edit selected_gpu reletive values;test=develop (#22277)

python/paddle/distributed/launch.py

@@ -184,7 +184,22 @@ paddlecloud environment.".format(args.cluster_node_ips, node_ips))
         gpus_num = fluid.core.get_cuda_device_count()
         selected_gpus = [str(x) for x in range(0, gpus_num)]
     else:
+        cuda_visible_devices = os.getenv("CUDA_VISIBLE_DEVICES")
+        if cuda_visible_devices is None or cuda_visible_devices == "":
             selected_gpus = [x.strip() for x in args.selected_gpus.split(',')]
+        else:
+            # change selected_gpus into relative values
+            # e.g. CUDA_VISIBLE_DEVICES=4,5,6,7; args.selected_gpus=4,5,6,7;
+            # therefore selected_gpus=0,1,2,3
+            cuda_visible_devices_list = cuda_visible_devices.split(',')
+            for x in args.selected_gpus.split(','):
+                assert x in cuda_visible_devices_list, "Can't find "\
+                "your selected_gpus %s in CUDA_VISIBLE_DEVICES[%s]."\
+                % (x, cuda_visible_devices)
+            selected_gpus = [
+                cuda_visible_devices_list.index(x.strip())
+                for x in args.selected_gpus.split(',')
+            ]
     selected_gpus_num = len(selected_gpus)
 
     trainers_endpoints = ""

python/paddle/fluid/tests/unittests/test_launch.sh

@@ -13,7 +13,7 @@ export PADDLE_TRAINER_ID=0
 
 distributed_args="--use_paddlecloud --cluster_node_ips=${cluster_node_ips} --node_ip=${node_ip}
 --selected_gpus=0,1 --log_dir=testlog"
-python -m paddle.distributed.launch ${distributed_args} multi_process.py
+CUDA_VISIBLE_DEVICES=0,1 python -m paddle.distributed.launch ${distributed_args} multi_process.py
 
 str1="selected_gpus:0 worker_endpoints:127.0.0.1:6170,127.0.0.1:6171,127.0.0.2:6170,127.0.0.2:6171 trainers_num:4 current_endpoint:127.0.0.1:6170 trainer_id:0"
 str2="selected_gpus:1 worker_endpoints:127.0.0.1:6170,127.0.0.1:6171,127.0.0.2:6170,127.0.0.2:6171 trainers_num:4 current_endpoint:127.0.0.1:6171 trainer_id:1"
@@ -45,7 +45,7 @@ fi
 
 echo ""
 echo "paddle.distributed.launch async poll process test"
-if ! python -m paddle.distributed.launch ${distributed_args} multi_process.py abort; then
+if ! CUDA_VISIBLE_DEVICES=0,1 python -m paddle.distributed.launch ${distributed_args} multi_process.py abort; then
     echo "train abort as planned"
 fi