load_pt, require_torch_gpu, skip_mps
 
 from ...test_pipelines_common import PipelineTesterMixin
 
@@ -41,16 +39,20 @@ from ...test_pipelines_common import PipelineTesterMixin
 torch.backends.cuda.matmul.allow_tf32 = False
 
 
-def download_from_url(embedding_url, local_filepath):
-    r = requests.get(embedding_url)
-    with open(local_filepath, "wb") as f:
-        f.write(r.content)
-
-
 @skip_mps
 class StableDiffusionPix2PixZeroPipelineFastTests(PipelineTesterMixin, unittest.TestCase):
     pipeline_class = StableDiffusionPix2PixZeroPipeline
 
+    @classmethod
+    def setUpClass(cls):
+        cls.source_embeds = load_pt(
+            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/src_emb_0.pt"
+        )
+
+        cls.target_embeds = load_pt(
+            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/tgt_emb_0.pt"
+        )
+
     def get_dummy_components(self):
         torch.manual_seed(0)
         unet = UNet2DConditionModel(
@@ -103,15 +105,6 @@ class StableDiffusionPix2PixZeroPipelineFastTests(PipelineTesterMixin, unittest.
         return components
 
     def get_dummy_inputs(self, device, seed=0):
-        src_emb_url = "https://hf.co/datasets/sayakpaul/sample-datasets/resolve/main/src_emb_0.pt"
-        tgt_emb_url = "https://hf.co/datasets/sayakpaul/sample-datasets/resolve/main/tgt_emb_0.pt"
-
-        for url in [src_emb_url, tgt_emb_url]:
-            download_from_url(url, url.split("/")[-1])
-
-        src_embeds = torch.load(src_emb_url.split("/")[-1])
-        target_embeds = torch.load(tgt_emb_url.split("/")[-1])
-
         generator = torch.manual_seed(seed)
 
         inputs = {
@@ -120,8 +113,8 @@ class StableDiffusionPix2PixZeroPipelineFastTests(PipelineTesterMixin, unittest.
             "num_inference_steps": 2,
             "guidance_scale": 6.0,
             "cross_attention_guidance_amount": 0.15,
-            "source_embeds": src_embeds,
-            "target_embeds": target_embeds,
+            "source_embeds": self.source_embeds,
+            "target_embeds": self.target_embeds,
             "output_type": "numpy",
         }
         return inputs
@@ -237,17 +230,18 @@ class StableDiffusionPix2PixZeroPipelineSlowTests(unittest.TestCase):
         gc.collect()
         torch.cuda.empty_cache()
 
-    def get_inputs(self, seed=0):
-        generator = torch.manual_seed(seed)
-
-        src_emb_url = "https://hf.co/datasets/sayakpaul/sample-datasets/resolve/main/cat.pt"
-        tgt_emb_url = "https://hf.co/datasets/sayakpaul/sample-datasets/resolve/main/dog.pt"
+    @classmethod
+    def setUpClass(cls):
+        cls.source_embeds = load_pt(
+            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/cat.pt"
+        )
 
-        for url in [src_emb_url, tgt_emb_url]:
-            download_from_url(url, url.split("/")[-1])
+        cls.target_embeds = load_pt(
+            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/dog.pt"
+        )
 
-        src_embeds = torch.load(src_emb_url.split("/")[-1])
-        target_embeds = torch.load(tgt_emb_url.split("/")[-1])
+    def get_inputs(self, seed=0):
+        generator = torch.manual_seed(seed)
 
         inputs = {
             "prompt": "turn him into a cyborg",
@@ -255,8 +249,8 @@ class StableDiffusionPix2PixZeroPipelineSlowTests(unittest.TestCase):
             "num_inference_steps": 3,
             "guidance_scale": 7.5,
             "cross_attention_guidance_amount": 0.15,
-            "source_embeds": src_embeds,
-            "target_embeds": target_embeds,
+            "source_embeds": self.source_embeds,
+            "target_embeds": self.target_embeds,
             "output_type": "numpy",
         }
         return inputs
@@ -364,10 +358,17 @@ class InversionPipelineSlowTests(unittest.TestCase):
         gc.collect()
         torch.cuda.empty_cache()
 
-    def test_stable_diffusion_pix2pix_inversion(self):
-        img_url = "https://github.com/pix2pixzero/pix2pix-zero/raw/main/assets/test_images/cats/cat_6.png"
-        raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB").resize((512, 512))
+    @classmethod
+    def setUpClass(cls):
+        raw_image = load_image(
+            "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/cat_6.png"
+        )
+
+        raw_image = raw_image.convert("RGB").resize((512, 512))
+
+        cls.raw_image = raw_image
 
+    def test_stable_diffusion_pix2pix_inversion(self):
         pipe = StableDiffusionPix2PixZeroPipeline.from_pretrained(
             "CompVis/stable-diffusion-v1-4", safety_checker=None, torch_dtype=torch.float16
         )
@@ -380,7 +381,7 @@ class InversionPipelineSlowTests(unittest.TestCase):
         pipe.set_progress_bar_config(disable=None)
 
         generator = torch.manual_seed(0)
-        output = pipe.invert(caption, image=raw_image, generator=generator, num_inference_steps=10)
+        output = pipe.invert(caption, image=self.raw_image, generator=generator, num_inference_steps=10)
         inv_latents = output[0]
 
         image_slice = inv_latents[0, -3:, -3:, -1].flatten()
@@ -391,9 +392,6 @@ class InversionPipelineSlowTests(unittest.TestCase):
         assert np.abs(expected_slice - image_slice.cpu().numpy()).max() < 1e-3
 
     def test_stable_diffusion_pix2pix_full(self):
-        img_url = "https://github.com/pix2pixzero/pix2pix-zero/raw/main/assets/test_images/cats/cat_6.png"
-        raw_image = Image.open(requests.get(img_url, stream=True).raw).convert("RGB").resize((512, 512))
-
         # numpy array of https://huggingface.co/datasets/hf-internal-testing/diffusers-images/blob/main/pix2pix/dog.png
         expected_image = load_numpy(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/dog.npy"
@@ -411,7 +409,7 @@ class InversionPipelineSlowTests(unittest.TestCase):
         pipe.set_progress_bar_config(disable=None)
 
         generator = torch.manual_seed(0)
-        output = pipe.invert(caption, image=raw_image, generator=generator)
+        output = pipe.invert(caption, image=self.raw_image, generator=generator)
         inv_latents = output[0]
 
         source_prompts = 4 * ["a cat sitting on the street", "a cat playing in the field", "a face of a cat"]