support static graph for kunlun

configs/deeplabv3p_xception65_optic_kunlun.yaml

@@ -0,0 +1,34 @@
+# 数据集配置
+DATASET:
+    DATA_DIR: "./dataset/optic_disc_seg/"
+    NUM_CLASSES: 2
+    TEST_FILE_LIST: "./dataset/optic_disc_seg/test_list.txt"
+    TRAIN_FILE_LIST: "./dataset/optic_disc_seg/train_list.txt"
+    VAL_FILE_LIST: "./dataset/optic_disc_seg/val_list.txt"
+    VIS_FILE_LIST: "./dataset/optic_disc_seg/test_list.txt"
+
+# 预训练模型配置
+MODEL:
+    MODEL_NAME: "deeplabv3p"
+    DEFAULT_NORM_TYPE: "bn"
+    DEEPLAB:
+        BACKBONE: "xception_65"
+
+# 其他配置
+TRAIN_CROP_SIZE: (512, 512)
+EVAL_CROP_SIZE: (512, 512)
+AUG:
+    AUG_METHOD: "unpadding"
+    FIX_RESIZE_SIZE: (512, 512)
+BATCH_SIZE: 2
+TRAIN:
+    PRETRAINED_MODEL_DIR: "./pretrained_model/deeplabv3p_xception65_bn_coco/"
+    MODEL_SAVE_DIR: "./saved_model/deeplabv3p_xception65_bn_optic/"
+    SNAPSHOT_EPOCH: 2
+TEST:
+    TEST_MODEL: "./saved_model/deeplabv3p_xception65_bn_optic/final"
+SOLVER:
+    NUM_EPOCHS: 20
+    LR: 0.001
+    LR_POLICY: "poly"
+    OPTIMIZER: "adam"

legacy/pdseg/eval.py

@@ -48,7 +48,13 @@ def parse_args():
     parser.add_argument(
         '--use_gpu',
         dest='use_gpu',
-        help='Use gpu or cpu',
+        help='Use xpu, gpu or cpu',
+        action='store_true',
+        default=False)
+    parser.add_argument(
+        '--use_xpu',
+        dest='use_xpu',
+        help='Use xpu, gpu or cpu',
         action='store_true',
         default=False)
     parser.add_argument(
@@ -68,7 +74,7 @@ def parse_args():
     return parser.parse_args()
 
 
-def evaluate(cfg, ckpt_dir=None, use_gpu=False, use_mpio=False, **kwargs):
+def evaluate(cfg, ckpt_dir=None, use_gpu=False, use_xpu=False, use_mpio=False, **kwargs):
     np.set_printoptions(precision=5, suppress=True)
 
     startup_prog = fluid.Program()
@@ -97,7 +103,13 @@ def data_generator():
         data_generator, drop_last=False, batch_size=cfg.BATCH_SIZE)
 
     # Get device environment
-    places = fluid.cuda_places() if use_gpu else fluid.cpu_places()
+    if use_gpu:
+        places = fluid.cuda_places()
+    elif use_xpu:
+        xpu_id = int(os.environ.get('FLAGS_selected_xpus', 0))
+        places = [fluid.XPUPlace(xpu_id)]
+    else:
+        fluid.cpu_places()
     place = places[0]
     dev_count = len(places)
     print("#Device count: {}".format(dev_count))

legacy/pdseg/train.py

@@ -56,7 +56,13 @@ def parse_args():
     parser.add_argument(
         '--use_gpu',
         dest='use_gpu',
-        help='Use gpu or cpu',
+        help='Use gpu, xpu or cpu',
+        action='store_true',
+        default=False)
+    parser.add_argument(
+        '--use_xpu',
+        dest='use_xpu',
+        help='Use xpu, gpu or cpu',
         action='store_true',
         default=False)
     parser.add_argument(
@@ -219,8 +225,16 @@ def data_generator():
 
     # Get device environment
     gpu_id = int(os.environ.get('FLAGS_selected_gpus', 0))
-    place = fluid.CUDAPlace(gpu_id) if args.use_gpu else fluid.CPUPlace()
-    places = fluid.cuda_places() if args.use_gpu else fluid.cpu_places()
+    xpu_id = int(os.environ.get('FLAGS_selected_xpus', 0))
+    if args.use_gpu:
+        place = fluid.CUDAPlace(gpu_id)
+        places = fluid.cuda_places()
+    elif args.use_xpu:
+        place = fluid.XPUPlace(xpu_id)
+        places = [place]
+    else:
+        place = fluid.CPUPlace()
+        places = fluid.cpu_places()
 
     # Get number of GPU
     dev_count = cfg.NUM_TRAINERS if cfg.NUM_TRAINERS > 1 else len(places)
@@ -263,10 +277,13 @@ def data_generator():
             print_info(
                 "Sync BatchNorm strategy will not be effective if GPU device"
                 " count <= 1")
-    compiled_train_prog = fluid.CompiledProgram(train_prog).with_data_parallel(
-        loss_name=avg_loss.name,
-        exec_strategy=exec_strategy,
-        build_strategy=build_strategy)
+    if args.use_xpu:
+        compiled_train_prog = train_prog
+    else:
+        compiled_train_prog = fluid.CompiledProgram(train_prog).with_data_parallel(
+            loss_name=avg_loss.name,
+            exec_strategy=exec_strategy,
+            build_strategy=build_strategy)
 
     # Resume training
     begin_epoch = cfg.SOLVER.BEGIN_EPOCH
@@ -408,6 +425,7 @@ def data_generator():
                     cfg=cfg,
                     ckpt_dir=ckpt_dir,
                     use_gpu=args.use_gpu,
+                    use_xpu=args.use_xpu,
                     use_mpio=args.use_mpio)
                 if args.use_vdl:
                     log_writer.add_scalar('Evaluate/mean_iou', mean_iou, step)