encoder server update to paddle 1.6,

+ encoder server model_dir sanity check

ernie/service/encoder_server.py

@@ -52,6 +52,8 @@ if __name__ == "__main__":
     cuda_env = os.getenv("CUDA_VISIBLE_DEVICES")
     if cuda_env is None:
         raise RuntimeError('CUDA_VISIBLE_DEVICES not set')
+    if not os.path.exists(args.model_dir):
+        raise ValueError('model_dir not found: %s' % args.model_dir)
     n_devices = len(cuda_env.split(","))
     if args.encode_layer.lower() == 'pooler':
         model_dir = os.path.join(args.model_dir, 'pooler')

propeller/service/utils.py

@@ -61,22 +61,19 @@ def numpy_to_slot(arr):
 def slot_to_paddlearray(slot):
     import paddle.fluid.core as core
     if slot.type == interface_pb2.Slot.FP32:
+        dtype = np.float32
         type_str = 'f'
-        dtype = core.PaddleDType.FLOAT32
     elif slot.type == interface_pb2.Slot.INT32:
+        dtype = np.int32
         type_str = 'i'
-        dtype = core.PaddleDType.INT32
     elif slot.type == interface_pb2.Slot.INT64:
+        dtype = np.int64
         type_str = 'q'
-        dtype = core.PaddleDType.INT64
     else:
         raise RuntimeError('know type %s' % slot.type)
-    ret = core.PaddleTensor()
-    ret.shape = slot.dims
-    ret.dtype = dtype
     num = len(slot.data) // struct.calcsize(type_str)
     arr = struct.unpack('%d%s' % (num, type_str), slot.data)
-    ret.data = core.PaddleBuf(arr)
+    ret = core.PaddleTensor(name='1', data=np.array(arr, dtype=dtype).reshape(slot.dims))
     return ret