bug fixing for lab 1

Author: slolla

lab1/Part1_TensorFlow.ipynb

@@ -377,7 +377,7 @@
         "    return y\n",
         "\n",
         "# Since layer parameters are initialized randomly, we will set a random seed for reproducibility\n",
-        "tf.random.set_seed(1)\n",
+        "tf.keras.utils.set_random_seed(1)\n",
         "layer = OurDenseLayer(3)\n",
         "layer.build((1,2))\n",
         "x_input = tf.constant([[1,2.]], shape=(1,2))\n",
@@ -707,7 +707,17 @@
     },
     "kernelspec": {
       "display_name": "Python 3",
+      "language": "python",
       "name": "python3"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.9.6"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
+      }
     }
   },
   "nbformat": 4,

lab1/solutions/Part1_TensorFlow_Solution.ipynb

@@ -383,7 +383,7 @@
         "    return y\n",
         "\n",
         "# Since layer parameters are initialized randomly, we will set a random seed for reproducibility\n",
-        "tf.random.set_seed(1)\n",
+        "tf.keras.utils.set_random_seed(1)\n",
         "layer = OurDenseLayer(3)\n",
         "layer.build((1,2))\n",
         "x_input = tf.constant([[1,2.]], shape=(1,2))\n",
@@ -725,7 +725,17 @@
     },
     "kernelspec": {
       "display_name": "Python 3",
+      "language": "python",
       "name": "python3"
+    },
+    "language_info": {
+      "name": "python",
+      "version": "3.9.6"
+    },
+    "vscode": {
+      "interpreter": {
+        "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
+      }
     }
   },
   "nbformat": 4,

mitdeeplearning/lab1.py

@@ -80,8 +80,8 @@ def test_batch_func_next_step(func, args):
     return True
 
 def test_custom_dense_layer_output(y):
-    true_y = np.array([[0.2697859,  0.45750418, 0.66536945]],dtype='float32')
+    true_y = np.array([[0.27064407 0.1826951  0.50374055]],dtype='float32')
     assert tf.shape(y).numpy().tolist() == list(true_y.shape), "[FAIL] output is of incorrect shape. expected {} but got {}".format(true_y.shape, y.numpy().shape)
-    np.testing.assert_almost_equal(y.numpy(), true_y, decimal=7, err_msg="[FAIL] output is of incorrect value. expected {} but got {}".format(y.numpy(), true_y), verbose=True)
+    np.testing.assert_almost_equal(y.numpy(), true_y, decimal=7, err_msg="[FAIL] output is of incorrect value. expected {} but got {}".format(true_y, y.numpy()), verbose=True)
     print("[PASS] test_custom_dense_layer_output")
     return True