Fix: dataset no longer treats rendered files as input files

README.md

@@ -38,7 +38,7 @@ Ex. `python scripts/train.py +exp=umx_distortion trainer.accelerator='gpu' train
 ## Misc.
 By default, files are rendered to `input_dir / processed / train/val/test`.
 To skip rendering files (use previously rendered), add `render_files=False` to the command-line
-
+To change the rendered location, add `render_root={path/to/dir}` to the command-line
 Test
 Experiment dictates data, ckpt dictates model
 `python scripts/test.py +exp=umx_distortion.yaml +ckpt_path=test_ckpts/umx_dist.ckpt`

cfg/config.yaml

@@ -9,7 +9,7 @@ sample_rate: 48000
 logs_dir: "./logs"
 log_every_n_steps: 1000
 render_files: True
-render_root: ${oc.env:DATASET_ROOT}
+render_root: "./data/processed"
 
 callbacks:
   model_checkpoint:

remfx/models.py

@@ -39,7 +39,6 @@ class RemFXModel(pl.LightningModule):
             }
         )
         # Log first batch metrics input vs output only once
-        self.log_first_metrics = True
         self.log_train_audio = True
 
     @property
@@ -73,21 +72,22 @@ class RemFXModel(pl.LightningModule):
         self.log(f"{mode}_loss", loss)
         x, y, label = batch
         # Metric logging
-        for metric in self.metrics:
-            # SISDR returns negative values, so negate them
-            if metric == "SISDR":
-                negate = -1
-            else:
-                negate = 1
-            self.log(
-                f"{mode}_{metric}",
-                negate * self.metrics[metric](output, y),
-                on_step=False,
-                on_epoch=True,
-                logger=True,
-                prog_bar=True,
-                sync_dist=True,
-            )
+        with torch.no_grad():
+            for metric in self.metrics:
+                # SISDR returns negative values, so negate them
+                if metric == "SISDR":
+                    negate = -1
+                else:
+                    negate = 1
+                self.log(
+                    f"{mode}_{metric}",
+                    negate * self.metrics[metric](output, y),
+                    on_step=False,
+                    on_epoch=True,
+                    logger=True,
+                    prog_bar=True,
+                    sync_dist=True,
+                )
 
         return loss