refactor

Author: LyndonFan

bench.py

@@ -448,25 +448,25 @@ def load_data(params, generated_data=[], add_dtype=False, label_2d=False,
                 int_dtype if 'y' in element and int_label else params.dtype,
                 params.data_order, params.data_format
             )
-        # generate and convert data if it's marked and path isn't specified
-        if full_data[element] is None and element in generated_data:
-            full_data[element] = convert_data(
-                np.random.rand(*params.shape),
-                int_dtype if 'y' in element and int_label else params.dtype,
-                params.data_order, params.data_format)
-        # convert existing labels from 1- to 2-dimensional
-        # if it's forced and possible
-        if full_data[element] is not None and 'y' in element \
-                and label_2d and hasattr(full_data[element], 'reshape'):
-            full_data[element] = full_data[element].reshape(
-                (full_data[element].shape[0], 1))
-        # add dtype property to data if it's needed and doesn't exist
-        if full_data[element] is not None and add_dtype and \
-                not hasattr(full_data[element], 'dtype'):
-            if hasattr(full_data[element], 'values'):
-                full_data[element].dtype = full_data[element].values.dtype
-            elif hasattr(full_data[element], 'dtypes'):
-                full_data[element].dtype = full_data[element].dtypes[0].type
+        if full_data[element] is None:
+            # generate and convert data if it's marked and path isn't specified
+            if element in generated_data:
+                full_data[element] = convert_data(
+                    np.random.rand(*params.shape),
+                    int_dtype if 'y' in element and int_label else params.dtype,
+                    params.data_order, params.data_format)
+        else:
+            # convert existing labels from 1- to 2-dimensional
+            # if it's forced and possible
+            if 'y' in element and label_2d and hasattr(full_data[element], 'reshape'):
+                full_data[element] = full_data[element].reshape(
+                    (full_data[element].shape[0], 1))
+            # add dtype property to data if it's needed and doesn't exist
+            if add_dtype and not hasattr(full_data[element], 'dtype'):
+                if hasattr(full_data[element], 'values'):
+                    full_data[element].dtype = full_data[element].values.dtype
+                elif hasattr(full_data[element], 'dtypes'):
+                    full_data[element].dtype = full_data[element].dtypes[0].type
 
     params.dtype = get_dtype(full_data['X_train'])
     # add size to parameters which is need for some cases