Add resnest model to the shark_inference examples list.

shark/examples/shark_inference/resnest.py

@@ -0,0 +1,35 @@
+import torch
+import torchvision.models as models
+from shark.shark_inference import SharkInference
+from shark.shark_importer import SharkImporter
+
+torch.hub.list("zhanghang1989/ResNeSt", force_reload=True)
+
+
+class ResnestModule(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.model = torch.hub.load("zhanghang1989/ResNeSt", "resnest50", pretrained=True)
+        self.model.eval()
+
+    def forward(self, input):
+        return self.model.forward(input)
+
+
+input = torch.randn(1, 3, 224, 224)
+
+
+mlir_importer = SharkImporter(
+    ResnestModule(),
+    (input),
+    frontend="torch",
+)
+
+(vision_mlir, func_name), inputs, golden_out = mlir_importer.import_debug(tracing_required=True)
+
+print(golden_out)
+
+shark_module = SharkInference(vision_mlir, func_name, device="cpu", mlir_dialect="linalg")
+shark_module.compile()
+result = shark_module.forward((input))
+print("Obtained result", result)