Fix Reduction Pipeline

app.py

@@ -859,7 +859,8 @@ def run_model(model_name):
         df_all = {}
         # Real
         df_real_proj = embeddings["real"].copy()
-        proj_real = reducer_real.named_steps["pca"].transform(df_real_proj[embedding_cols].values)
+        # proj_real = reducer_real.named_steps["pca"].transform(df_real_proj[embedding_cols].values)
+        proj_real = reducer_real.transform(df_real_proj[embedding_cols].values)
         for i in range(proj_real.shape[1]):
             df_real_proj[f'PC{i+1}'] = proj_real[:, i]
         df_all["real"] = df_real_proj
@@ -867,7 +868,7 @@ def run_model(model_name):
         # Synthetic
         if "synthetic" in embeddings:
             df_synth_proj = embeddings["synthetic"].copy()
-            proj_synth = reducer_real.named_steps["pca"].transform(df_synth_proj[embedding_cols].values)
+            proj_synth = reducer_real.transform(df_synth_proj[embedding_cols].values)
             for i in range(proj_synth.shape[1]):
                 df_synth_proj[f'PC{i+1}'] = proj_synth[:, i]
             df_all["synthetic"] = df_synth_proj
@@ -875,7 +876,7 @@ def run_model(model_name):
         # Pretrained
         if "pretrained" in embeddings:
             df_pretr_proj = embeddings["pretrained"].copy()
-            proj_pretr = reducer_real.named_steps["pca"].transform(df_pretr_proj[embedding_cols].values)
+            proj_pretr = reducer_real.transform(df_pretr_proj[embedding_cols].values)
             for i in range(proj_pretr.shape[1]):
                 df_pretr_proj[f'PC{i+1}'] = proj_pretr[:, i]
             df_all["pretrained"] = df_pretr_proj