From 326ac718f2c7f974c634c93251d6e52bcfd7ed21 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= <ageron@users.noreply.github.com>
Date: Sat, 5 Oct 2024 18:35:28 +1300
Subject: [PATCH] Update notebook to latest Colab library versions

---
 ..._models_and_training_with_tensorflow.ipynb | 606 +++++++++---------
 1 file changed, 303 insertions(+), 303 deletions(-)

diff --git a/12_custom_models_and_training_with_tensorflow.ipynb b/12_custom_models_and_training_with_tensorflow.ipynb
index a66daa6..0449cab 100644
--- a/12_custom_models_and_training_with_tensorflow.ipynb
+++ b/12_custom_models_and_training_with_tensorflow.ipynb
@@ -2222,7 +2222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2246,7 +2246,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 95,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2261,7 +2261,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 96,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2270,7 +2270,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 97,
    "metadata": {},
    "outputs": [
     {
@@ -2289,7 +2289,7 @@
        "<keras.src.callbacks.History at 0x19b4fcf10>"
       ]
      },
-     "execution_count": 99,
+     "execution_count": 97,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2317,7 +2317,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 98,
    "metadata": {},
    "outputs": [
     {
@@ -2326,7 +2326,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=0.8>"
       ]
      },
-     "execution_count": 100,
+     "execution_count": 98,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2338,7 +2338,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 99,
    "metadata": {},
    "outputs": [
     {
@@ -2347,7 +2347,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=0.5>"
       ]
      },
-     "execution_count": 101,
+     "execution_count": 99,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2358,7 +2358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 100,
    "metadata": {},
    "outputs": [
     {
@@ -2367,7 +2367,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=0.5>"
       ]
      },
-     "execution_count": 102,
+     "execution_count": 100,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2378,7 +2378,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 101,
    "metadata": {},
    "outputs": [
     {
@@ -2388,7 +2388,7 @@
        " <tf.Variable 'false_positives:0' shape=(1,) dtype=float32, numpy=array([4.], dtype=float32)>]"
       ]
      },
-     "execution_count": 103,
+     "execution_count": 101,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2406,7 +2406,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 102,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2429,7 +2429,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 103,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2463,7 +2463,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 104,
    "metadata": {},
    "outputs": [
     {
@@ -2472,7 +2472,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=14.0>"
       ]
      },
-     "execution_count": 106,
+     "execution_count": 104,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2488,7 +2488,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 105,
    "metadata": {},
    "outputs": [
     {
@@ -2497,7 +2497,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=7.0>"
       ]
      },
-     "execution_count": 107,
+     "execution_count": 105,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2511,7 +2511,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 106,
    "metadata": {},
    "outputs": [
     {
@@ -2520,7 +2520,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=7.0>"
       ]
      },
-     "execution_count": 108,
+     "execution_count": 106,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2531,7 +2531,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 107,
    "metadata": {},
    "outputs": [
     {
@@ -2541,7 +2541,7 @@
        " <tf.Variable 'count:0' shape=() dtype=float32, numpy=3.0>]"
       ]
      },
-     "execution_count": 109,
+     "execution_count": 107,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2552,7 +2552,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 110,
+   "execution_count": 108,
    "metadata": {},
    "outputs": [
     {
@@ -2562,7 +2562,7 @@
        " <tf.Variable 'count:0' shape=() dtype=float32, numpy=0.0>]"
       ]
      },
-     "execution_count": 110,
+     "execution_count": 108,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2581,7 +2581,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 109,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2595,7 +2595,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 110,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2605,7 +2605,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 111,
    "metadata": {},
    "outputs": [
     {
@@ -2624,7 +2624,7 @@
        "<keras.src.callbacks.History at 0x19c2d1300>"
       ]
      },
-     "execution_count": 113,
+     "execution_count": 111,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2635,7 +2635,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
+   "execution_count": 112,
    "metadata": {},
    "outputs": [
     {
@@ -2659,7 +2659,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 113,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2674,7 +2674,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
+   "execution_count": 114,
    "metadata": {},
    "outputs": [
     {
@@ -2693,7 +2693,7 @@
        "<keras.src.callbacks.History at 0x19b5f0130>"
       ]
      },
-     "execution_count": 116,
+     "execution_count": 114,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2711,7 +2711,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 118,
+   "execution_count": 115,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2739,7 +2739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 116,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2753,7 +2753,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 117,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2763,7 +2763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 121,
+   "execution_count": 118,
    "metadata": {
     "scrolled": true
    },
@@ -2788,7 +2788,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 122,
+   "execution_count": 119,
    "metadata": {},
    "outputs": [
     {
@@ -2797,7 +2797,7 @@
        "(0.3272010087966919, 0.3272010869771911)"
       ]
      },
-     "execution_count": 122,
+     "execution_count": 119,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2809,7 +2809,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 123,
+   "execution_count": 120,
    "metadata": {},
    "outputs": [
     {
@@ -2833,7 +2833,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 124,
+   "execution_count": 121,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2843,7 +2843,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 125,
+   "execution_count": 122,
    "metadata": {},
    "outputs": [
     {
@@ -2862,7 +2862,7 @@
        "<keras.src.callbacks.History at 0x19c576e90>"
       ]
      },
-     "execution_count": 125,
+     "execution_count": 122,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2880,7 +2880,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 127,
+   "execution_count": 123,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2889,7 +2889,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 128,
+   "execution_count": 124,
    "metadata": {},
    "outputs": [
     {
@@ -2898,7 +2898,7 @@
        "<tf.Tensor: shape=(3,), dtype=float32, numpy=array([0.36787945, 1.        , 2.7182817 ], dtype=float32)>"
       ]
      },
-     "execution_count": 128,
+     "execution_count": 124,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2917,7 +2917,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 129,
+   "execution_count": 125,
    "metadata": {},
    "outputs": [
     {
@@ -2943,7 +2943,7 @@
        "0.3781099021434784"
       ]
      },
-     "execution_count": 129,
+     "execution_count": 125,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2970,7 +2970,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 130,
+   "execution_count": 126,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2998,7 +2998,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 131,
+   "execution_count": 127,
    "metadata": {},
    "outputs": [
     {
@@ -3037,7 +3037,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 132,
+   "execution_count": 128,
    "metadata": {},
    "outputs": [
     {
@@ -3056,7 +3056,7 @@
        "<keras.src.callbacks.History at 0x19cbf39a0>"
       ]
      },
-     "execution_count": 132,
+     "execution_count": 128,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3071,7 +3071,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 133,
+   "execution_count": 129,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3091,7 +3091,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 134,
+   "execution_count": 130,
    "metadata": {},
    "outputs": [
     {
@@ -3109,7 +3109,7 @@
        " <KerasTensor: shape=(None, 2) dtype=float32 (created by layer 'my_multi_layer')>)"
       ]
      },
-     "execution_count": 134,
+     "execution_count": 130,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3132,7 +3132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 135,
+   "execution_count": 131,
    "metadata": {},
    "outputs": [
     {
@@ -3156,7 +3156,7 @@
        "        [0.5      , 2.3333333]], dtype=float32)>)"
       ]
      },
-     "execution_count": 135,
+     "execution_count": 131,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3176,7 +3176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 136,
+   "execution_count": 132,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3202,7 +3202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 137,
+   "execution_count": 133,
    "metadata": {},
    "outputs": [
     {
@@ -3222,7 +3222,7 @@
        "1.1058681011199951"
       ]
      },
-     "execution_count": 137,
+     "execution_count": 133,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3251,7 +3251,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 138,
+   "execution_count": 134,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3271,7 +3271,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 135,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3300,7 +3300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 140,
+   "execution_count": 136,
    "metadata": {},
    "outputs": [
     {
@@ -3335,7 +3335,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 141,
+   "execution_count": 137,
    "metadata": {},
    "outputs": [
     {
@@ -3357,7 +3357,7 @@
        "       [4.71127  ]], dtype=float32)"
       ]
      },
-     "execution_count": 141,
+     "execution_count": 137,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3379,7 +3379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 142,
+   "execution_count": 138,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3410,7 +3410,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 143,
+   "execution_count": 139,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3438,7 +3438,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 144,
+   "execution_count": 140,
    "metadata": {},
    "outputs": [
     {
@@ -3477,7 +3477,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 145,
+   "execution_count": 141,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3487,7 +3487,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
+   "execution_count": 142,
    "metadata": {},
    "outputs": [
     {
@@ -3496,7 +3496,7 @@
        "36.000003007075065"
       ]
      },
-     "execution_count": 146,
+     "execution_count": 142,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3509,7 +3509,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
+   "execution_count": 143,
    "metadata": {},
    "outputs": [
     {
@@ -3518,7 +3518,7 @@
        "10.000000003174137"
       ]
      },
-     "execution_count": 147,
+     "execution_count": 143,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3529,7 +3529,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
+   "execution_count": 144,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3542,7 +3542,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 149,
+   "execution_count": 145,
    "metadata": {},
    "outputs": [
     {
@@ -3552,7 +3552,7 @@
        " <tf.Tensor: shape=(), dtype=float32, numpy=10.0>]"
       ]
      },
-     "execution_count": 149,
+     "execution_count": 145,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3563,7 +3563,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 150,
+   "execution_count": 146,
    "metadata": {},
    "outputs": [
     {
@@ -3587,7 +3587,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 151,
+   "execution_count": 147,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3601,7 +3601,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 152,
+   "execution_count": 148,
    "metadata": {},
    "outputs": [
     {
@@ -3611,7 +3611,7 @@
        " <tf.Tensor: shape=(), dtype=float32, numpy=10.0>)"
       ]
      },
-     "execution_count": 152,
+     "execution_count": 148,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3622,7 +3622,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 153,
+   "execution_count": 149,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3635,7 +3635,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 154,
+   "execution_count": 150,
    "metadata": {},
    "outputs": [
     {
@@ -3644,7 +3644,7 @@
        "[None, None]"
       ]
      },
-     "execution_count": 154,
+     "execution_count": 150,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3655,7 +3655,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 155,
+   "execution_count": 151,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3667,6 +3667,99 @@
     "gradients = tape.gradient(z, [c1, c2])"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 152,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<tf.Tensor: shape=(), dtype=float32, numpy=36.0>,\n",
+       " <tf.Tensor: shape=(), dtype=float32, numpy=10.0>]"
+      ]
+     },
+     "execution_count": 152,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "gradients"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 153,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<tf.Tensor: shape=(), dtype=float32, numpy=136.0>,\n",
+       " <tf.Tensor: shape=(), dtype=float32, numpy=30.0>]"
+      ]
+     },
+     "execution_count": 153,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# extra code – if given a vector, tape.gradient() will compute the gradient of\n",
+    "#              the vector's sum.\n",
+    "with tf.GradientTape() as tape:\n",
+    "    z1 = f(w1, w2 + 2.)\n",
+    "    z2 = f(w1, w2 + 5.)\n",
+    "    z3 = f(w1, w2 + 7.)\n",
+    "\n",
+    "tape.gradient([z1, z2, z3], [w1, w2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 154,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<tf.Tensor: shape=(), dtype=float32, numpy=136.0>,\n",
+       " <tf.Tensor: shape=(), dtype=float32, numpy=30.0>]"
+      ]
+     },
+     "execution_count": 154,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# extra code – shows that we get the same result as the previous cell\n",
+    "with tf.GradientTape() as tape:\n",
+    "    z1 = f(w1, w2 + 2.)\n",
+    "    z2 = f(w1, w2 + 5.)\n",
+    "    z3 = f(w1, w2 + 7.)\n",
+    "    z = z1 + z2 + z3\n",
+    "\n",
+    "tape.gradient(z, [w1, w2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 155,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# extra code – shows how to compute the jacobians and the hessians\n",
+    "with tf.GradientTape(persistent=True) as hessian_tape:\n",
+    "    with tf.GradientTape() as jacobian_tape:\n",
+    "        z = f(w1, w2)\n",
+    "    jacobians = jacobian_tape.gradient(z, [w1, w2])\n",
+    "hessians = [hessian_tape.gradient(jacobian, [w1, w2])\n",
+    "            for jacobian in jacobians]\n",
+    "del hessian_tape"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 156,
@@ -3685,106 +3778,13 @@
     }
    ],
    "source": [
-    "gradients"
+    "jacobians"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 157,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<tf.Tensor: shape=(), dtype=float32, numpy=136.0>,\n",
-       " <tf.Tensor: shape=(), dtype=float32, numpy=30.0>]"
-      ]
-     },
-     "execution_count": 157,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# extra code – if given a vector, tape.gradient() will compute the gradient of\n",
-    "#              the vector's sum.\n",
-    "with tf.GradientTape() as tape:\n",
-    "    z1 = f(w1, w2 + 2.)\n",
-    "    z2 = f(w1, w2 + 5.)\n",
-    "    z3 = f(w1, w2 + 7.)\n",
-    "\n",
-    "tape.gradient([z1, z2, z3], [w1, w2])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 158,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<tf.Tensor: shape=(), dtype=float32, numpy=136.0>,\n",
-       " <tf.Tensor: shape=(), dtype=float32, numpy=30.0>]"
-      ]
-     },
-     "execution_count": 158,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "# extra code – shows that we get the same result as the previous cell\n",
-    "with tf.GradientTape() as tape:\n",
-    "    z1 = f(w1, w2 + 2.)\n",
-    "    z2 = f(w1, w2 + 5.)\n",
-    "    z3 = f(w1, w2 + 7.)\n",
-    "    z = z1 + z2 + z3\n",
-    "\n",
-    "tape.gradient(z, [w1, w2])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 159,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# extra code – shows how to compute the jacobians and the hessians\n",
-    "with tf.GradientTape(persistent=True) as hessian_tape:\n",
-    "    with tf.GradientTape() as jacobian_tape:\n",
-    "        z = f(w1, w2)\n",
-    "    jacobians = jacobian_tape.gradient(z, [w1, w2])\n",
-    "hessians = [hessian_tape.gradient(jacobian, [w1, w2])\n",
-    "            for jacobian in jacobians]\n",
-    "del hessian_tape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 160,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<tf.Tensor: shape=(), dtype=float32, numpy=36.0>,\n",
-       " <tf.Tensor: shape=(), dtype=float32, numpy=10.0>]"
-      ]
-     },
-     "execution_count": 160,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "jacobians"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 161,
-   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -3794,7 +3794,7 @@
        " [<tf.Tensor: shape=(), dtype=float32, numpy=2.0>, None]]"
       ]
      },
-     "execution_count": 161,
+     "execution_count": 157,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3805,7 +3805,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 162,
+   "execution_count": 158,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3820,7 +3820,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 163,
+   "execution_count": 159,
    "metadata": {},
    "outputs": [
     {
@@ -3829,7 +3829,7 @@
        "[<tf.Tensor: shape=(), dtype=float32, numpy=30.0>, None]"
       ]
      },
-     "execution_count": 163,
+     "execution_count": 159,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3840,7 +3840,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 164,
+   "execution_count": 160,
    "metadata": {},
    "outputs": [
     {
@@ -3849,7 +3849,7 @@
        "[<tf.Tensor: shape=(), dtype=float32, numpy=inf>]"
       ]
      },
-     "execution_count": 164,
+     "execution_count": 160,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3864,7 +3864,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 165,
+   "execution_count": 161,
    "metadata": {},
    "outputs": [
     {
@@ -3873,7 +3873,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=30.0>"
       ]
      },
-     "execution_count": 165,
+     "execution_count": 161,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3884,7 +3884,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 166,
+   "execution_count": 162,
    "metadata": {},
    "outputs": [
     {
@@ -3893,7 +3893,7 @@
        "[<tf.Tensor: shape=(1,), dtype=float32, numpy=array([nan], dtype=float32)>]"
       ]
      },
-     "execution_count": 166,
+     "execution_count": 162,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3908,7 +3908,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 167,
+   "execution_count": 163,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3933,7 +3933,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 168,
+   "execution_count": 164,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3948,7 +3948,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 169,
+   "execution_count": 165,
    "metadata": {},
    "outputs": [
     {
@@ -3958,7 +3958,7 @@
        " [<tf.Tensor: shape=(1,), dtype=float32, numpy=array([1.], dtype=float32)>])"
       ]
      },
-     "execution_count": 169,
+     "execution_count": 165,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3981,7 +3981,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 170,
+   "execution_count": 166,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3996,7 +3996,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 171,
+   "execution_count": 167,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4007,7 +4007,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 172,
+   "execution_count": 168,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4020,7 +4020,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 173,
+   "execution_count": 169,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4036,7 +4036,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 174,
+   "execution_count": 170,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4051,7 +4051,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 175,
+   "execution_count": 171,
    "metadata": {
     "scrolled": true
    },
@@ -4103,7 +4103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 176,
+   "execution_count": 172,
    "metadata": {},
    "outputs": [
     {
@@ -4235,7 +4235,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 177,
+   "execution_count": 173,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4245,7 +4245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 178,
+   "execution_count": 174,
    "metadata": {},
    "outputs": [
     {
@@ -4254,7 +4254,7 @@
        "8"
       ]
      },
-     "execution_count": 178,
+     "execution_count": 174,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4265,7 +4265,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 179,
+   "execution_count": 175,
    "metadata": {},
    "outputs": [
     {
@@ -4274,7 +4274,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=8.0>"
       ]
      },
-     "execution_count": 179,
+     "execution_count": 175,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4285,7 +4285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 180,
+   "execution_count": 176,
    "metadata": {},
    "outputs": [
     {
@@ -4294,7 +4294,7 @@
        "<tensorflow.python.eager.polymorphic_function.polymorphic_function.Function at 0x19db349d0>"
       ]
      },
-     "execution_count": 180,
+     "execution_count": 176,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4306,7 +4306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 181,
+   "execution_count": 177,
    "metadata": {},
    "outputs": [
     {
@@ -4315,7 +4315,7 @@
        "<tf.Tensor: shape=(), dtype=int32, numpy=8>"
       ]
      },
-     "execution_count": 181,
+     "execution_count": 177,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4326,7 +4326,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 182,
+   "execution_count": 178,
    "metadata": {},
    "outputs": [
     {
@@ -4335,7 +4335,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=8.0>"
       ]
      },
-     "execution_count": 182,
+     "execution_count": 178,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4346,7 +4346,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 183,
+   "execution_count": 179,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4371,7 +4371,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 184,
+   "execution_count": 180,
    "metadata": {},
    "outputs": [
     {
@@ -4380,7 +4380,7 @@
        "<ConcreteFunction tf_cube(x) at 0x19F90F400>"
       ]
      },
-     "execution_count": 184,
+     "execution_count": 180,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4392,7 +4392,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 185,
+   "execution_count": 181,
    "metadata": {},
    "outputs": [
     {
@@ -4401,7 +4401,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=8.0>"
       ]
      },
-     "execution_count": 185,
+     "execution_count": 181,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4412,7 +4412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 186,
+   "execution_count": 182,
    "metadata": {},
    "outputs": [
     {
@@ -4421,7 +4421,7 @@
        "True"
       ]
      },
-     "execution_count": 186,
+     "execution_count": 182,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4439,7 +4439,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 187,
+   "execution_count": 183,
    "metadata": {},
    "outputs": [
     {
@@ -4448,7 +4448,7 @@
        "PyGraph<6956689888>"
       ]
      },
-     "execution_count": 187,
+     "execution_count": 183,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4459,7 +4459,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 188,
+   "execution_count": 184,
    "metadata": {},
    "outputs": [
     {
@@ -4471,7 +4471,7 @@
        " <tf.Operation 'Identity' type=Identity>]"
       ]
      },
-     "execution_count": 188,
+     "execution_count": 184,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4483,7 +4483,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 189,
+   "execution_count": 185,
    "metadata": {},
    "outputs": [
     {
@@ -4493,7 +4493,7 @@
        " <tf.Tensor 'pow/y:0' shape=() dtype=float32>]"
       ]
      },
-     "execution_count": 189,
+     "execution_count": 185,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4505,7 +4505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 190,
+   "execution_count": 186,
    "metadata": {},
    "outputs": [
     {
@@ -4514,7 +4514,7 @@
        "[<tf.Tensor 'pow:0' shape=() dtype=float32>]"
       ]
      },
-     "execution_count": 190,
+     "execution_count": 186,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4525,7 +4525,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 191,
+   "execution_count": 187,
    "metadata": {},
    "outputs": [
     {
@@ -4534,7 +4534,7 @@
        "<tf.Operation 'x' type=Placeholder>"
       ]
      },
-     "execution_count": 191,
+     "execution_count": 187,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4545,7 +4545,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 192,
+   "execution_count": 188,
    "metadata": {},
    "outputs": [
     {
@@ -4554,7 +4554,7 @@
        "<tf.Tensor 'Identity:0' shape=() dtype=float32>"
       ]
      },
-     "execution_count": 192,
+     "execution_count": 188,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4565,7 +4565,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 193,
+   "execution_count": 189,
    "metadata": {},
    "outputs": [
     {
@@ -4582,7 +4582,7 @@
        "}"
       ]
      },
-     "execution_count": 193,
+     "execution_count": 189,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4600,7 +4600,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 194,
+   "execution_count": 190,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4612,7 +4612,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 195,
+   "execution_count": 191,
    "metadata": {},
    "outputs": [
     {
@@ -4629,7 +4629,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 196,
+   "execution_count": 192,
    "metadata": {},
    "outputs": [
     {
@@ -4638,7 +4638,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=8.0>"
       ]
      },
-     "execution_count": 196,
+     "execution_count": 192,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4649,7 +4649,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 197,
+   "execution_count": 193,
    "metadata": {},
    "outputs": [
     {
@@ -4666,7 +4666,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 198,
+   "execution_count": 194,
    "metadata": {},
    "outputs": [
     {
@@ -4683,7 +4683,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 199,
+   "execution_count": 195,
    "metadata": {},
    "outputs": [
     {
@@ -4700,7 +4700,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 200,
+   "execution_count": 196,
    "metadata": {},
    "outputs": [
     {
@@ -4725,7 +4725,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 201,
+   "execution_count": 197,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4741,7 +4741,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 202,
+   "execution_count": 198,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4753,7 +4753,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 203,
+   "execution_count": 199,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4762,7 +4762,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 204,
+   "execution_count": 200,
    "metadata": {},
    "outputs": [
     {
@@ -4782,7 +4782,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 205,
+   "execution_count": 201,
    "metadata": {},
    "outputs": [
     {
@@ -4822,7 +4822,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 206,
+   "execution_count": 202,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4835,7 +4835,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 207,
+   "execution_count": 203,
    "metadata": {},
    "outputs": [
     {
@@ -4844,7 +4844,7 @@
        "<tf.Tensor: shape=(), dtype=int32, numpy=15>"
       ]
      },
-     "execution_count": 207,
+     "execution_count": 203,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4855,7 +4855,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 208,
+   "execution_count": 204,
    "metadata": {},
    "outputs": [
     {
@@ -4885,7 +4885,7 @@
        " <tf.Operation 'Identity' type=Identity>]"
       ]
      },
-     "execution_count": 208,
+     "execution_count": 204,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4903,7 +4903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 209,
+   "execution_count": 205,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4918,7 +4918,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 210,
+   "execution_count": 206,
    "metadata": {},
    "outputs": [
     {
@@ -4927,7 +4927,7 @@
        "<tf.Tensor: shape=(), dtype=int32, numpy=15>"
       ]
      },
-     "execution_count": 210,
+     "execution_count": 206,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4938,7 +4938,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 211,
+   "execution_count": 207,
    "metadata": {},
    "outputs": [
     {
@@ -4952,7 +4952,7 @@
        " <tf.Operation 'Identity' type=Identity>]"
       ]
      },
-     "execution_count": 211,
+     "execution_count": 207,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4970,7 +4970,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 212,
+   "execution_count": 208,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4983,7 +4983,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 213,
+   "execution_count": 209,
    "metadata": {},
    "outputs": [
     {
@@ -5009,7 +5009,7 @@
        " <tf.Operation 'Identity' type=Identity>]"
       ]
      },
-     "execution_count": 213,
+     "execution_count": 209,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5027,7 +5027,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 214,
+   "execution_count": 210,
    "metadata": {},
    "outputs": [
     {
@@ -5036,7 +5036,7 @@
        "<tf.Tensor: shape=(), dtype=int32, numpy=2>"
       ]
      },
-     "execution_count": 214,
+     "execution_count": 210,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5054,7 +5054,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 215,
+   "execution_count": 211,
    "metadata": {},
    "outputs": [
     {
@@ -5064,7 +5064,7 @@
        "type: DT_RESOURCE"
       ]
      },
-     "execution_count": 215,
+     "execution_count": 211,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5076,7 +5076,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 216,
+   "execution_count": 212,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5089,7 +5089,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 217,
+   "execution_count": 213,
    "metadata": {},
    "outputs": [
     {
@@ -5098,7 +5098,7 @@
        "<tf.Tensor: shape=(), dtype=int32, numpy=2>"
       ]
      },
-     "execution_count": 217,
+     "execution_count": 213,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5110,7 +5110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 218,
+   "execution_count": 214,
    "metadata": {},
    "outputs": [
     {
@@ -5120,7 +5120,7 @@
        "type: DT_RESOURCE"
       ]
      },
-     "execution_count": 218,
+     "execution_count": 214,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5132,7 +5132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 219,
+   "execution_count": 215,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5147,7 +5147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 220,
+   "execution_count": 216,
    "metadata": {},
    "outputs": [
     {
@@ -5156,7 +5156,7 @@
        "<tf.Tensor: shape=(), dtype=int32, numpy=2>"
       ]
      },
-     "execution_count": 220,
+     "execution_count": 216,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5169,7 +5169,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 221,
+   "execution_count": 217,
    "metadata": {
     "scrolled": true
    },
@@ -5220,7 +5220,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 222,
+   "execution_count": 218,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5235,7 +5235,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 223,
+   "execution_count": 219,
    "metadata": {},
    "outputs": [
     {
@@ -5300,7 +5300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 224,
+   "execution_count": 220,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5312,7 +5312,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 225,
+   "execution_count": 221,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5324,7 +5324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 226,
+   "execution_count": 222,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5352,7 +5352,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 227,
+   "execution_count": 223,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5361,7 +5361,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 228,
+   "execution_count": 224,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5386,7 +5386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 229,
+   "execution_count": 225,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5395,7 +5395,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 230,
+   "execution_count": 226,
    "metadata": {},
    "outputs": [
     {
@@ -5433,7 +5433,7 @@
        "[0.4203692376613617, 0.4711270332336426]"
       ]
      },
-     "execution_count": 230,
+     "execution_count": 226,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5453,7 +5453,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 231,
+   "execution_count": 227,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5469,7 +5469,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 235,
+   "execution_count": 228,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5478,7 +5478,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 236,
+   "execution_count": 229,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5487,7 +5487,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 237,
+   "execution_count": 230,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5496,7 +5496,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 238,
+   "execution_count": 231,
    "metadata": {},
    "outputs": [
     {
@@ -5547,7 +5547,7 @@
        "[5.545090198516846, 2.0603599548339844]"
       ]
      },
-     "execution_count": 238,
+     "execution_count": 231,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5636,7 +5636,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 242,
+   "execution_count": 232,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5693,7 +5693,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 243,
+   "execution_count": 233,
    "metadata": {},
    "outputs": [
     {
@@ -5702,7 +5702,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=3.9782837e-08>"
       ]
      },
-     "execution_count": 243,
+     "execution_count": 233,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5726,7 +5726,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 244,
+   "execution_count": 234,
    "metadata": {},
    "outputs": [
     {
@@ -5735,7 +5735,7 @@
        "<tf.Tensor: shape=(), dtype=float32, numpy=1.764704e-08>"
       ]
      },
-     "execution_count": 244,
+     "execution_count": 234,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5777,7 +5777,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 245,
+   "execution_count": 235,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5790,7 +5790,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 246,
+   "execution_count": 236,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5799,7 +5799,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 247,
+   "execution_count": 237,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5812,7 +5812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 248,
+   "execution_count": 238,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5827,7 +5827,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 249,
+   "execution_count": 239,
    "metadata": {},
    "outputs": [
     {
@@ -5956,7 +5956,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 250,
+   "execution_count": 240,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5965,7 +5965,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 251,
+   "execution_count": 241,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5983,7 +5983,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 252,
+   "execution_count": 242,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -5993,7 +5993,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 253,
+   "execution_count": 243,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -6007,7 +6007,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 254,
+   "execution_count": 244,
    "metadata": {},
    "outputs": [
     {
@@ -6139,7 +6139,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -6153,7 +6153,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.9.10"
   }
  },
  "nbformat": 4,