snapshot...

modules/deeplearning/cnn_cld_frac_mod_res.py

@@ -341,6 +341,7 @@ class SRCNN:
         for param in data_params_half:
             idx = params.index(param)
             tmp = input_data[:, idx, :, :]
+            tmp = tmp.copy()
             if DO_ESPCN:
                 tmp = tmp[:, slc_y_2, slc_x_2]
             else:  # Half res upsampled to full res:
@@ -354,6 +355,7 @@ class SRCNN:
         for param in data_params_full:
             idx = params.index(param)
             tmp = input_data[:, idx, :, :]
+            tmp = tmp.copy()
 
             lo, hi, std, avg = get_min_max_std(tmp)
             # std = np.where(np.isnan(std), 0, std)
@@ -367,6 +369,7 @@ class SRCNN:
             # data_norm.append(std[:, 0:66, 0:66])
         # ---------------------------------------------------
         tmp = input_data[:, label_idx, :, :]
+        tmp = tmp.copy()
         tmp = np.where(np.isnan(tmp), 0, tmp)
         if DO_ESPCN:
             tmp = tmp[:, slc_y_2, slc_x_2]
@@ -390,6 +393,7 @@ class SRCNN:
         # -----------------------------------------------------
         # -----------------------------------------------------
         label = input_data[:, label_idx, :, :]
+        label = label.copy()
         label = label[:, y_128, x_128]
         label = get_label_data(label)