replace print with warning for cpu tensors and allow numpy arrays as inputs to forward function

apex/amp/_initialize.py

 import torch
 from torch._six import string_classes
 import functools
+import numpy as np
+import warnings
 from ._amp_state import _amp_state, warn_or_err, container_abcs
 from .handle import disable_casts
 from .scaler import LossScaler
@@ -15,7 +17,7 @@ def to_type(dtype, t):
     if isinstance(t, torch.Tensor):
         if not t.is_cuda:
             # This should not be a hard error, since it may be legitimate.
-            print("Warning:  An input tensor was not cuda. ")
+            warnings.warn("An input tensor was not cuda.")
         # GANs require this.
         # if t.requires_grad:
         #     warn_or_err("input data requires grad.  Since input data is not a model parameter,\n"
@@ -34,6 +36,8 @@ def applier(value, fn):
         return fn(value)
     elif isinstance(value, string_classes):
         return value
+    elif isinstance(value, np.ndarray):
+        return value
     elif isinstance(value, container_abcs.Mapping):
         return {applier(k, fn) : applier(v, fn) for k, v in value.items()}
     elif isinstance(value, container_abcs.Iterable):