fix bug of norm level check for r1.7

mindarmour/utils/_check_param.py

@@ -204,7 +204,7 @@ def check_norm_level(norm_level):
     """Check norm_level of regularization."""
     if not isinstance(norm_level, (int, str)):
         msg = 'Type of norm_level must be in [int, str], but got {}'.format(type(norm_level))
-    accept_norm = [1, 2, '1', '2', 'l1', 'l2', 'inf', 'linf', np.inf]
+    accept_norm = [1, 2, '1', '2', 'l1', 'l2', 'inf', 'linf', 'np.inf', np.inf]
     if norm_level not in accept_norm:
         msg = 'norm_level must be in {}, but got {}'.format(accept_norm, norm_level)
         LOGGER.error(TAG, msg)
@@ -218,14 +218,13 @@ def normalize_value(value, norm_level):
 
     Args:
         value (numpy.ndarray): Inputs.
-        norm_level (Union[int, str]): Normalized level. Option: [1, 2, np.inf, '1', '2', 'inf', 'l1', 'l2']
+        norm_level (Union[int, str]): Normalized level. Option: [1, 2, np.inf, 'np.inf', '1', '2', 'inf', 'l1', 'l2']
 
     Returns:
         numpy.ndarray, normalized value.
 
     Raises:
-        NotImplementedError: If norm_level is not in [1, 2 , np.inf, '1', '2',
-            'inf', 'l1', 'l2']
+        NotImplementedError: If norm_level is not in [1, 2 , np.inf, 'np.inf', '1', '2', 'inf', 'l1', 'l2']
     """
     norm_level = check_norm_level(norm_level)
     ori_shape = value.shape
@@ -237,12 +236,12 @@ def normalize_value(value, norm_level):
     elif norm_level in (2, '2', 'l2'):
         norm = np.linalg.norm(value_reshape, ord=2, axis=1, keepdims=True) + avoid_zero_div
         norm_value = value_reshape / norm
-    elif norm_level in (np.inf, 'inf'):
+    elif norm_level in (np.inf, 'inf', 'np.inf'):
         norm = np.max(abs(value_reshape), axis=1, keepdims=True) + avoid_zero_div
         norm_value = value_reshape / norm
     else:
-        msg = 'Values of `norm_level` different from 1, 2 and `np.inf` are currently not supported, but got {}.' \
-            .format(norm_level)
+        accept_norm = [1, 2, '1', '2', 'l1', 'l2', 'inf', 'linf', 'np.inf', np.inf]
+        msg = 'Values of `norm_level` must be in {}, but got {}'.format(accept_norm, norm_level)
         LOGGER.error(TAG, msg)
         raise NotImplementedError(msg)
     return norm_value.reshape(ori_shape)