From 34998902270c6d6bab73430d72a8c2504657c0db Mon Sep 17 00:00:00 2001
From: ASEM000 <mahmoudasem00@gmail.com>
Date: Sat, 2 Dec 2023 15:24:52 +0900
Subject: [PATCH] Update train_bilstm.ipynb

---
 docs/notebooks/train_bilstm.ipynb | 26 +++++++++++++-------------
 1 file changed, 13 insertions(+), 13 deletions(-)

diff --git a/docs/notebooks/train_bilstm.ipynb b/docs/notebooks/train_bilstm.ipynb
index 9c900a8..f9fc894 100644
--- a/docs/notebooks/train_bilstm.ipynb
+++ b/docs/notebooks/train_bilstm.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -26,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -54,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,7 +79,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -99,15 +99,15 @@
     "\n",
     "    def __call__(self, input: Input) -> Input:\n",
     "        # initialize the states of the cells\n",
-    "        (state1, state2, state3) = sk.tree_state((self.cell1, self.cell2, self.cell3))\n",
+    "        state = sk.tree_state(self)\n",
     "        # run the forward cell\n",
-    "        output1, state1 = sk.nn.scan_cell(self.cell1)(input, state1)\n",
+    "        output1, state1 = sk.nn.scan_cell(self.cell1)(input, state.cell1)\n",
     "        # run the backward cell\n",
-    "        output2, state2 = sk.nn.scan_cell(self.cell2, reverse=True)(input, state2)\n",
+    "        output2, state2 = sk.nn.scan_cell(self.cell2, reverse=True)(input, state.cell2)\n",
     "        # concatenate the outputs\n",
     "        output = jnp.concatenate((output1, output2), axis=1)\n",
     "        # run the final cell\n",
-    "        output, state3 = sk.nn.scan_cell(self.cell3)(output, state3)\n",
+    "        output, state3 = sk.nn.scan_cell(self.cell3)(output, state.cell3)\n",
     "        # return the last time step\n",
     "        return output[-1]\n",
     "\n",
@@ -130,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -171,23 +171,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Epoch: 100/100\tBatch: 100/100\tBatch loss: 2.065103e-03\tTime: 0.019\r"
+      "Epoch: 100/100\tBatch: 100/100\tBatch loss: 2.065103e-03\tTime: 0.022\r"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x28a8d2450>"
+       "<matplotlib.legend.Legend at 0x298c1dc10>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     },