steps for save

PlayVoice · Jun 12, 2023 · e4d311e · e4d311e
1 parent 7f70a58
commit e4d311e
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Showing 4 changed files with 19 additions and 19 deletions.
diff --git a/README.md b/README.md
@@ -24,7 +24,7 @@ Necessary pre-processing:
 - 1 accompaniment separation
 - 2 band extension
 - 3 sound quality improvement
-- 4 cut audio, less than 30 seconds for whisper💗
+- 4 cut audio, less than 30 seconds for whisper
 
 then put the dataset into the dataset_raw directory according to the following file structure
 ```shell
@@ -88,7 +88,7 @@ dataset_raw
     > python prepare/preprocess_train.py
 
 - 8， training file debugging
-    > python prepare/preprocess_zzz.py
+    > python prepare/preprocess_zzz.py -c configs/maxgan.yaml
 
 ```shell
 data_svc/

diff --git a/configs/maxgan.yaml b/configs/maxgan.yaml
@@ -52,8 +52,8 @@ dist_config:
 #############################
 log:
   info_interval: 100
-  eval_interval: 1
-  save_interval: 5
+  eval_interval: 1000
+  save_interval: 1000
   num_audio: 6
   pth_dir: 'chkpt'
   log_dir: 'logs'
diff --git a/utils/train.py b/utils/train.py
@@ -204,16 +204,16 @@ def train(rank, args, chkpt_path, hp, hp_str):
                 with torch.no_grad():
                     validate(hp, args, model_g, model_d, valloader, stft, writer, step, device)
 
-        if rank == 0 and epoch % hp.log.save_interval == 0:
-            save_path = os.path.join(pt_dir, '%s_%04d.pt'
-                                     % (args.name, epoch))
-            torch.save({
-                'model_g': (model_g.module if args.num_gpus > 1 else model_g).state_dict(),
-                'model_d': (model_d.module if args.num_gpus > 1 else model_d).state_dict(),
-                'optim_g': optim_g.state_dict(),
-                'optim_d': optim_d.state_dict(),
-                'step': step,
-                'epoch': epoch,
-                'hp_str': hp_str,
-            }, save_path)
-            logger.info("Saved checkpoint to: %s" % save_path)
+            if rank == 0 and step % hp.log.save_interval == 0:
+                save_path = os.path.join(pth_dir, '%s_%08d.pt'
+                                         % (args.name, step))
+                torch.save({
+                    'model_g': (model_g.module if args.num_gpus > 1 else model_g).state_dict(),
+                    'model_d': (model_d.module if args.num_gpus > 1 else model_d).state_dict(),
+                    'optim_g': optim_g.state_dict(),
+                    'optim_d': optim_d.state_dict(),
+                    'step': step,
+                    'epoch': epoch,
+                    'hp_str': hp_str,
+                }, save_path)
+                logger.info("Saved checkpoint to: %s" % save_path)
diff --git a/utils/writer.py b/utils/writer.py
@@ -21,8 +21,8 @@ def log_training(self, g_loss, d_loss, mel_loss, stft_loss, score_loss, step):
     def log_validation(self, mel_loss, generator, discriminator, step):
         self.add_scalar('validation/mel_loss', mel_loss, step)
 
-        self.log_histogram(generator, step)
-        self.log_histogram(discriminator, step)
+        # self.log_histogram(generator, step)
+        # self.log_histogram(discriminator, step)
         if self.is_first:
             self.is_first = False