For real this time

runner/frameworks/classification/analyze.py

@@ -105,8 +105,8 @@ def analyze(
     if epoch == 0:
         _perform_initialization_analysis(
             channel_analysis,
-            analyses_dir,
             use_wandb,
+            analyses_dir,
             plot_dir,
             checkpoint_plot_dir,
             run_dir,
@@ -128,6 +128,7 @@ def analyze(
 
     _perform_reconstruction_analysis(
         use_wandb,
+        analyses_dir,
         plot_dir,
         checkpoint_plot_dir,
         device,
@@ -152,8 +153,8 @@ def _plot_and_save_histories(plot_dir: Path, histories: Dict[str, List[float]]):
 
 def _perform_initialization_analysis(
     channel_analysis: bool,
-    analyses_dir: Path,
     use_wandb: bool,
+    analyses_dir: Path,
     plot_dir: Path,
     checkpoint_plot_dir: Path,
     run_dir: Path,
@@ -326,6 +327,7 @@ def _analyze_regular_layer(
 
 def _perform_reconstruction_analysis(
     use_wandb: bool,
+    analyses_dir: Path,
     plot_dir: Path,
     checkpoint_plot_dir: Path,
     device: torch.device,
@@ -348,7 +350,7 @@ def _perform_reconstruction_analysis(
             reconstruct_images(device, brain, decoder, train_set, test_set, 5)
         )
         # Save the reconstructions
-        rec_path = plot_dir / f"{decoder}_reconstructions_epoch_{epoch}.json"
+        rec_path = analyses_dir / f"{decoder}_reconstructions_epoch_{epoch}.json"
         with open(rec_path, "w") as f:
             json.dump(rec_dict, f, cls=NumpyEncoder)