chore: import upstream snapshot with attribution

doc/source/serve/doc_code/resnet50_example.py

@@ -0,0 +1,66 @@
+# __serve_example_begin__
+import requests
+from io import BytesIO
+
+from PIL import Image
+import starlette.requests
+import torch
+from torchvision import transforms
+import torchvision.models as models
+from torchvision.models import ResNet50_Weights
+
+from ray import serve
+
+
+@serve.deployment(
+    ray_actor_options={"num_cpus": 1},
+    num_replicas="auto",
+)
+class Model:
+    def __init__(self):
+        self.resnet50 = (
+            models.resnet50(weights=ResNet50_Weights.DEFAULT).eval().to("cpu")
+        )
+        self.preprocess = transforms.Compose(
+            [
+                transforms.Resize(256),
+                transforms.CenterCrop(224),
+                transforms.ToTensor(),
+                transforms.Normalize(
+                    mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
+                ),
+            ]
+        )
+        resp = requests.get(
+            "https://raw.githubusercontent.com/pytorch/hub/master/imagenet_classes.txt"
+        )
+        self.categories = resp.content.decode("utf-8").split("\n")
+
+    async def __call__(self, request: starlette.requests.Request) -> str:
+        uri = (await request.json())["uri"]
+        image_bytes = requests.get(uri).content
+        image = Image.open(BytesIO(image_bytes)).convert("RGB")
+
+        # Batch size is 1
+        input_tensor = torch.cat([self.preprocess(image).unsqueeze(0)]).to("cpu")
+        with torch.no_grad():
+            output = self.resnet50(input_tensor)
+            sm_output = torch.nn.functional.softmax(output[0], dim=0)
+        ind = torch.argmax(sm_output)
+        return self.categories[ind]
+
+
+app = Model.bind()
+# __serve_example_end__
+
+if __name__ == "__main__":
+    import requests  # noqa
+
+    serve.run(app)
+    resp = requests.post(
+        "http://localhost:8000/",
+        json={
+            "uri": "https://serve-resnet-benchmark-data.s3.us-west-1.amazonaws.com/000000000019.jpeg"  # noqa
+        },
+    )  # noqa
+    assert resp.text == "ox"