Align xpu models batch size with A100 (#2378)

Summary:
To align xpu batchsize for dynamobenchmark torchbench suite

Pull Request resolved: #2378

Reviewed By: aaronenyeshi

Differential Revision: D59961717

Pulled By: xuzhao9

fbshipit-source-id: c926d6d14d8b979284aa465738132c17425dafe9

torchbenchmark/util/model.py

@@ -31,7 +31,7 @@
 )
 from torchbenchmark.util.input import input_cast, ModelInputDescriptor
 
-SPECIAL_DEVICE_MAPPING = {"AMD Instinct MI210": "NVIDIA A100-SXM4-40GB"}
+SPECIAL_DEVICE_MAPPING = {"AMD Instinct MI210": "NVIDIA A100-SXM4-40GB", "Intel(R) Data Center GPU Max 1100": "NVIDIA A100-SXM4-40GB", "Intel(R) Data Center GPU Max 1550": "NVIDIA A100-SXM4-40GB"}
 
 
 class PostInitProcessor(type):
@@ -211,16 +211,24 @@ def _determine_dynamic_num_batches(
         return 1
 
     def _get_batch_size_from_metadata(self) -> Optional[str]:
-        if self.device != "cuda":
-            current_device_name = str(self.device)
-        else:
+        if self.device == "cuda":
             current_device_name = (
                 torch.cuda.get_device_name()
                 if torch.cuda.get_device_name()
                 else "UNKNOWN"
             )
             if current_device_name in SPECIAL_DEVICE_MAPPING:
                 current_device_name = SPECIAL_DEVICE_MAPPING[current_device_name]
+        elif self.device == "xpu":
+            current_device_name = (
+                torch.xpu.get_device_name()
+                if torch.xpu.get_device_name()
+                else "UNKNOWN"
+            )
+            if current_device_name in SPECIAL_DEVICE_MAPPING:
+                current_device_name = SPECIAL_DEVICE_MAPPING[current_device_name]
+        else:
+            current_device_name = str(self.device)
 
         # use the device suggestion on CUDA inference tests, key should be either eval_batch_size or train_batch_size
         device_batch_size_key = f"{self.test}_batch_size"