Layer factory

docs/api.rst

@@ -50,6 +50,5 @@ Model Handler
 
     .. Add/replace module names you want documented here
     xfer.model_handler.ModelHandler
-    xfer.model_handler.layer_factory
     xfer.model_handler.exceptions
     xfer.model_handler.consts

docs/demos/xfer-custom-repurposers.ipynb

@@ -347,8 +347,8 @@
       "             precision    recall  f1-score   support\n",
       "\n",
       "          0       1.00      0.50      0.67         2\n",
-      "          1       1.00      1.00      1.00         2\n",
-      "          2       0.67      1.00      0.80         2\n",
+      "          1       0.67      1.00      0.80         2\n",
+      "          2       1.00      1.00      1.00         2\n",
       "          3       1.00      1.00      1.00         2\n",
       "\n",
       "avg / total       0.92      0.88      0.87         8\n",
@@ -417,14 +417,13 @@
     "        model_handler.update_sym(target_symbol)\n",
     "\n",
     "        # Add a fully connected layer (with nodes equal to number of target classes) and a softmax output layer on top\n",
-    "        fully_connected_layer1 = xfer.model_handler.layer_factory.FullyConnected(num_hidden=self.num_nodes, name='fc_rep')\n",
-    "        fully_connected_layer2 = xfer.model_handler.layer_factory.FullyConnected(num_hidden=self.target_class_count,\n",
-    "                                                             name='fc_from_fine_tune_repurposer')\n",
-    "        softmax_output_layer = xfer.model_handler.layer_factory.SoftmaxOutput(name=train_iterator.provide_label[0][0].replace('_label', ''))\n",
+    "        fully_connected_layer1 = mx.sym.FullyConnected(num_hidden=self.num_nodes, name='fc_rep')\n",
+    "        fully_connected_layer2 = mx.sym.FullyConnected(num_hidden=self.target_class_count, name='fc_from_fine_tune_repurposer')\n",
+    "        softmax_output_layer = mx.sym.SoftmaxOutput(name=train_iterator.provide_label[0][0].replace('_label', ''))\n",
     "        model_handler.add_layer_top([fully_connected_layer1, fully_connected_layer2,  softmax_output_layer])\n",
     "\n",
     "        # Get fixed layers\n",
-    "        conv_layer_names = model_handler.get_layer_names_matching_type(xfer.model_handler.consts.LayerType.CONVOLUTION)\n",
+    "        conv_layer_names = model_handler.get_layer_names_matching_type('Convolution')\n",
     "        conv_layer_params = model_handler.get_layer_parameters(conv_layer_names)\n",
     "        \n",
     "        # Create and return target mxnet module using the new symbol and params\n",
@@ -488,10 +487,10 @@
       "\n",
       "          0       1.00      0.50      0.67         2\n",
       "          1       1.00      1.00      1.00         2\n",
-      "          2       0.50      1.00      0.67         2\n",
-      "          3       1.00      0.50      0.67         2\n",
+      "          2       1.00      1.00      1.00         2\n",
+      "          3       0.67      1.00      0.80         2\n",
       "\n",
-      "avg / total       0.88      0.75      0.75         8\n",
+      "avg / total       0.92      0.88      0.87         8\n",
       "\n"
      ]
     }
@@ -503,7 +502,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python [default]",
    "language": "python",
    "name": "python3"
   },
@@ -517,7 +516,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.4"
+   "version": "3.6.1"
   }
  },
  "nbformat": 4,