code: def T(a, half=False, cuda=True):
      
      if not torch.is_tensor(a):
          a = np.array(np.ascontiguousarray(a))
          if a.dtype in (np.int8, np.int16, np.int32, np.int64):
              a = torch.LongTensor(a.astype(np.int64))
          elif a.dtype in (np.float32, np.float64):
              a = to_half(a) if half else torch.FloatTensor(a)
          else: raise NotImplementedError(a.dtype)
      if cuda: a = to_gpu(a)
      return a
docs: Convert numpy array into a pytorch tensor. 
      if Cuda is available and USE_GPU=True, store resulting tensor in GPU.