use fp32 to initilize parameter values and then cast to fp16.

PaddleCV/image_classification/train.py

@@ -189,12 +189,12 @@ def train(args):
         #Create test_prog and set layers' is_test params to True
         test_prog = test_prog.clone(for_test=True)
 
-    if args.use_pure_fp16:
-        cast_parameters_to_fp16(startup_prog)
     gpu_id = int(os.environ.get('FLAGS_selected_gpus', 0))
     place = fluid.CUDAPlace(gpu_id) if args.use_gpu else fluid.CPUPlace()
     exe = fluid.Executor(place)
     exe.run(startup_prog)
+    if args.use_pure_fp16:
+        cast_parameters_to_fp16(exe, train_prog, fluid.global_scope())
 
     trainer_id = int(os.getenv("PADDLE_TRAINER_ID", 0))