diff --git a/GPT_SoVITS/s2_train.py b/GPT_SoVITS/s2_train.py
index 4d88ee8..ea863b0 100644
--- a/GPT_SoVITS/s2_train.py
+++ b/GPT_SoVITS/s2_train.py
@@ -429,26 +429,25 @@ def train_and_evaluate(
                 # scalar_dict.update({"loss/g/{}".format(i): v for i, v in enumerate(losses_gen)})
                 # scalar_dict.update({"loss/d_r/{}".format(i): v for i, v in enumerate(losses_disc_r)})
                 # scalar_dict.update({"loss/d_g/{}".format(i): v for i, v in enumerate(losses_disc_g)})
-                image_dict = {
-                    "slice/mel_org": utils.plot_spectrogram_to_numpy(
-                        y_mel[0].data.cpu().numpy()
-                    ),
-                    "slice/mel_gen": utils.plot_spectrogram_to_numpy(
-                        y_hat_mel[0].data.cpu().numpy()
-                    ),
-                    "all/mel": utils.plot_spectrogram_to_numpy(
-                        mel[0].data.cpu().numpy()
-                    ),
-                    "all/stats_ssl": utils.plot_spectrogram_to_numpy(
-                        stats_ssl[0].data.cpu().numpy()
-                    ),
-                }
-                utils.summarize(
-                    writer=writer,
-                    global_step=global_step,
-                    images=image_dict,
-                    scalars=scalar_dict,
-                )
+                image_dict=None
+                try:###Some people installed the wrong version of matplotlib.
+                    image_dict = {
+                        "slice/mel_org": utils.plot_spectrogram_to_numpy(
+                            y_mel[0].data.cpu().numpy()
+                        ),
+                        "slice/mel_gen": utils.plot_spectrogram_to_numpy(
+                            y_hat_mel[0].data.cpu().numpy()
+                        ),
+                        "all/mel": utils.plot_spectrogram_to_numpy(
+                            mel[0].data.cpu().numpy()
+                        ),
+                        "all/stats_ssl": utils.plot_spectrogram_to_numpy(
+                            stats_ssl[0].data.cpu().numpy()
+                        ),
+                    }
+                except:pass
+                if image_dict:utils.summarize(writer=writer,global_step=global_step,images=image_dict,scalars=scalar_dict,)
+                else:utils.summarize(writer=writer,global_step=global_step,scalars=scalar_dict,)
         global_step += 1
     if epoch % hps.train.save_every_epoch == 0 and rank == 0:
         if hps.train.if_save_latest == 0: