change ascend to npu (#47641)

paddle/fluid/inference/api/analysis_config.cc

@@ -160,14 +160,17 @@ void AnalysisConfig::SetXpuDeviceId(int device_id) {
 }
 
 void AnalysisConfig::EnableNpu(int device_id) {
-#ifdef PADDLE_WITH_ASCEND_CL
+#if defined(PADDLE_WITH_ASCEND_CL)
   use_npu_ = true;
   npu_device_id_ = device_id;
+#elif defined(PADDLE_WITH_CUSTOM_DEVICE)
+  use_custom_device_ = true;
+  custom_device_id_ = device_id;
+  custom_device_type_ = "npu";
 #else
   LOG(ERROR) << "Please compile with npu to EnableNpu()";
   use_npu_ = false;
 #endif
-
   Update();
 }
 

python/paddle/device/__init__.py

@@ -195,7 +195,13 @@ def get_cudnn_version():
 
 def _convert_to_place(device):
     lower_device = device.lower()
-    if lower_device == 'cpu':
+    if device in core.get_all_custom_device_type():
+        selected_devices = os.getenv(
+            "FLAGS_selected_{}s".format(device), "0"
+        ).split(",")
+        device_id = int(selected_devices[0])
+        place = core.CustomPlace(device, device_id)
+    elif lower_device == 'cpu':
         place = core.CPUPlace()
     elif lower_device == 'gpu':
         if not core.is_compiled_with_cuda():
@@ -238,12 +244,6 @@ def _convert_to_place(device):
         selected_mlus = os.getenv("FLAGS_selected_mlus", "0").split(",")
         device_id = int(selected_mlus[0])
         place = core.MLUPlace(device_id)
-    elif device in core.get_all_custom_device_type():
-        selected_devices = os.getenv(
-            "FLAGS_selected_{}s".format(device), "0"
-        ).split(",")
-        device_id = int(selected_devices[0])
-        place = core.CustomPlace(device, device_id)
     else:
         avaliable_gpu_device = re.match(r'gpu:\d+', lower_device)
         avaliable_xpu_device = re.match(r'xpu:\d+', lower_device)