Checking dtype of data and label passed to update method

Added missing label parameter to the train global function

wrapper/cxxnet.py

@@ -171,6 +171,10 @@ def update(self, data, label = None):
  raise Exception('Net.update: label need to be 2 dimension or one dimension ndarray')
  if label.shape[0] != data.shape[0]:
  raise Exception('Net.update: data size mismatch')
+ if data.dtype != numpy.float32:
+ raise Exception('Net.update: data must be of type numpy.float32')
+ if label.dtype != numpy.float32:
+ raise Exception('Net.update: label must be of type numpy.float32')
  cxnlib.CXNNetUpdateBatch(self.handle,
  data.ctypes.data_as(ctypes.POINTER(ctypes.c_float)),
  shape2ctypes(data),
@@ -278,7 +282,7 @@ def get_weight(self, layer_name, tag):
  return None
  return ctypes2numpyT(ret, [oshape[i] for i in range(odim.value)], 'float32')
 
-def train(cfg, data, num_round, param, eval_data = None):
+def train(cfg, data, label, num_round, param, eval_data = None):
  net = Net(cfg = cfg)
  if isinstance(param, dict):
  param = param.items()