first attempt to prune VAE

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "jupyter.jupyterServerType": "local"
+}

MNIST_dataset.py

@@ -59,13 +59,20 @@ def crop_and_interpolate(self, size_initial, size_final, color_depth):
 
         X_train_flat_zoom = []
         X_test_flat_zoom = []
+
+        X_train_flat_zoom_int = []
+        X_test_flat_zoom_int = []
 
         for image in self.x_train:
             tmp = scipy.ndimage.zoom(image[bordo:bordo_top, bordo:bordo_top],
                                      size_final/size_initial).flatten()
             tmp = (tmp/(256//2**color_depth)).astype(int)
             X_train_flat_zoom.append(tmp/2**color_depth)
+            X_train_flat_zoom_int.append(tmp)
+
         X_train_flat_zoom = np.array(X_train_flat_zoom)
+        X_train_flat_zoom_int = np.array(X_train_flat_zoom_int)
+
         self.x_train=X_train_flat_zoom
 
         #processing Test Set
@@ -74,7 +81,10 @@ def crop_and_interpolate(self, size_initial, size_final, color_depth):
                                         size_final/size_initial).flatten()
             tmp = (tmp/(256//2**color_depth)).astype(int)
             X_test_flat_zoom.append(tmp/2**color_depth)
+            X_test_flat_zoom_int.append(tmp)
+
         X_test_flat_zoom = np.array(X_test_flat_zoom)
+        X_test_flat_zoom_int = np.array(X_test_flat_zoom_int)
         self.x_test=X_test_flat_zoom
 
 

hls4ml_conversion.ipynb

@@ -190,7 +190,8 @@
     "hls_model = hls4ml.converters.convert_from_keras_model(ae_wo_classifier,\n",
     "                                                       hls_config=config,\n",
     "                                                       output_dir='model/AE_model/hls4ml_prj',\n",
-    "                                                       part='xcu250-figd2104-2L-e')\n"
+    "                                                       part='xc250-figd2104-2L-e')\n",
+    "                                                       #part='xcvu9p-flgc2104aaz')\n"
    ]
   },
   {