diff --git a/docs/conf.py b/docs/conf.py
index f98418e..78a7796 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -136,6 +136,20 @@
 nbsphinx_codecell_lexer = "ipython"
 nbsphinx_kernel_name = "python"
 nbsphinx_timeout = 180
+# source: https://github.com/NTT123/pax/blob/main/docs/conf.py
+nbsphinx_prolog = r"""
+{% set docname = 'docs/' + env.doc2path(env.docname, base=None) %}
+
+.. only:: html
+
+    .. role:: raw-html(raw)
+        :format: html
+
+    .. nbinfo::
+
+        Open in colab:
+        :raw-html:`<a href="https://colab.research.google.com/github/asem000/serket/blob/main/{{ docname }}"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg" style="vertical-align:text-bottom"></a>`
+"""
 
 # Tell sphinx-autodoc-typehints to generate stub parameter annotations including
 # types, even if the parameters aren't explicitly documented.
diff --git a/docs/notebooks/layers_overview.ipynb b/docs/notebooks/layers_overview.ipynb
index c066ffe..fae676c 100644
--- a/docs/notebooks/layers_overview.ipynb
+++ b/docs/notebooks/layers_overview.ipynb
@@ -7,6 +7,15 @@
     "# 📙 `serket.nn` layers overview"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install git+https://github.com/ASEM000/serket --quiet"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -44,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -126,7 +135,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -167,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -176,14 +185,14 @@
        "Linear(\n",
        "  in_features=(10), \n",
        "  out_features=5, \n",
-       "  weight_init=he_normal, \n",
-       "  bias_init=ones, \n",
-       "  weight=f16[10,5](μ=0.08, σ=0.43, ∈[-1.01,0.87]), \n",
-       "  bias=f16[5](μ=1.00, σ=0.00, ∈[1.00,1.00])\n",
+       "  weight_init=glorot_uniform, \n",
+       "  bias_init=zeros, \n",
+       "  weight=f16[10,5](μ=0.07, σ=0.35, ∈[-0.63,0.60]), \n",
+       "  bias=f16[5](μ=0.00, σ=0.00, ∈[0.00,0.00])\n",
        ")"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/docs/notebooks/lazy_initialization.ipynb b/docs/notebooks/lazy_initialization.ipynb
index 468d36f..b12e26a 100644
--- a/docs/notebooks/lazy_initialization.ipynb
+++ b/docs/notebooks/lazy_initialization.ipynb
@@ -15,6 +15,15 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install git+https://github.com/ASEM000/serket --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -22,7 +31,7 @@
        "(5, 10)"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -51,7 +60,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -60,7 +69,7 @@
        "(5, 10)"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
diff --git a/docs/notebooks/mental_model.ipynb b/docs/notebooks/mental_model.ipynb
index 18a6d9b..e352c8d 100644
--- a/docs/notebooks/mental_model.ipynb
+++ b/docs/notebooks/mental_model.ipynb
@@ -19,6 +19,15 @@
    "execution_count": 1,
    "metadata": {},
    "outputs": [],
+   "source": [
+    "!pip install git+https://github.com/ASEM000/serket --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import jax\n",
     "import functools as ft\n",
@@ -62,7 +71,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
diff --git a/docs/notebooks/regularization.ipynb b/docs/notebooks/regularization.ipynb
index 2c66a36..79d93ee 100644
--- a/docs/notebooks/regularization.ipynb
+++ b/docs/notebooks/regularization.ipynb
@@ -20,6 +20,15 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install git+https://github.com/ASEM000/serket --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -67,7 +76,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
diff --git a/docs/notebooks/train_bilstm.ipynb b/docs/notebooks/train_bilstm.ipynb
index 569d128..d6a49d2 100644
--- a/docs/notebooks/train_bilstm.ipynb
+++ b/docs/notebooks/train_bilstm.ipynb
@@ -7,6 +7,15 @@
     "# 🚆 Train bidirectional-`LSTM`"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install git+https://github.com/ASEM000/serket --quiet"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -16,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -42,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -70,7 +79,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -106,7 +115,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -149,23 +158,23 @@
   },
   {
    "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: 1.485198e-03\tTime: 0.018\r"
+      "Epoch: 100/100\tBatch: 100/100\tBatch loss: 1.485198e-03\tTime: 0.020\r"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x16d857220>"
+       "<matplotlib.legend.Legend at 0x148c532b0>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     },
diff --git a/docs/notebooks/train_eval.ipynb b/docs/notebooks/train_eval.ipynb
index 963d65c..e001463 100644
--- a/docs/notebooks/train_eval.ipynb
+++ b/docs/notebooks/train_eval.ipynb
@@ -24,6 +24,15 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install git+https://github.com/ASEM000/serket --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -35,19 +44,19 @@
       "      in_features=(1), \n",
       "      out_features=50, \n",
       "      weight_init=he_normal, \n",
-      "      bias_init=ones, \n",
-      "      weight=f32[1,50](μ=0.21, σ=1.42, ∈[-2.97,2.61]), \n",
-      "      bias=f32[50](μ=0.99, σ=0.08, ∈[0.71,1.09])\n",
+      "      bias_init=zeros, \n",
+      "      weight=f32[1,50](μ=0.20, σ=1.41, ∈[-2.92,2.53]), \n",
+      "      bias=f32[50](μ=-0.00, σ=0.01, ∈[-0.02,0.02])\n",
       "    ), \n",
-      "    Dropout(p=f32[](μ=0.12, σ=0.00, ∈[0.12,0.12])), \n",
-      "    <PjitFunction of <function jax.numpy.tanh at 0x12505b010>>, \n",
+      "    Dropout(drop_rate=f32[](μ=0.12, σ=0.00, ∈[0.12,0.12]), drop_axes=Ellipsis), \n",
+      "    <PjitFunction of <function jax.numpy.tanh at 0x117b86830>>, \n",
       "    Linear(\n",
       "      in_features=(50), \n",
       "      out_features=1, \n",
-      "      weight_init=he_normal, \n",
-      "      bias_init=ones, \n",
-      "      weight=f32[50,1](μ=-0.02, σ=0.14, ∈[-0.30,0.34]), \n",
-      "      bias=f32[1](μ=0.79, σ=0.00, ∈[0.79,0.79])\n",
+      "      weight_init=glorot_uniform, \n",
+      "      bias_init=zeros, \n",
+      "      weight=f32[50,1](μ=-0.02, σ=0.12, ∈[-0.24,0.27]), \n",
+      "      bias=f32[1](μ=-0.01, σ=0.00, ∈[-0.01,-0.01])\n",
       "    )\n",
       "  )\n",
       ")\n"
@@ -61,9 +70,9 @@
     "import jax\n",
     "\n",
     "net = sk.nn.Sequential(\n",
-    "    sk.nn.Linear(1, 50),\n",
+    "    sk.nn.Linear(1, 50, weight_init=\"he_normal\"),\n",
     "    sk.nn.Dropout(0.125),\n",
-    "    jax.numpy.tanh,\n",
+    "    jnp.tanh,\n",
     "    sk.nn.Linear(50, 1),\n",
     ")\n",
     "\n",
@@ -104,7 +113,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -117,19 +126,19 @@
       "      in_features=(1), \n",
       "      out_features=50, \n",
       "      weight_init=he_normal, \n",
-      "      bias_init=ones, \n",
-      "      weight=f32[1,50](μ=0.21, σ=1.42, ∈[-2.97,2.61]), \n",
-      "      bias=f32[50](μ=0.99, σ=0.08, ∈[0.71,1.09])\n",
+      "      bias_init=zeros, \n",
+      "      weight=f32[1,50](μ=0.20, σ=1.41, ∈[-2.92,2.53]), \n",
+      "      bias=f32[50](μ=-0.00, σ=0.01, ∈[-0.02,0.02])\n",
       "    ), \n",
       "    Identity(), \n",
-      "    <PjitFunction of <function jax.numpy.tanh at 0x12505b010>>, \n",
+      "    <PjitFunction of <function jax.numpy.tanh at 0x117b86830>>, \n",
       "    Linear(\n",
       "      in_features=(50), \n",
       "      out_features=1, \n",
-      "      weight_init=he_normal, \n",
-      "      bias_init=ones, \n",
-      "      weight=f32[50,1](μ=-0.02, σ=0.14, ∈[-0.30,0.34]), \n",
-      "      bias=f32[1](μ=0.79, σ=0.00, ∈[0.79,0.79])\n",
+      "      weight_init=glorot_uniform, \n",
+      "      bias_init=zeros, \n",
+      "      weight=f32[50,1](μ=-0.02, σ=0.12, ∈[-0.24,0.27]), \n",
+      "      bias=f32[1](μ=-0.01, σ=0.00, ∈[-0.01,-0.01])\n",
       "    )\n",
       "  )\n",
       ")\n"
@@ -143,22 +152,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x13720afe0>]"
+       "[<matplotlib.lines.Line2D at 0x17ea006d0>]"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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Oncsrr7xyRXl/f/9S3y9evBhPT88rEhyj0UhwcLDtAhdCiGoiI7eAV5YdAGB893C6NPIv4wxRafnZkHwAUg5Calzx7TDkZZQqFgGlRrkqrrXQ+dYD72DwCgavQPV+rbrgWQc8/cHDX/3q5q0mIOKG2DTBKSgoYNeuXUyePNl6TK/XEx0dTUxMTLnqmDNnDiNGjKBWrVqljm/evJnAwEBq167NbbfdxltvvUWdOnWuWkd+fj75+fnW700mUyVaI4QQjunNVXGcz8qncd1avNCvudbhOA+LWU1mknbCmd1wdg+kHS0ep/JPOvALA//GUKcx+DfmjC6IJ35KJcHsz7TB3Rl6U327N6Ems2mCk5aWhtlsJigoqNTxoKAgjhw5Uub5sbGxHDx4kDlz5pQ63r9/f+6++27Cw8M5fvw4r776KgMGDCAmJgaDwXBFPdOnT2fatGk31hghhHBA2+LT+GG3+tHU+/e0x931yr+BopzMhXBmF5zaCqe2QeIOKMi6spx3KAS3hcCWENRa/VqnKbi6lypWD4jOOcZ/1v3FtFWH6dGsLgFeMpzCXhz6Q9o5c+bQtm3bKwYkjxgxwnq/bdu2tGvXjsaNG7N582b69OlzRT2TJ09m0qRJ1u9NJhNhYWG2C1wIIewgr9DMv1YcBOCByIZ0alhb44iqoYxEiN8A8evhxG9XJjRGXwjrAvU6QWhHCL0JvIOuXtdVPNa7MasPJhN3zsTUlYeYNfKmKm6AuBabJjgBAQEYDAZSUlJKHU9JSSlz/ExOTg6LFy/mjTfeKPM6ERERBAQEEB8ff9UEx2g0yiBkIYTTmbUpnpNpOQR6G3mxv3w0VS6Koo6fObwS4n6C83GlH/esA416QINu0LCb2kOjr3yvmKtBzwf3tGPIrK38vP8cQ9on07e1jB+1B5smOG5ubnTq1IkNGzYwdOhQACwWCxs2bGDixInXPXfp0qXk5+fzwAMPlHmdpKQkLly4QEhISFWELYQQDu9YShazfzsOwBtDWuPjLgv6XVfyAdi/RE1qLp78+7jOAPW7QJNoaNIHQjpU+QDfNvV8mdAzgtm/HWfaT4fp0TRANj61A5v/hCdNmsSYMWPo3LkzXbt25aOPPiInJ8c6q2r06NHUq1eP6dOnlzpvzpw5DB069IqBw9nZ2UybNo1hw4YRHBzM8ePHeemll2jSpAn9+vWzdXOEEEJzFovC5GUHKDQrRLcMop/0CFxdVgocWAL7Fqu9NiVc3NWEpuWd0KwfeNj+o71n+jTlp31nOZNxiZkb43m5v6xTZGs2T3CGDx/O+fPnmTJlCsnJyXTo0IE1a9ZYBx4nJiai/0e2fPToUf744w/Wrl17RX0Gg4H9+/ezYMECMjIyCA0NpW/fvrz55pvyMZQQokb4dmcif566SC03A28MaS17TV3OYlbH0+ycA/Hr/p7xZHCDZv2hzd3Q5HZ1bRk78nAz8O/BrZmw8E+++P0Ed3esR9Mgb7vGUNPoFKWiay9XfyaTCV9fXzIzM/Hx0XYhIiGEqIi07HxunbGZrLwiptzRiod6hGsdkmPITYc9X6mJTcapv4/X7wrtR6iJjR16asry8IKdrI9L5eYIf76dcLMkpxVUkfdv+RBQCCGqkQ/WHCUrr4g29XwY062R1uFo78Jx2Pax+jFUydYA7r7Q8UHoNA4Cmmgb3z9MvbM1f8Snsf1EOj/uPcvQjvW0DslpSYIjhBDVxN7TGSzZdRqAaYPbYNDX4P/+z+2DP/4PDv/498dQwe2g6wRoc4+6nYEDCvP35KnbmvLBr0d56+fD3NoiUHZ8txFJcIQQohqwWBSm/ngQRYG7b6pXc9e8ObMLNr2jjrMp0bQf9HgWGkSVb48kjU3oGcGy3UkcP5/Df9Ye5Y0hbbQOySnJZhdCCFENfL8riX1JmXgZXWrmTuGpcbB4FHxxm5rc6PTQ9l54bCuMWqKuWVMNkhsANxc9bxYnNV9vP0XcOdk+yBYkwRFCCAeXeamQ99ao29s806cpgd7uZZzhRC6egmWPwv+i4MgqNbFpPxKe2g3DvoTg6tn70a1JAAPbBmNR4M1Vh6mB831sTj6iEkIIB/fR+r+4kFNA47q1as7A4vxsdYzNtplgLt4sueVguPVfEOgcPViTB7RkfVwq245fYO3hFFnPqIpJD44QQjiwo8lZLIxRpz3/e3Br3Fyc/M+2oqgrDn/SGbbMUJOb8FtgwiYY/pXTJDegDjie0FOd5v/O6jjyi8waR+RcnPyVIoQQ1ZeiKLz182HMFoV+rYPo2bSu1iHZVvJBmNsPlk2ArHPg1xCGL4LRK6Gec25S+UTvJgR6Gzl1IZd5WxO0DsepSIIjhBAOavNf59lyLA03g55/DWyldTi2U3gJ1k+Dz3vB6R3gWgv6TIEnY6HlHdVm8HBl1DK68FLxtg2fbIznfFa+xhE5D0lwhBDCARWZLbzzs7rT9ZhuDWlQxzHXdblhJ7fAp93hjw/BUgQt7oCn/oSez4NrzRhMfXfHerSv70t2fhEzfj2qdThOQxIcIYRwQEv+TOJYajZ+nq5MvLWp1uFUvfxs+OkZWHAHpB8Hr2AY/jWMWAQ+oVpHZ1d6vY4pd6o9dEt2nebgmUyNI3IOkuAIIYSDyc4v4sN16n/yT9/WFF9PJ1vp9nQszO4Ou+ar33caB0/uUHf3rqE6NfRncPtQFEUdcCzTxm+cJDhCCOFgPvvtOGnZBTSq48kDNzfUOpyqYy6EjW+pA4kvJoBPfRjzE9z5EXj4aRyc9l7s1xw3g55txy/w21/ntQ6n2pMERwghHMi5zEt8seUEAK8MaOk808LT4uHLaPj9A3XvqHYj4PGt6hRwAajTxsd0UxPad385gtkivTg3wkleOUII4Rw++PUoeYUWujbyp1/rIK3DqRoHf1BnSJ3bCx614d75cPdn0mtzFU/e2gQfdxeOJGexYs8ZrcOp1iTBEUIIB3H4rInlxW9q/xrUEl11nx5dmAerJsH3D0FBNjTsDo9vg9Z3aR2Zw/LzdOOJW5sA8J+1R8krlMX/KksSHCGEcBAf/HoERYE72oXQPsxP63BuTPoJmHM7/DlH/b7n8+qCfTVshlRljO3WiFBfd85m5rFgW4LW4VRbkuAIIYQDiD2Zzqaj53HR63ihb3Otw7kxx9bDZ70heT94+MOoH9SF+wyy/WF5uLsamFT8OzBrUzwZuQUaR1Q9SYIjhBAaUxSF94t3Cx/eJYxGAbU0jqiSFAW2/he+uRfyM6F+V3jsD2garXVk1c5dHevRItgbU14RszbFax1OtSQJjhBCaGzjkVT+PHURd1c9T/eppov6FV5S95BaN0WdJXXTaBi7CnzraR1ZtWTQ63hlgLqFw4JtpzibcUnjiKofSXCEEEJDZovC+2vURf3GdQ8nyKcabk+QeUZd2+bAUtC7wMAZcOfH4GLUOrJqrVezutwc4U+B2cLMjce0DqfakQRHCCE0tHLfGY6mZOHj7sJjtzTWOpyKO7cfvuwD5/aBZx14cAV0neDUG2Tai06n48V+6licJX8mkZCWo3FE1YskOEIIoZGCIgv/WfsXAI/1blz9tmQ4th7mDYCsc1C3JUzYBOE9tY7KqXRq6M+tzetitih8tP4vrcOpViTBEUIIjXwbm0jSxUsEehsZ1y1c63Aq5s958M196vo24bfAQ2ugthNtK+FAni+eUfXjvrMcTc7SOJrqQxIcIYTQwKUCM58Uz455qk9TPNwMGkdUTooC66fBqmdBMUP7keo0cFmV2Gba1PNlYNtgFAXrJqyibJLgCCGEBhbtOMX5rHzq1/ZgeOcwrcMpH3MRrJwIf3yoft97Mgz9H7i4aRtXDfBcdDN0Ovj1UAr7kzK0DqdakARHCCHsLLegiE83Hwfg6duaVo8NNQvzYOkY2PM16PQw+BPo/YoMJraTpkHe3NVBnXI/Y62MxSmPavCqEkII57Iw5hQXcgpoWMeTu26qBuvE5Jlg0T1wZBUYjHDfV3DTg1pHVeM8G90MF72O3/86z44TF7QOx+FJgiOEEHaUnV/EZ7/93XvjanDwP8M5abDgTkjYAm7e8MAP0PIOraOqkRrU8eS+LurHmf8nM6rK5OCvLCGEcC4LtiVwMbeQiIBaDOng4BtPZiXDvIFwbi94BqgrE8s0cE1NvLUJbgY920+ks116ca5LEhwhhLATU14hn/9+AoBnopvi4si9N5ln1OQm7Sj41FOngYd20DqqGi/Uz4P7utQH4L/rZXXj67HLq2vWrFk0atQId3d3IiMjiY2NvWbZ+fPno9PpSt3c3UsvXa4oClOmTCEkJAQPDw+io6M5dkyeaCGEY5v3RwKZlwppEujFHe0cuPcmIxHmD4T04+DbAMathoBqukeWE3qidxNcDTpiTlyQsTjXYfME57vvvmPSpElMnTqV3bt30759e/r160dqauo1z/Hx8eHcuXPW26lTp0o9/v777/Pxxx8ze/ZsduzYQa1atejXrx95eXm2bo4QQlRK5qVCvvxD7b15NropBr2Dzj5KP6H23FxMgNqN1OSmdiONgxKXC/Xz4L7ipQX+u0H+ub8Wmyc4H374IRMmTGDcuHG0atWK2bNn4+npydy5c695jk6nIzg42HoLCgqyPqYoCh999BGvvfYaQ4YMoV27dixcuJCzZ8+yYsUKWzdHCCEqZd7Wk2TlFdE8yJuBbUK0DufqLhyHeYMg8zTUaQLjfgG/arJGTw3zxK1qL86249KLcy02TXAKCgrYtWsX0dHRf19Qryc6OpqYmJhrnpednU3Dhg0JCwtjyJAhHDp0yPrYyZMnSU5OLlWnr68vkZGR16wzPz8fk8lU6iaEEPaSlVfI3D9OAvBUnyboHbH35mICLBgMWWchoDmMXQ0+DvwxWg1XT3pxymTTBCctLQ2z2VyqBwYgKCiI5OTkq57TvHlz5s6dy48//sjXX3+NxWKhW7duJCUlAVjPq0id06dPx9fX13oLC5P/SIQQ9rMw5hSmvCIa163FAEfsvck4DfPvBFMSBDRTZ0t5B5V9ntDU5b04sSfTtQ7H4TjcEP6oqChGjx5Nhw4d6NWrF8uWLaNu3bp89tlnla5z8uTJZGZmWm+nT5+uwoiFEOLacvKLmFPcezPxtiaON/bGdBYW3AGZieDfGEavBK9AraMS5VDPz4N7rb04si7OP9k0wQkICMBgMJCSklLqeEpKCsHBweWqw9XVlY4dOxIfr25KV3JeReo0Go34+PiUugkhhD0s2nGK9OJVi+90tJlTWckw/46/BxSP+Ql8HLCHSVzTE70b42rQsTX+ArtOSS/O5Wya4Li5udGpUyc2bNhgPWaxWNiwYQNRUVHlqsNsNnPgwAFCQtQXXXh4OMHBwaXqNJlM7Nixo9x1CiGEPeQVmvn8d7X35sneTRxr3ZucC7BwyN9Twcf8BL7VYNsIUUr92p4Mu0ldF+eTjfEaR+NYbP5qmzRpEl988QULFiwgLi6Oxx9/nJycHMaNGwfA6NGjmTx5srX8G2+8wdq1azlx4gS7d+/mgQce4NSpUzz88MOAOsPq2Wef5a233mLlypUcOHCA0aNHExoaytChQ23dHCGEKLdvYxNJy86nnp+HY+05lWeCRcPg/BHwDoUxK8GvgdZRiUp6rFdj9DrYdPQ8B89kah2Ow3Cx9QWGDx/O+fPnmTJlCsnJyXTo0IE1a9ZYBwknJiai1/+dZ128eJEJEyaQnJxM7dq16dSpE9u2baNVq1bWMi+99BI5OTk88sgjZGRk0KNHD9asWXPFgoBCCKGV/CIzn/2mrnvzxK2NHWfPqcJL8O39cHYPeNaB0SvAP1zrqMQNaBRQizvbh/Lj3rPM2hTPpw900jokh6BTFEXROgh7M5lM+Pr6kpmZKeNxhBA28fX2U7y24iAhvu5sfrE3RheD1iGBuRAWj4Jjv4LRR/1YSrZfcApHk7Po99Hv6HSw7rlbaBLorXVINlGR928H+ZdCCCGcR6HZwqeb1R3DH70lwjGSG4sZlj+qJjcu7jDyO0lunEjzYG/6tgpCUeB/m45rHY5DkARHCCGq2E/7znIm4xIBXm6M6OoAY1sUBX55GQ7+AHoXGP41NOymdVSiik28rQkAP+47S+KFXI2j0Z4kOEIIUYUsFsXaezOuezjurg7Qe/P7DNj5BaCDuz+HprdrHZGwgXb1/bilWV3MFoXZv0svjiQ4QghRhdbHpXAsNRtvowsPRjXUOhzYNR82vaXeH/AetBmmaTjCtibeqvbifP9nEsmZNXsDaklwhBCiiiiKwqzi3psHoxri4+6qbUBxq2DVc+r9ni9A5KPaxiNsrmu4P10b+VNgtvDFlhNah6MpSXCEEKKKxBy/wL7TGRhd9DzUQ+Op16e2wQ/jQbFAxwfhtte0jUfYzZPFY3G+jU3kYk6BxtFoRxIcIYSoIv8r7r0Z3iWMAC+jdoGkHoFvR0BRHjQfCHd8BDoH2wNL2MwtTQNoFeJDboGZhTGntA5HM5LgCCFEFdiflMEf8WkY9Dom9IzQLpCsZFh0D+RlQv2uMGwOGGy+pqtwIDqdjsd6NwZg/raT5BYUaRyRNiTBEUKIKlCy9siQ9qGE+XtqE0R+Fiy6FzJPqzuD378Y3DSKRWhqYJtgGvh7cjG3kCU7T2sdjiYkwRFCiBsUn5rNr4eTAaz/OduduRCWjoXk/eAZAA98D7XqaBOL0JyLQc+EW9SexC+2nKTQbNE4IvuTBEcIIW7QF7+fQFHg9lZBNAvSYIl8RVFnS8WvBxcPGLkE/DX8mEw4hHs71SfAy40zGZdYtf+s1uHYnSQ4QghxA1JMeSzfcwZQd3XWxJYZsOcr0Onh3nlQXzZbFODuamBcd3U23+zNJ6hpW09KgiOEEDdg3tYECswWujSqTaeGte0fwIHvYWPJQn7vQ/MB9o9BOKwHbm6Il9GFoylZbDqaqnU4diUJjhBCVFJWXiGLtqvTcB+9RYPem8TtsOIJ9X7UROg6wf4xCIfm6+HKqEh1P7SSLURqCklwhBCikr6NTSQrv4jGdWtxW4tA+148/QQsHgnmfGhxB9z+hn2vL6qNh3qE42bQszPhIn8mpGsdjt1IgiOEEJVQUGRhzh8nAbX3Rq+340J6uemw6D7IvQAhHdQNNPUOsKmncEhBPu7c1bEeAJ//XnO2b5AERwghKuHHvWdIMeUT6G1kSMdQ+124qACWjIYLx8CnPoz8Dtxq2e/6olqacIs62HhdXAonzmdrHI19SIIjhBAVZLEo1o0MH+oRjtHFTr0nigI/T4KELeDmrSY33sH2ubao1poEetOnRSCKgrXn0dlJgiOEEBW0+a9U/krJxsvowsjiAZx2EfPJ39PB75kLwW3sd21R7ZUs/Pf9riTSsvM1jsb2JMERQogKmv2b2nszMrIBPu6u9rno0V9g7evq/b5vQ7O+9rmucBqR4f60r+9LfpGFr2rAJpyS4AghRAXsO51B7Ml0XPQ6xnVvZJ+LJh+EHx4GFOg0Fm5+3D7XFU5Fp9NZe3G+2n6KSwVmjSOyLUlwhBCiAkrG3gxuH0qIr4ftL5idCt+OgIJsCL8FBs4AnR1nbAmn0r91MGH+HqTnFPD97iStw7EpSXCEEKKcki7m8stBdVPNh3vaYa+nonxYPOrv3cHvXQAGO30kJpySi0HP+OLtG+ZsOYHZ4rzbN0iCI4QQ5TRvawJmi0L3JnVoFepj24spCvz0DCTFgruvOmPK09+21xQ1wr2dw/D1cCXhQi7rDidrHY7NSIIjhBDlkHmpkMWxiQBMsEfvzbaZsO9b0Bng3vkQ0NT21xQ1Qi2jCw/e3BBw7oX/JMERQohyWBybSE6BmWZBXvRqVte2F/vrV1g3Rb3ffzo0vs221xM1zuhuDXEz6NmdmMGuUxe1DscmJMERQogyFJotzN+WAMDDPSLQ2XKQb+oR+H481hlTXR+x3bVEjRXo7c6QDuoK3HOddOE/SXCEEKIMP+8/x7nMPAK8bLwtQ246fDscCrKgYXcY8IHMmBI2M76nOtj4l4PnOJ2eq3E0VU8SHCGEuA5F+XtbhrHdGtpuWwZzISwdAxcTwK8B3PcVuLjZ5lpCAC2CfejZNACLgrWH0plIgiOEENcRc+ICh86acHfVMyqyoe0u9Ou/4OTv4FoL7l8MterY7lpCFBvfQ+3F+W7naUx5hRpHU7UkwRFCiOuYs0Udn3BvpzBq17JRj8ruhRD7mXr/7s8gqLVtriPEP/RqVpemgV5k5xexZOdprcOpUnZJcGbNmkWjRo1wd3cnMjKS2NjYa5b94osv6NmzJ7Vr16Z27dpER0dfUX7s2LHodLpSt/79+9u6GUKIGubE+Ww2HEkFsN22DInbYdUk9X7vV6Hlnba5jhBXodPpeLh4LM68rQkUmS0aR1R1bJ7gfPfdd0yaNImpU6eye/du2rdvT79+/UhNTb1q+c2bN3P//fezadMmYmJiCAsLo2/fvpw5c6ZUuf79+3Pu3Dnr7dtvv7V1U4QQNcy8rQkA9GkRSERdr6q/QGYSfPcAWAqh5WC45cWqv4YQZRjSoR51arlxJuOSdaVuZ2DzBOfDDz9kwoQJjBs3jlatWjF79mw8PT2ZO3fuVcsvWrSIJ554gg4dOtCiRQu+/PJLLBYLGzZsKFXOaDQSHBxsvdWuXdvWTRFC1CAZuQV8v0vdq6dknEKVKsiFxSMh5zwEtYGhn4JeRg0I+3N3NfBglDq+7MstJ1AU59i+waavpoKCAnbt2kV0dPTfF9TriY6OJiYmplx15ObmUlhYiL9/6SXKN2/eTGBgIM2bN+fxxx/nwoUL16wjPz8fk8lU6iaEENfzbexpLhWaaRHsTVTjKh7wqyjw09Nwbh94+MOIb8Bogx4iIcrpgZsb4uaiZ19SptMs/GfTBCctLQ2z2UxQUFCp40FBQSQnl68b7OWXXyY0NLRUktS/f38WLlzIhg0beO+99/jtt98YMGAAZvPVt36fPn06vr6+1ltYWFjlGyWEcHqFZgsLiqfNju8RXvUL+22bCQeWqtsw3LcQattwdpYQ5RDgZeSuDvUAmLvVORb+c+j+0HfffZfFixezfPly3N3drcdHjBjB4MGDadu2LUOHDmXVqlXs3LmTzZs3X7WeyZMnk5mZab2dPu1cI8WFEFVr9YFzJJvUhf0Gd6jihf3i18P6qer9/u9CeM+qrV+ISnqo+KPYNQeTnWLhP5smOAEBARgMBlJSUkodT0lJITg4+Lrnzpgxg3fffZe1a9fSrl2765aNiIggICCA+Pj4qz5uNBrx8fEpdRNCiKtRFMW6dP2DN1fxwn4XjsP3D4FigY4PQtcJVVe3EDeoebA3PZqoC/8tjEnQOpwbZtMEx83NjU6dOpUaIFwyYDgqKuqa573//vu8+eabrFmzhs6dO5d5naSkJC5cuEBISEiVxC2EqLl2nbrIvqRM3Fz0jLq5QdVVnJ+lDirOy4T6XWHQf2QbBuFwSgbUL955muz8Io2juTE2/4hq0qRJfPHFFyxYsIC4uDgef/xxcnJyGDduHACjR49m8uTJ1vLvvfcer7/+OnPnzqVRo0YkJyeTnJxMdnY2ANnZ2bz44ots376dhIQENmzYwJAhQ2jSpAn9+vWzdXOEEE6uZPzBXR3qEeBlrJpKLRZY/hicPwLeITD8K3CporqFqEK9mtUlIqAWWXlF/FA8i7C6snmCM3z4cGbMmMGUKVPo0KEDe/fuZc2aNdaBx4mJiZw7d85a/tNPP6WgoIB77rmHkJAQ623GjBkAGAwG9u/fz+DBg2nWrBnjx4+nU6dObNmyBaNR/mAIISov6WIua4rXAXmoKqeG//4BHFkFBjcY/jV4X/8jeiG0otfrrItaztt6Eoul+k4Z1ynOMuG9AkwmE76+vmRmZsp4HCGE1Tur4/j89xP0aBLA1w9HVk2lR1bD4vvV+0NmQccHqqZeIWwkJ7+IqOkbMOUV8eXozkS3Cir7JDupyPu3Q8+iEkIIe8nJL+Lb2EQAHurRqGoqPX8Ulj2i3u/6qCQ3olqoZXTh/kh1/Fl1njIuCY4QQgDLdieRlVdEeEAtejcLvPEKL2XAt/dDQRY07AH93r7xOoWwk9FRjTDodWw7foG4c9VzcVxJcIQQNZ7Folj3nRoT1RC9/gZnN1nMsGwCpB8H3zC4bwEYXG88UCHspJ6fB/3bqGPFSpZNqG4kwRFC1Hi/HTvPibQcvI0u3NO5ClY63/QOHFsLLu7qoOJaATdepxB29lB3daD9j3vPkpadr3E0FScJjhCixiv5D/W+LmF4GV1urLLDK2GLOuuTwTMhtMON1SeERm5q4Ef7+r4UmC18uyNR63AqTBIcIUSNdiwliy3H0tDrYGy3RjdWWcphdb0bgJufhHb33XB8QmhFp9MxrrgX56vtpygosmgcUcVIgiOEqNHmFW+qGd0yiDB/z8pXdOmiulJxYQ6E3wK3v1E1AQqhoYFtQwj0NpKalc8vB8+VfYIDkQRHCFFjZeQWsGy3ulpryX+qlWIxww8Pw8WT4NsA7pkPhhv8qEsIB+DmoueBm9Xd7ucWD8SvLiTBEULUWN/Gniav0ELLEB9ujvCvfEUb31J3CXfxgBGLoFadqgtSCI2NjGyAm0HPvtMZ7E68qHU45SYJjhCiRioyW/iqeMfkcd0boavsxpeHVsAfH6r3h3wCIe2qJD4hHEWAl5E724cCML8a9eJIgiOEqJHWHU7hbGYe/rXcGFz8x7vCUg7DiifU+1EToe09VRegEA6kZH+q1QfOkZyZp20w5SQJjhCiRioZXDyyawPcXQ0Vr6DUoOJeED2tagMUwoG0qedL10b+FFkUvt5+SutwykUSHCFEjXPobCaxJ9Nx0eusAygr5PJBxX4N4N75MqhYOL2SXpxvYhPJKzRrG0w5SIIjhKhxSsYRDGgbQrCve8UruHxQ8fBF4HkDA5SFqCZubxVEPT8P0nMKWLn3rNbhlEkSHCFEjXIhO58f96l/nCu1sN/lg4oHz5RBxaLGcDHoeTBK7fGcvy0BRVE0juj6JMERQtQoi3eepqDIQrv6vtzUwK9iJ/9zUHG7e6s8PiEc2YguYbi76jl8zsTOBMeeMi4JjhCixig0W/gqRh0gObZbBaeGy6BiIfDzdOOujvUAmL/NsXcZlwRHCFFjrDmYTLIpjwAvI4PahZT/RIsZfphw2UrF82RQsaixxhR/tPvroRTOZFzSNpjrkARHCFFjzC+eGj4qsgFGlwpMDd/0DsSvAxd3GPG1rFQsarQWwT5ERdTB7OBTxiXBEULUCAeSMtl16iKuBh2jIhuU/8TDK2HLDPX+4JkQ0t42AQpRjYwtnjL+rQNPGZcERwhRI8wrHi8wqG0IgT7lnBqeGgfLH1Pv3/wEtLvPRtEJUb1Et1SnjGfkFvLj3jNah3NVkuAIIZxeWnY+q/adA2BseXcNv5QBi0epg4ob9YTb37RdgEJUMwa9jjHdSqaMn3LIKeOS4AghnN63OxIpMFvoEOZHhzC/sk+wWGDZI5B+HHzDZKViIa5ieOcGeLgaiDtnIvZkutbhXEESHCGEUys0W/h6x99Tw8vlt3fh2K/qoOLhX0OtANsFKEQ15evpyl03lUwZT9A2mKuQBEcI4dTWHEwmxZRPXW8jA9uWY2r4kZ/ht/fU+3f+F0I72DQ+IaqzsdYp48kkXczVNph/kARHCOHULp8a7uZSxp+883/BskfV+5GPQfsRtg1OiGquWZA33RrXwaLA19sTtQ6nFElwhBBO6/Kp4SPLmhqeZ1JXKi7Igobdoe9b9glSiGqupBdn8U7HmjIuCY4QwmmV9N4MahtCoPd1poZbLLDicbhwDHzqFQ8qdrVLjEJUd31aBlG/tuNNGZcERwjhlNKy8/mpZNfwsqaGb/kPHFkFBje47yvwCrRDhEI4B4Nex+gox5syLgmOEMIplUwNb1/W1PC/foVNb6v3B30I9TvZJT4hnMl9ndVdxh1pyrgkOEIIp1N6anjDaxe8cFzdRBMFOj8ENz1onwCFcDLqLuP1AVgQk6BtMMXskuDMmjWLRo0a4e7uTmRkJLGxsdctv3TpUlq0aIG7uztt27Zl9erVpR5XFIUpU6YQEhKCh4cH0dHRHDt2zJZNEEJUIyVTwwO8jAxqG3r1QvnZ6krF+ZkQFgn937NvkEI4mZKVjX89lMJZB9hl3OYJznfffcekSZOYOnUqu3fvpn379vTr14/U1NSrlt+2bRv3338/48ePZ8+ePQwdOpShQ4dy8OBBa5n333+fjz/+mNmzZ7Njxw5q1apFv379yMvLs3VzhBDVwIKypoYrCvz4JJyPA68guHcBuLjZN0ghnIyj7TKuU2w8GigyMpIuXbrwySefAGCxWAgLC+Opp57ilVdeuaL88OHDycnJYdWqVdZjN998Mx06dGD27NkoikJoaCjPP/88L7zwAgCZmZkEBQUxf/58Rowoe90Kk8mEr68vmZmZ+Pj4VFFLhRCO4OCZTO6Y+Qcueh3bXrnt6htr/vERrJ8KelcYuwoa3Gz3OIVwRmsOJvPY17uo7elKzOQ+uLsaqrT+irx/27QHp6CggF27dhEdHf33BfV6oqOjiYmJueo5MTExpcoD9OvXz1r+5MmTJCcnlyrj6+tLZGTkNevMz8/HZDKVutlCodnCz/vPcfBMpk3qF0KUrWRq+MBr7Rp+fCNsmKbeH/CuJDdCVKHoloHU8/PgYm4hK4tnMWrFpglOWloaZrOZoKCgUseDgoJITk6+6jnJycnXLV/ytSJ1Tp8+HV9fX+stLCysUu0py/trjvDkN7uZtSneJvULIa7vQna+9Y/q2O6Nrixw8RR8/xAoFujwAHQeb98AhXByLgY9DxZPGf/JmRMcRzF58mQyMzOtt9OnT9vkOsM6qSPI1x5O4YwDDLASoqZZvPM0BUUW2tX3peM/p4YXXoLvHoBLFyG0Iwz6D+h0msQphDMb0SWM/9zbni/HdNY0DpsmOAEBARgMBlJSUkodT0lJITg4+KrnBAcHX7d8ydeK1Gk0GvHx8Sl1swVHG2AlRE1SZLZYX3djuzVCd3nyoijw07OQvB88A9Qdwl2vs7KxEKLS/DzdGNapPkaXqh1/U1E2TXDc3Nzo1KkTGzZssB6zWCxs2LCBqKioq54TFRVVqjzAunXrrOXDw8MJDg4uVcZkMrFjx45r1mlPY0r25Ih1rD05hHB2aw+ncC4zjwAvNwa1+8eu4bFfwP7FoDPAvfPAt742QQoh7MbmH1FNmjSJL774ggULFhAXF8fjjz9OTk4O48aNA2D06NFMnjzZWv6ZZ55hzZo1/Oc//+HIkSP8+9//5s8//2TixIkA6HQ6nn32Wd566y1WrlzJgQMHGD16NKGhoQwdOtTWzSlTqQFWe7X9/FGImmT+1gQARnZtUPo/x1Pb4NfivzG3vwHht9g/OCGE3bnY+gLDhw/n/PnzTJkyheTkZDp06MCaNWusg4QTExPR6//Os7p168Y333zDa6+9xquvvkrTpk1ZsWIFbdq0sZZ56aWXyMnJ4ZFHHiEjI4MePXqwZs0a3N2173IuGWD17i9HmL8tgXs71y/dVS6EqHKHzmYSm5COi17HqJsvW7nYdBaWjAFLEbQZBlFPahekEMKubL4OjiOy9To4F3MKuHn6BvKLLCx5NIqu4f5Vfg0hxN9e+n4fS/5M4o52IXwy8ib1YFE+zB8ESTshsDU8vA7camkbqBDihjjMOjg1Ve1abtzVsR7w94qqQgjbSM8p4Mfij4PHXT41fM0ranLj7gsjvpbkRogaRhIcGykZbLzmULJD7MkhhLNavDOR/CILbev5clOD2urBPV/Dn3MBHdz9JfhHaBqjEML+JMGxkZYhPkSG+2O2KCzaIVPGhbCFIrOFr2PU19eYkqnhZ/fAqklqgVtfhWZ9NYxQCKEVSXBsaGxxL843O2TKuBC2sO5wCmcz86hTy4072oVAzgX47kEw50OzAdDzBa1DFEJoRBIcG7q9VRChvu5czC3UfMlqIZzRvOIxbiMjG+CuV+D7cZB5Gvwbw92fgV7+xAlRU8mr34bUKeONAHUDwBo4YU0Imzl81kTsyeKp4ZENYeObcPI3cPVUVyp299U6RCGEhiTBsbERXcIwuug5dNbEn6cuah2OEE6jZIZi/zbBBJ/5FbZ+pD4w5BMIaqVZXEIIxyAJjo1dPmW8ZKVVIcSNuZhTwIq9ZwB4rLUZVjyhPhA1UV3QTwhR40mCYwcyZVyIqrV452nyiyx0CXWh9ZYnoCAbGvaA6GlahyaEcBCS4NhByxAfbo6QKeNCVIUis4WvYhIAhf9z+wJd2l/gHapuommw+e4zQohqQhIcOxnbLRyQKeNC3Ki1xVPDn/VYQ/3kdaB3hfsWgleg1qEJIRyIJDh2UmqXcZkyLkSlzd+aQJT+EE8ri9QDA96FsC7aBiWEcDiS4NiJi0HP6Ch1l+P5W2XKuBCVcfBMJokJx/jEdSZ6LNB+JHQer3VYQggHJAmOHQ3vEoa7q57D50zsTJAp40JU1Fd//MWnbv+ljs4EwW3hjg9Bp9M6LCGEA5IEx478PN24q2N9AOZtPalxNEJUL2nZ+bQ7+D4d9fEUufnAfV+Bq4fWYQkhHJQkOHZWsj/V2sMpnJEp40KU256fPmWUYS0Ahnu+BP9wjSMSQjgySXDsrHmwN90a18FsUVgYk6B1OEJUC4Vn9tHz6NsAxDV/HF2zfhpHJIRwdJLgaGBcd/U/z8Wxp8ktKNI4GiEc3KUMCr55AHcK2KbrSONhb2odkRCiGpAERwO3tQikgb8nmZcKWb7njNbhCOG4LBZY/hi1chJJUgLY3/V93NxctY5KCFENSIKjAYNeZ92+QaaMC3EdWz+Cv34hX3FhYtFz3N2jndYRCSGqCUlwNHJv5/rUcjNwLDWbrfEXtA5HCMdz4jfYqH4cNbVoLOHtehDo7a5xUEKI6kISHI34uLtyTyeZMi7EVZnOwvcPgWLhe3MvFptv5aHuMmtKCFF+kuBoqORjqo1HU0lIy9E2GCEcRVEBLBkDuWmkejblX4Xj6NzQn7b1fbWOTAhRjUiCo6GIul7c2rwuigLztyVoHY4QjmHdFEiKRTH68HDeM+TjxkM9pPdGCFExkuBorGTK+Pe7ksjKK9Q4GiE0dvAH2PEpAFvbvs3+XH/q+XnQt1WQxoEJIaobSXA01rNpAE0CvcjOL2LJn0lahyOEds7/BSufBkDp/hxvxTcCYHRUQ1wM8qdKCFEx8ldDYzqdjnHdGwGwYFsCZotMGRc1UH42LHkQCrKhUU9iGj3GkeQsPFwNjOjSQOvohBDVkCQ4DuDujvXx9XAlMT2XDXEpWocjhH0pCqx6Fs4fAa9gGDaHeTFqb+awTvXw9ZSF/YQQFScJjgPwcDMwMlL9L3WuTBkXNc3OL+HAUtAZ4N55JBZ4s7440R/bTQYXCyEqRxIcBzE6qiEGvY7tJ9I5dDZT63CEsI8zu2DNZPV+9L+hYTfmb0tAUaBXs7o0CfTSNDwhRPUlCY6DCPH1YGDbEADm/pGgbTBC2ENuOiwZC5ZCaHEHdHuKrLxClv55GsA6Nk0IISrDpglOeno6o0aNwsfHBz8/P8aPH092dvZ1yz/11FM0b94cDw8PGjRowNNPP01mZukeDZ1Od8Vt8eLFtmyKXYwvXuvjp31nSc3K0zgaIWyoeBNNMhOhdjgMmQU6HUv+TCIrv4jGdWtxS9O6WkcphKjGbJrgjBo1ikOHDrFu3TpWrVrF77//ziOPPHLN8mfPnuXs2bPMmDGDgwcPMn/+fNasWcP48eOvKDtv3jzOnTtnvQ0dOtSGLbGPDmF+3NTAjwKzhUXbE7UORwjb2foRHPsVDEa4byF4+GG2KMzfpo5Be6hHOHq9TtsYhRDVmk6x0VbWcXFxtGrVip07d9K5c2cA1qxZw8CBA0lKSiI0NLRc9SxdupQHHniAnJwcXFxc1KB1OpYvX17ppMZkMuHr60tmZiY+Pj6VqsNWVu0/y8Rv9hDg5cYfL9+Gu6tB65CEqFont8DCwaBY4M6PodMYANYcPMdjX+/Gz9OVmFf64OEmv/tCiNIq8v5tsx6cmJgY/Pz8rMkNQHR0NHq9nh07dpS7npJGlCQ3JZ588kkCAgLo2rUrc+fO5Xp5Wn5+PiaTqdTNUfVvHUyorztp2QX8tO+s1uEIUbWyUqybaNL+frhptPWhOX+ovTejIhtIciOEuGE2S3CSk5MJDAwsdczFxQV/f3+Sk5PLVUdaWhpvvvnmFR9rvfHGGyxZsoR169YxbNgwnnjiCWbOnHnNeqZPn46vr6/1FhYWVvEG2YmLQW/dhHPOHyevm7gJUa2Yi+CH8ZCTCoGtYNB/QKd+DLXvdAY7Ey7iatAxOqqRtnEKIZxChROcV1555aqDfC+/HTly5IYDM5lMDBo0iFatWvHvf/+71GOvv/463bt3p2PHjrz88su89NJLfPDBB9esa/LkyWRmZlpvp0+fvuH4bGlElwZ4uBo4kpzFtuMXtA5HiKqxeTokbAE3L3XcjVst60MlvTd3tAslyMddqwiFEE7EpewipT3//POMHTv2umUiIiIIDg4mNTW11PGioiLS09MJDg6+7vlZWVn0798fb29vli9fjqvr9VcyjYyM5M033yQ/Px+j0XjF40aj8arHHZWvpyv3da7PgphTfLnlBN2bBGgdkhA35tg62DJDvT/4Ywhoan3oXOYlVh84B/w9k1AIIW5UhROcunXrUrdu2dM3o6KiyMjIYNeuXXTq1AmAjRs3YrFYiIyMvOZ5JpOJfv36YTQaWblyJe7uZf83t3fvXmrXrl2tkpiyjOsezsLtp9h09DzxqVk0CfTWOiQhKiczCZYVf8zc5WFoM6zUwwu2naLIotA13J829Xw1CFAI4YxsNganZcuW9O/fnwkTJhAbG8vWrVuZOHEiI0aMsM6gOnPmDC1atCA2NhZQk5u+ffuSk5PDnDlzMJlMJCcnk5ycjNlsBuCnn37iyy+/5ODBg8THx/Ppp5/yzjvv8NRTT9mqKZpoFFCL21sGATBHFv4T1VVRASwdC5fSIaQD9Hun1MO5BUV8G6suiSC9N0KIqlThHpyKWLRoERMnTqRPnz7o9XqGDRvGxx9/bH28sLCQo0ePkpubC8Du3butM6yaNGlSqq6TJ0/SqFEjXF1dmTVrFs899xyKotCkSRM+/PBDJkyYYMumaOLhnhGsPZzCst1JvNC3GXW8nKeHStQQG6ZB0k4w+sK988Gl9O/wD7uSyLxUSAN/T6KLE3ohhKgKNlsHx5E58jo4l1MUhSGztrI/KZNJtzfj6T5Nyz5JCEcRtwq+G6XeH74IWt5R6mGzRaHPfzaTcCGXf9/ZirHdpQdHCHF9DrEOjrhxOp3O2m2/MCaBvEKzxhEJUU4XE2DFE+r9m5+8IrkBWHc4hYQLufi4u3BvZ8ddukEIUT1JguPgBrYNIaR44b+Ve2XhP1ENFOWr427yM6F+F7h92lWLfbnlBACjbm5ILaNNPy0XQtRAkuA4OFeDnrHFC/99+ccJWfhPOL61r8PZPeBRG+6ZB4Yrl3nYk3iRP0+pC/uV/H4LIURVkgSnGhjRtQGebgb+Ssnm92NpWocjxLUdWgGxn6n37/oM/K7+0dOXW9SF/Qa3rycL+wkhbEISnGrA18OV+4rHKJR06wvhcNJPwMri5Rq6PwPN+l212On0XH45qC7s93BPGVgshLANSXCqifE9wtHrYMuxNA6dzdQ6HCFKK8wrHndjgrCb4bbXr1l07taTWBTo2TSAliGOO4tRCFG9SYJTTYT5ezKwbQjwd/e+EA5j7b/g3D7wrAP3zL3quBuAzNxCvtup7gX3cM8Ie0YohKhhJMGpRh65RX1D+GnfWc5mXNI4GiGKHVwGO79U79/1OfjWu2bRb2ITyS0w0zzIm1uayh5rQgjbkQSnGmlX34+bI/wpsijM2yq9OMIBXDgOK59W7/eYBE2jr1m0oMjCgm0JAIzvGY5Op7NDgEKImkoSnGrm0VsaA/Bt7GlMeYUaRyNqtJJxNwVZ0KAb3Pqv6xZfue8syaY86nobGdIh1D4xCiFqLElwqplezerSNNCL7Pwivt2RqHU4oiZb+y9I3l887mYOGK69WJ/FovD578cBeKh7OEYXg72iFELUUJLgVDN6vY4JxWNx5m1NoKDIonFEoka6fNzN3Z+Dz/V7ZDb/lcpfKdl4GV0YGdnADgEKIWo6SXCqoSEdQgn0NpJsyuOnfbJ9g7Czy8fd9Hwemlx73E2J2b+p6zeNjGyAr8fVZ1gJIURVkgSnGjK6GBjbvREAX2yR7RuEHf1z3E3vV8s8ZU/iRWJPpuNq0DGu+PdWCCFsTRKcampU14bUcjNwJDmLzX+d1zocUVNUYNxNic9/V3tvhnSoR4ivh60jFEIIQBKcasvX05X7u6pjGT7dfFzjaESNUMFxNwAn03JYcygZ+HsdJyGEsAdJcKqx8T3DcTXoiD2Zzq5TF7UORzizSoy7gZKPUOG2FoE0C/K2YYBCCFGaJDjVWIivB0M7qKvGzv5NenGEjVRi3A3A+ax8vt+VBMCj0nsjhLAzSXCquUd7RaDTwbrDKcSnZmkdjnBGa1+r8LgbgPnbTlJQZKFDmB9dw/1tHKQQQpQmCU411yTQm9tbBgF/T8UVosocWg47v1Dv31W+cTcAWXmFLIw5BcBjvSJkWwYhhN1JguMEHuutbt/w494zsgmnqDoXjsOPT6n3y9hn6p++3p5IVl4RjevWom+rYBsFKIQQ1yYJjhO4qUFtIsP9KTQrzPlDNuEUVaDUuJuoMveZulxeodn6e/h47ybo9dJ7I4SwP0lwnMTjvUs24UwkI7dA42hEtXf5uJth5R93A7B0VxJp2fnU8/OQTTWFEJqRBMdJ9GpWl5YhPuQWmK1jH4SolH+Ou/GtV+5Ti8wW66aaE3qG42qQPzFCCG3IXx8nodPpeKyXOhV37taT5OQXaRyRqJZuYNwNwKr95zidfok6tdwY3kU21RRCaEcSHCdyR7tQGtXxJCO3kG92JGodjqhuCvNg6ZhKjbsBsFgU66raD/UIx8PNYIsohRCiXCTBcSIGvc46FufzLSfIKzRrHJGoVn59FZIPFK93M7dC424ANh5J5WhKFl5GFx64uaGNghRCiPKRBMfJ3NWxPqG+7pzPymfpn6e1DkdUFwd/gD/nALpy7zN1OUVR+N/meAAeuLkhvh6uNghSCCHKTxIcJ+PmoufRXmovzuzfTlBotmgckXB4afGV2mfqcjEnLrA7MQM3Fz0P9WhUtfEJIUQlSILjhIZ3CSPAy8iZjEus2HNG63CEIyu8VLzeTTY07AG9J1eqmo83HAPg/i5hBHq7V2GAQghROZLgOCF3VwMP9wwH4NPNxzFbFI0jEg7rl5ch5QB4BsCwLys87gZgZ0I620+k42rQWXsPhRBCazZNcNLT0xk1ahQ+Pj74+fkxfvx4srOzr3tO79690el0pW6PPfZYqTKJiYkMGjQIT09PAgMDefHFFykqkmnRlysZB3EiLYfVB85pHY5wRPsWw+4FgA6GfQE+IZWqpqT35p5OYYT6eVRhgEIIUXk2TXBGjRrFoUOHWLduHatWreL333/nkUceKfO8CRMmcO7cOevt/ffftz5mNpsZNGgQBQUFbNu2jQULFjB//nymTJliy6ZUO15GF8Z1bwTArE3xKIr04ojLpB6BVc+p93u/Ao1vq1Q1exIvsuVYGga9jid6S++NEMJx2CzBiYuLY82aNXz55ZdERkbSo0cPZs6cyeLFizl79ux1z/X09CQ4ONh68/HxsT62du1aDh8+zNdff02HDh0YMGAAb775JrNmzaKgQLYouNzYbo3wMrpwJDmLdYdTtA5HOIqCHFgyGgpzIaI33PJipauauVGdOXVXx3qE+XtWUYBCCHHjbJbgxMTE4OfnR+fOna3HoqOj0ev17Nix47rnLlq0iICAANq0acPkyZPJzc0tVW/btm0JCgqyHuvXrx8mk4lDhw5dtb78/HxMJlOpW03g5+nGmG7qeiQfrT8mvTgCFEXtuUk7Cl7BcPeXoK/cgnwHz2Sy8Ugqeh08eWuTKg5UCCFujM0SnOTkZAIDA0sdc3Fxwd/fn+Tk5GueN3LkSL7++ms2bdrE5MmT+eqrr3jggQdK1Xt5cgNYv79WvdOnT8fX19d6CwsLq2yzqp2He0RQy83A4XMm6cUR6pib/d+BzgD3zgOvupWuauZGdezN4PahhAfUqqoIhRCiSlQ4wXnllVeuGAT8z9uRI0cqHdAjjzxCv379aNu2LaNGjWLhwoUsX76c48ePV7rOyZMnk5mZab2dPl1zFsCrXcuNMd0aAfDfDdKLU6Od3QurX1Lv95kCDbtVuqq4cyZ+PZSCTgcTb5PeGyGE46nwnNDnn3+esWPHXrdMREQEwcHBpKamljpeVFREeno6wcHB5b5eZGQkAPHx8TRu3Jjg4GBiY2NLlUlJUXsmrlWv0WjEaDSW+5rO5uGeESzYlsChsybWx6Vye6ugsk8SzuXSRXXcjTkfmvWHbk/fUHWfFI+9GdgmhCaB3lURoRBCVKkKJzh169albt2yu7WjoqLIyMhg165ddOrUCYCNGzdisVisSUt57N27F4CQkBBrvW+//TapqanWj8DWrVuHj48PrVq1qmBragb/Wm6M7taITzcf578b/iK6ZSA6nU7rsIS9WCyw4gnIOAV+DeGu2aCv/KfTcedM/Fy89MBTfaT3RgjhmGw2Bqdly5b079+fCRMmEBsby9atW5k4cSIjRowgNFTd5+bMmTO0aNHC2iNz/Phx3nzzTXbt2kVCQgIrV65k9OjR3HLLLbRr1w6Avn370qpVKx588EH27dvHr7/+ymuvvcaTTz5Zo3tpyjKhZwSebgYOnjGxIS617BOE89j2Xzi6GgxGuG8heNS+oeo+Wv8XAIPahdAi2KeM0kIIoQ2broOzaNEiWrRoQZ8+fRg4cCA9evTg888/tz5eWFjI0aNHrbOk3NzcWL9+PX379qVFixY8//zzDBs2jJ9++sl6jsFgYNWqVRgMBqKionjggQcYPXo0b7zxhi2bUu35y1icmunkFthQ/NoY8B6Edrih6g6eybSOvXm2T9Mbj08IIWxEp9TAdzqTyYSvry+ZmZml1thxduk5BfR4byO5BWbmjOlMn5YyFsepZSXD7J6Qkwrt74ehn8INfjT58IKdrI9LZUiHUP47omMVBSqEEOVTkfdv2YuqBvGv5cboqEYA/N/6v6QXx5mZC2HpODW5CWwFgz684eRm3+kM1sep6948Lb03QggHJwlODfPILRF4GV04eMbEmoPXXo9IVHPrpkLiNjD6wH1fgduNrzL8f8Vjb4Z2rEfjul43XJ8QQtiSJDg1jH8tNx7qoe40/p91f8lO487o4A+wfZZ6/67ZEHDjM512nbrI5qPnMeh1PH2b9N4IIRyfJDg10MM9w/H1cCU+NZsf957ROhxRlVLj4Men1Ps9noMWg6qk2pKZU8NuqkcjWbVYCFENSIJTA/m4u/JYL3Xn54/WH6PQbNE4IlEl8kzw3QNQmAPhveDW16qk2h0nLrDlWBoueh1PSe+NEKKakASnhhrTrSEBXkYS03NZ8mfN2brCaSkK/PgEXIgHn3pwz1wwVHgdz6tUq/D+r0cBuK9LmOwYLoSoNiTBqaE83VyYeKvai/PxhmPkFZo1jkjckC3/gbifQO+qDiquFVAl1W6IS2XXqYu4u+p5RmZOCSGqEUlwarD7IxsQ6utOiimfr7ef0jocUVnH1sHGt9T7g2ZA/U5VUq3ZovBBce/NuO7hBPm4V0m9QghhD5Lg1GBGF4N1PZP/bT5Odn6RxhGJCrtwHH4YDyjQaRx0GltlVf+49wxHU7LwcXfhsVsaV1m9QghhD5Lg1HDDOtUnPKAW6TkFfPH7Ca3DERWRnw2LR0FeJtTvqm7FUEUKiix8uE6dOfVY78b4erpWWd1CCGEPkuDUcK4GPS/0bQ7AF1tOkJqVp3FEolxKBhWfjwOvYBj+FbhU3Waz38YmknTxEoHeRsZ1C6+yeoUQwl4kwREMbBtM+zA/cgvMfLzhmNbhiPL440M4/GPxoOKF4B1cZVXn5Bcxc6P6e/B0n6Z4uBmqrG4hhLAXSXAEOp2OyQNaAPBt7GmOn8/WOCJxXUdWw4Y31fsD34cGkVVa/dw/TpKWXUDDOp4M7xJWpXULIYS9SIIjALg5og59WgSqM2fWHNU6HHEtqXGwbAKgQJeHofNDVVr9+ax8Zv92HIDn+zbH1SB/IoQQ1ZP89RJWLw9ogV4Haw4ls+vURa3DEf+Umw7fjoCCbGjUE/q/W+WX+L/1f5FTYKZ9fV/uaBtS5fULIYS9SIIjrJoFeXNvJ/UjiXd/iUNRZCNOh2EuhCWj4WIC+DWEexeAoWpnNh1LyWJxbCIA/xrUCr1eV6X1CyGEPUmCI0p57vZmuLvq2ZlwkXWHU7QOR5T49VVI2AJuXnD/YqhVp8ov8c7qOCwK9GsdRNdw/yqvXwgh7EkSHFFKsK8743uo04LfXXNENuJ0BLFfQOzn6v27P4egVlV+iT+OpbHp6Hlc9DpeGdCyyusXQgh7kwRHXOGxXo0J8HLjxPkcFsbIFg6aOrYefnlJvd9nCrQYVOWXMFsU3vr5MAAPRjUkPKBWlV9DCCHsTRIccQVvd1fr4n//Xf8X6TkFGkdUQ6UchqVjQbFA+5HQY5JNLvPDriSOJKtbMjx9m2yoKYRwDpLgiKu6t3MYrUJ8MOUV8eE6mTZud9mp8M1wKMiCht3hzv+CruoH/eYWFDFjrfr8PnVbU2rXcqvyawghhBYkwRFXZdDrmHKnOtbjmx2JHEk2aRxRDVJ4Cb69HzITwT8Chn8NLrZJPP636TipWfmE+XswultDm1xDCCG0IAmOuKabI+owoE0wFgXeXHVYpo3bg8UCyx+DM3+Cux+MXAqetpnRdOpCDp8Xb7D6r4GtMLrIlgxCCOchCY64rlcHtsTNRc/W+Asybdwe1r4Gh1eoe0wN/woCmtjsUm+uOkyB2ULPpgH0ax1ks+sIIYQWJMER1xXm78nDxdPG314dR36RWeOInFjMLNg+S70/9FMIv8Vml9p0JJX1cam46HVMvbM1OhuM7xFCCC1JgiPK9MStTajrbeTUhVy+3HJS63Cc08Fl6mJ+ANHToN29NrtUfpGZaT8dAmBc90Y0CfSy2bWEEEIrkuCIMnkZXXh1oLrb+MyNxzidnqtxRE4mYSssf1S93/UR6P6MTS8354+TJFzIpa63kaf7yLRwIYRzkgRHlMvQDvWIDPcnr9DCtJ8Oax2O80g5BIvvB3MBtLhD3UDThh8XJWfm8cnGeABe6d8Cb/eq3c9KCCEchSQ4olx0Oh1vDW2Di17H+rgUGXBcFdJPwld3QV4mhEXCsC9Bb9uZTG+vjiO3wMxNDfy4q2M9m15LCCG0JAmOKLemQd5MuCUCgH+vPERuQZHGEVVjWcnw1VDIToHA1jDyO3D1sOklf/vrPD/tO4tOB9MGt5HdwoUQTk0SHFEhT93WhHp+HpzJuGT9qENU0KWLas/NxQSo3QgeXAYetW17yQIzr604AMCYqEa0re9r0+sJIYTWbJrgpKenM2rUKHx8fPDz82P8+PFkZ2dfs3xCQgI6ne6qt6VLl1rLXe3xxYsX27IpopinmwtTi1c4/mLLCeJTszSOqJopyIFF90HqYfAKhgdXgHewzS/73w3HOJ1+iRBfd17o19zm1xNCCK3ZNMEZNWoUhw4dYt26daxatYrff/+dRx555Jrlw8LCOHfuXKnbtGnT8PLyYsCAAaXKzps3r1S5oUOH2rIp4jK3twqiT4tACs0Kr604KCscl1dhHiweBUmx6irFDy4H/3CbXzbunIkvtqgrFr8xpA1eRhebX1MIIbRms790cXFxrFmzhp07d9K5c2cAZs6cycCBA5kxYwahoaFXnGMwGAgOLv3f7PLly7nvvvvw8iq9Voefn98VZYV96HQ6/j24NVuPp7H9RDrfxp5mZGQDrcNybEX58N0oOLEJXGvBqKUQ1MrmlzVbFCYvO4DZotC/dTC3t5IVi4UQNYPNenBiYmLw8/OzJjcA0dHR6PV6duzYUa46du3axd69exk/fvwVjz355JMEBATQtWtX5s6de91ehPz8fEwmU6mbuDFh/p680Ff9qOOd1XGcy7ykcUQOrKgAloyG+PXg4gGjlkBYV7tcetGOU+w9nYG30YV/D25tl2sKIYQjsFmCk5ycTGBgYKljLi4u+Pv7k5ycXK465syZQ8uWLenWrVup42+88QZLlixh3bp1DBs2jCeeeIKZM2des57p06fj6+trvYWFhVW8QeIK47qH07GBH9n5Rby67IB8VHU15kL4fhz8tQZc3GHkYmjUwy6XTs7M4/01RwF4qX9zgn3d7XJdIYRwBBVOcF555ZVrDgQuuR05cuSGA7t06RLffPPNVXtvXn/9dbp3707Hjh15+eWXeemll/jggw+uWdfkyZPJzMy03k6fPn3D8Qkw6HV8cE873Ax6Nh09z4q9Z7QOybGYi+CHh+HIKjC4wYhFENHbLpdWFIVXlu0nO7+Ijg38GBXZ0C7XFUIIR1HhMTjPP/88Y8eOvW6ZiIgIgoODSU1NLXW8qKiI9PT0co2d+f7778nNzWX06NFllo2MjOTNN98kPz8fo9F4xeNGo/Gqx8WNaxLozdN9mjBj7V9M++kwPZrUpa63/KwpyofvH1KTG70rDF8ETaLtdvklf55m89HzuLnoeX9YO1nzRghR41Q4walbty5169Yts1xUVBQZGRns2rWLTp06AbBx40YsFguRkZFlnj9nzhwGDx5crmvt3buX2rVrSxKjkUd7NWb1gWQOnzMxdeVB/jeqk9YhaavwEnz3gDrmxuAG9y2EZn3tdvmki7m8uSoOgBf6NqNpkLfdri2EEI7CZmNwWrZsSf/+/ZkwYQKxsbFs3bqViRMnMmLECOsMqjNnztCiRQtiY2NLnRsfH8/vv//Oww8/fEW9P/30E19++SUHDx4kPj6eTz/9lHfeeYennnrKVk0RZXA16Hn/nnYY9DpWH0jm5/3ntA5JO/lZsOjevwcUj/wOmg8o+7wqYrEovPS9+tFU54a1Gd8jwm7XFkIIR2LTdXAWLVpEixYt6NOnDwMHDqRHjx58/vnn1scLCws5evQoubmld6eeO3cu9evXp2/fK//rdXV1ZdasWURFRdGhQwc+++wzPvzwQ6ZOnWrLpogytKnnyxO9GwPw6vIDJGfmaRyRBkpWKE7YAm7e6grFjW+zawhfbT/FtuMX8HA1MOPe9hjkoykhRA2lU2rg1BeTyYSvry+ZmZn4+PhoHY7TKCiyMOzTbRw4k0n3JnX46qHImjP2w3RO7blJOVC8iN8yqGffj+pOpuUw8L9buFRoZtrg1ozp1siu1xdCCFuryPu37EUlqoybi56PRnTAw9XA1vgLzN16UuuQ7OP8UZhzu5rc1AqEsT/bPbkpMlt4Yek+LhWaiYqow4M3y6wpIUTNJgmOqFKN63rx2h0tAXh/zVHizjn5ooqnYmBOX8g8DXWawMPrILiN3cP474Zj7Dp1ES+jC+/fI7OmhBBCEpyqlHNB/ZgiYavWkWhqZNcGRLcMpMBs4dnFe8krNGsdkm0cXgkLh0BeBtTvAg+tVXcHt7Nt8Wl8sknd2f2du9sS5u9p9xiEEMLRSIJTlWJmwrG1MH8gLBgMidu1jkgTOp2Od4e1I8DLjaMpWbz7y40v/OhQFAW2/lfdfsGcD80HweiVUKuO3UNJy87nme/2oigwvHMYg9tfucebEELURJLgVKUuD0Pnh9SF3U7+BnP7qbNqTu/UOjK7C/Ay8sE97QGYvy2BNQedZOp44SVY/iismwIo0Hk8DP8K3Ozfa2KxKDy/ZB/ns/JpEugle00JIcRlJMGpSr714Y7/g6d3w01jQO8CxzfCnGg10Uks3yajzuLWFoFM6BkOwAtL93PifLbGEd0g01mYNxD2fwc6Awz4AAb9B/QGTcL5YssJfvvrPEYXPbNG3oSHmzZxCCGEI5IExxb8GsDgj+GpXdDxAfXN8PhGmNtXHbNxKkbrCO3mpf4t6NKoNtn5RTz+9W5yC4q0DqlyTu+Ez2+Fs7vBozY8uBwiHwGdNoN5dyde5INf1Y00p97ZmubBslqxEEJcThIcW6rdCIbMUhOdm0arPTonNsO8/jD/Dji+SR3P4cRcDXo+GXkTAV5GjqZk8a/lB6vXruOKAjH/g3kDIDsZ6raECZsgopdmIaWa8nj8610UWRQGtQ3h/q5hmsUihBCOShIce/APh8Ez4ek90GmcOkYnYQt8NRS+7ANHVoPFonWUNhPk484nIzti0OtYvucMi3Ykah1S+eSmw+KR8OtksBRCyzvVaeD+4ZqFlF9k5rGvd5FiUsfdvDusLTqNepGEEMKRSYJjT34N4M6P4Jm9EPkYuLjDmV2w+H6Y3QP2fQfmQq2jtImbI+rwUr/mALzx02H2ns7QNqCyJO6A2T3h6Gp1w8yBM+C+r8Co3UdBiqIwZcUhdidm4OPuwhejO+Pt7qpZPEII4cgkwdGCb30Y8B48exB6PKfuW5R6CJY/Ah93hO2zoSBH6yir3CO3RNC3VRAFZgsTFv7JmYxLWod0JXMhbH5X/UjKlAT+EfDweug6QbPxNiW+2n6K7/48jV4HH9/fkfCAWprGI4QQjkz2onKEvaguXYSdc2DHbMg5rx7zqA1dJqhTz72DtI2vCmXlFXLv7BiOJGfRPMib7x+PcpxeiOQDsOJx9StAm2Fwx0fgrv3vSMzxCzw4ZwdFFoXJA1rwaK/GWockhBB2V5H3b0lwHCHBKVF4CfZ9C1s/hovF+zgZ3KDtvXDzE5psAWALZzIuMXTWVs5n5XNLs7rMHdMZF4OGnYnmQtjyIfz+PliK1ORy4Aw1wXGA8S0nzmdzz+wY0nMKGNw+lP+O6CDjboQQNZIkOGVw2ASnhMUMcT/B9v/B6cvWzgm/RR2706y/ZmuvVJX9SRnc91kMeYUWRkU24K2hbbR5007cAauf/7vXpsUdMOhDh+k1SzXlcfen20i6eIm29XxZ8miUrHcjhKixJMEpg8MnOJdL+hNiZsHhH0Ep3tPJN0xdMfmm0VArQNv4bsCvh5J57OtdKAq8NqglD/eMsN/Fs5Jh3VTYv1j93qO2unBf23scotcGwJRXyPDPthN3zkTDOp58/1g36nobtQ5LCCE0IwlOGapVglMi4zTs/AJ2fwWX0tVjBiO0vgs6jYEGUQ7zxlwRX245wVs/x6HTwYx72jOsU33bXrCoAGI/g83vQUEWoFMXY+wzFbzq2vbaFZBXaGbsvFi2n0gnwMvID49H0bCODCoWQtRskuCUoVomOCUKL8Gh5RD7OZzd8/fxOk3VHp0OI6tVr46iKEz76TDztyWg18F/R3TkTltsGGkuUntrfnsPMorX4anXCQZ+oH51IGaLwlPf7mb1gWS8jC4sfuRm2tTz1TosIYTQnCQ4ZajWCc7lknbBrnlwcBkUFk8r17tCs37Qbrj61cXxP9KwWBReXX6AxTtPY9Dr+HTUTfRtHVxFlZvVn8/m6ZB+XD3mFQR9pkD7kaB3rJUSLv9ZuBn0zB/XhW5Nqk/CKoQQtiQJThmcJsEpkZ8FB3+AXQvUvZJKuPupH2G1Gw5hkQ73Zn45s0XhhaX7WL7nDG4GPZ+P7kTv5oGVr7Dwkrop5vZP4fwR9ZhnHej+rDr1XoPdv8titii89P1+ftidZF3r5o52NujNEkKIakoSnDI4XYJzuZTD6kcx+5dC1tm/j3uHQMvB0GoINLjZIWdhFZktPLN4Lz8fOIfRRc+cMV3o0bSCvRems7DzS/hz3t9jldx9odtT6gw0DVcivp5Cs4VJS/bx076zGPQ6/m94Bwbb4qM6IYSoxiTBKYNTJzglLGY4+bvai3HkZ8g3/f2YV5A61bxZPwjvBUYv7eL8h0Kzhce/3sX6uFRcDeobfZm9GEX5cGyt2tajv6hr2YC6NUbXR+GmB9Ukx0EVFFl4+ts9rDmUjItex8z7OzKgbYjWYQkhhMORBKcMNSLBuVxRvrpz+eEV6sae+Zl/P2Zwg0Y9oMnt6jo7ga00/ygrv8jMc9/tZfWBZHQ6mHpHK8Z2/8cGl+YiOL0dDixVB13nXdamht3h5seh+UCH7Km63KUCM099u5v1cam4GfT8b9RNRLdyjDV4hBDC0UiCU4Yal+BcrqhA7dk59iv89StknCr9uIe/mvA06gkNItWEx2D/rRTMFoVpPx1iYYwa3xO9G/NiNx90xzfCsXVwYlPppMY7FNrdq443Cmpt93grI8WUx4SFf7I/KROji57PHrzBcUdCCOHkJMEpQ41OcC6nKJD2l5ronNgEiduhMLd0GRd3CG4LoTdBaAeo2xwCmtl+LEtRAUrKQX7f9AtpR2NorztOE/3Z0mU8akPzQdB+uNpr4+C9NZc7kJTJwwt3kmLKp7anK7Mf6ERkRB2twxJCCIcmCU4ZJMG5hqICdW2dhC2Q8Ic6I+vyXpLLeYdC3Wbg1xB8QtVBzD6h4B2sJj9u3uBWS52m/s8FCM1F6gajl9IhN139ajoLF45D+gn1djEBLIWlTrMoOuJdmxJ80x34tB0I9W6qVklNidUHzjFpyV7yCi00CfRizpjOsoifEEKUgyQ4ZZAEp5wsFnXTzzO74Mxudb+mtL8gJ7X8dehd1LV5FLM68Llku4ny8KitLsJXrzP7aMzTv+k5leeBr4crHw3vwK0tqtfHOYVmCx9vOMbMjfEA9GpWl5kjO+LjKLupCyGEg5MEpwyS4NygSxch7Zia7GQmqb0vWefUr9kpkJ8NRZfKrsfdV12bxsNfndlVJwL8I8C/sfrVt36p3p/T6blM/GY3+5LUXqUnejdm0u3NtN2JvJyOn89m0nd7rbE/1D2cVwe2qBaxCyGEo5AEpwyS4NiBxQwF2Wqyo5hBpwedQf1ISe8CRh8wuFS42vwiM2//HGcdfNyxgR/v3NWWliGO+TwqisLX20/x9uo48got+Li78NZdbWWNGyGEqARJcMogCU71t3LfWV5ddoDs/CIMeh0P9wjnmeimeLpVPGmylYS0HKauPMRvf50HoEeTAD64tx0hvh4aRyaEENWTJDhlkATHOSRn5jHtp0P8cjAZgHp+HrwxpDW3tQhEp+HO6uk5BXy84Rhfbz9FkUXB6KJn8oAWjI5qhF5f/XZ8F0IIRyEJThkkwXEuG+JSmPLjIc5kqON+Ojbw48neTejT0r6JTl6hmfnbEpi1KZ6sPHU15d7N6/LaoFY0CXSc1aKFEKK6qsj7t81GOL799tt069YNT09P/Pz8ynWOoihMmTKFkJAQPDw8iI6O5tixY6XKpKenM2rUKHx8fPDz82P8+PFkZ2fboAWiuujTMoh1k27h0V4RuLno2ZOYwcML/2TAf7fw494zFJktNr1+4oVc3v3lCN3f3ci7vxwhK6+IliE+fD0+kvnjukpyI4QQGrBZD87UqVPx8/MjKSmJOXPmkJGRUeY57733HtOnT2fBggWEh4fz+uuvc+DAAQ4fPoy7uzsAAwYM4Ny5c3z22WcUFhYybtw4unTpwjfffFPu2KQHx3mlZuUx948Evt5+iux8tRelrreR/q2DGdg2hK7h/hiq4GOi3IIithxL45sdifx+7Dwlr6JQX3cm9W3OXR3rVcl1hBBC/M2hPqKaP38+zz77bJkJjqIohIaG8vzzz/PCCy8AkJmZSVBQEPPnz2fEiBHExcXRqlUrdu7cSefOnQFYs2YNAwcOJCkpidDQ8s1MkQTH+WXmFrIwJoG5W09yMffvBQMDvIz0bR1Eh/p+tAzxoWmQF+6uZS8WmFdo5uCZTLbGX2Dr8TT2JF6k0Pz3S+eWZnUZFdmAPi0CZeq3EELYSEXevx1mysnJkydJTk4mOjraeszX15fIyEhiYmIYMWIEMTEx+Pn5WZMbgOjoaPR6PTt27OCuu+7SInThgHw9XXmqT1Me6RXBtvgL/HzgHGsPJZOWnc83OxL5ZkciAAa9joiAWtSr7YG7iwF3Vz3urgYMeh2pWfmcy7xEcmYeadkFV1wj1NedO9uHMjKygaxELIQQDsZhEpzkZHUmTFBQ6Z2Ug4KCrI8lJycTGFh69VoXFxf8/f2tZa4mPz+f/Px86/cmk6mqwhYOzuhi4NYWgdzaIpCCu9qy7Xgav/+VxuFzmcSdyyLzUiHHUrM5llr2OC7/Wm5ERdShW5M6dG8cQMM6nprO1hJCCHFtFUpwXnnlFd57773rlomLi6NFixY3FFRVmz59OtOmTdM6DKExNxc9vZsHWnfsVhSFc5l5HEk2kZZdQH6hmbxCC3mFZgotCnW93Ajx9SDEz51QXw/8PF0loRFCiGqiQgnO888/z9ixY69bJiIiolKBBAcHA5CSkkJISIj1eEpKCh06dLCWSU0tvQ9SUVER6enp1vOvZvLkyUyaNMn6vclkIiwsrFJxCueh0+kI9fMg1E8W3hNCCGdToQSnbt261K1b1yaBhIeHExwczIYNG6wJjclkYseOHTz++OMAREVFkZGRwa5du+jUqRMAGzduxGKxEBkZec26jUYjRqPRJnELIYQQwvHYbLpHYmIie/fuJTExEbPZzN69e9m7d2+pNWtatGjB8uXLAfW/6WeffZa33nqLlStXcuDAAUaPHk1oaChDhw4FoGXLlvTv358JEyYQGxvL1q1bmThxIiNGjCj3DCohhBBCOD+bDTKeMmUKCxYssH7fsWNHADZt2kTv3r0BOHr0KJmZmdYyL730Ejk5OTzyyCNkZGTQo0cP1qxZY10DB2DRokVMnDiRPn36oNfrGTZsGB9//LGtmiGEEEKIaki2apB1cIQQQohqwSG2ahBCCCGE0IokOEIIIYRwOpLgCCGEEMLpSIIjhBBCCKcjCY4QQgghnI4kOEIIIYRwOpLgCCGEEMLpSIIjhBBCCKcjCY4QQgghnI7NtmpwZCWLN5tMJo0jEUIIIUR5lbxvl2cThhqZ4GRlZQEQFhamcSRCCCGEqKisrCx8fX2vW6ZG7kVlsVg4e/Ys3t7e6HS6Kq3bZDIRFhbG6dOnnXKfK2lf9efsbZT2VX/O3kZnbx/Yro2KopCVlUVoaCh6/fVH2dTIHhy9Xk/9+vVteg0fHx+n/cUFaZ8zcPY2SvuqP2dvo7O3D2zTxrJ6bkrIIGMhhBBCOB1JcIQQQgjhdCTBqWJGo5GpU6diNBq1DsUmpH3Vn7O3UdpX/Tl7G529feAYbayRg4yFEEII4dykB0cIIYQQTkcSHCGEEEI4HUlwhBBCCOF0JMERQgghhNORBKeC3n77bbp164anpyd+fn7lOkdRFKZMmUJISAgeHh5ER0dz7NixUmXS09MZNWoUPj4++Pn5MX78eLKzs23QguuraBwJCQnodLqr3pYuXWotd7XHFy9ebI8mXaEyP+vevXtfEf9jjz1WqkxiYiKDBg3C09OTwMBAXnzxRYqKimzZlKuqaPvS09N56qmnaN68OR4eHjRo0ICnn36azMzMUuW0fA5nzZpFo0aNcHd3JzIyktjY2OuWX7p0KS1atMDd3Z22bduyevXqUo+X5zVpTxVp3xdffEHPnj2pXbs2tWvXJjo6+oryY8eOveK56t+/v62bcU0Vad/8+fOviN3d3b1UGUd7/qBibbza3xOdTsegQYOsZRzpOfz999+58847CQ0NRafTsWLFijLP2bx5MzfddBNGo5EmTZowf/78K8pU9HVdYYqokClTpigffvihMmnSJMXX17dc57z77ruKr6+vsmLFCmXfvn3K4MGDlfDwcOXSpUvWMv3791fat2+vbN++XdmyZYvSpEkT5f7777dRK66tonEUFRUp586dK3WbNm2a4uXlpWRlZVnLAcq8efNKlbu8/fZUmZ91r169lAkTJpSKPzMz0/p4UVGR0qZNGyU6OlrZs2ePsnr1aiUgIECZPHmyrZtzhYq278CBA8rdd9+trFy5UomPj1c2bNigNG3aVBk2bFipclo9h4sXL1bc3NyUuXPnKocOHVImTJig+Pn5KSkpKVctv3XrVsVgMCjvv/++cvjwYeW1115TXF1dlQMHDljLlOc1aS8Vbd/IkSOVWbNmKXv27FHi4uKUsWPHKr6+vkpSUpK1zJgxY5T+/fuXeq7S09Pt1aRSKtq+efPmKT4+PqViT05OLlXGkZ4/Ral4Gy9cuFCqfQcPHlQMBoMyb948axlHeg5Xr16t/Otf/1KWLVumAMry5cuvW/7EiROKp6enMmnSJOXw4cPKzJkzFYPBoKxZs8ZapqI/s8qQBKeS5s2bV64Ex2KxKMHBwcoHH3xgPZaRkaEYjUbl22+/VRRFUQ4fPqwAys6dO61lfvnlF0Wn0ylnzpyp8tivpari6NChg/LQQw+VOlaeF4U9VLaNvXr1Up555plrPr569WpFr9eX+kP86aefKj4+Pkp+fn6VxF4eVfUcLlmyRHFzc1MKCwutx7R6Drt27ao8+eST1u/NZrMSGhqqTJ8+/arl77vvPmXQoEGljkVGRiqPPvqooijle03aU0Xb909FRUWKt7e3smDBAuuxMWPGKEOGDKnqUCulou0r62+roz1/inLjz+H//d//Kd7e3kp2drb1mCM9h5crz9+Bl156SWndunWpY8OHD1f69etn/f5Gf2blIR9R2djJkydJTk4mOjraeszX15fIyEhiYmIAiImJwc/Pj86dO1vLREdHo9fr2bFjh91irYo4du3axd69exk/fvwVjz355JMEBATQtWtX5s6dW67t7qvajbRx0aJFBAQE0KZNGyZPnkxubm6petu2bUtQUJD1WL9+/TCZTBw6dKjqG3INVfW7lJmZiY+PDy4upbers/dzWFBQwK5du0q9fvR6PdHR0dbXzz/FxMSUKg/qc1FSvjyvSXupTPv+KTc3l8LCQvz9/Usd37x5M4GBgTRv3pzHH3+cCxcuVGns5VHZ9mVnZ9OwYUPCwsIYMmRIqdeQIz1/UDXP4Zw5cxgxYgS1atUqddwRnsPKKOs1WBU/s/KokZtt2lNycjJAqTe+ku9LHktOTiYwMLDU4y4uLvj7+1vL2ENVxDFnzhxatmxJt27dSh1/4403uO222/D09GTt2rU88cQTZGdn8/TTT1dZ/OVR2TaOHDmShg0bEhoayv79+3n55Zc5evQoy5Yts9Z7tee45DF7qYrnMC0tjTfffJNHHnmk1HEtnsO0tDTMZvNVf7ZHjhy56jnXei4uf72VHLtWGXupTPv+6eWXXyY0NLTUm0X//v25++67CQ8P5/jx47z66qsMGDCAmJgYDAZDlbbheirTvubNmzN37lzatWtHZmYmM2bMoFu3bhw6dIj69es71PMHN/4cxsbGcvDgQebMmVPquKM8h5VxrdegyWTi0qVLXLx48YZ/78tDEhzglVde4b333rtumbi4OFq0aGGniKpWedt3oy5dusQ333zD66+/fsVjlx/r2LEjOTk5fPDBB1X25mjrNl7+Zt+2bVtCQkLo06cPx48fp3HjxpWut7zs9RyaTCYGDRpEq1at+Pe//13qMVs/h6Li3n33XRYvXszmzZtLDcQdMWKE9X7btm1p164djRs3ZvPmzfTp00eLUMstKiqKqKgo6/fdunWjZcuWfPbZZ7z55psaRmYbc+bMoW3btnTt2rXU8er8HDoKSXCA559/nrFjx163TERERKXqDg4OBiAlJYWQkBDr8ZSUFDp06GAtk5qaWuq8oqIi0tPTreffiPK270bj+P7778nNzWX06NFllo2MjOTNN98kPz+/SvYqsVcbS0RGRgIQHx9P48aNCQ4OvmIGQEpKCkC1eQ6zsrLo378/3t7eLF++HFdX1+uWr+rn8GoCAgIwGAzWn2WJlJSUa7YnODj4uuXL85q0l8q0r8SMGTN49913Wb9+Pe3atbtu2YiICAICAoiPj7frm+ONtK+Eq6srHTt2JD4+HnCs5w9urI05OTksXryYN954o8zraPUcVsa1XoM+Pj54eHhgMBhu+PeiXKpsNE8NU9FBxjNmzLAey8zMvOog4z///NNa5tdff9VskHFl4+jVq9cVM2+u5a233lJq165d6Vgrq6p+1n/88YcCKPv27VMU5e9BxpfPAPjss88UHx8fJS8vr+oaUIbKti8zM1O5+eablV69eik5OTnlupa9nsOuXbsqEydOtH5vNpuVevXqXXeQ8R133FHqWFRU1BWDjK/3mrSnirZPURTlvffeU3x8fJSYmJhyXeP06dOKTqdTfvzxxxuOt6Iq077LFRUVKc2bN1eee+45RVEc7/lTlMq3cd68eYrRaFTS0tLKvIaWz+HlKOcg4zZt2pQ6dv/9918xyPhGfi/KFWuV1VRDnDp1StmzZ491KvSePXuUPXv2lJoS3bx5c2XZsmXW7999913Fz89P+fHHH5X9+/crQ4YMueo08Y4dOyo7duxQ/vjjD6Vp06aaTRO/XhxJSUlK8+bNlR07dpQ679ixY4pOp1N++eWXK+pcuXKl8sUXXygHDhxQjh07pvzvf/9TPD09lSlTpti8PVdT0TbGx8crb7zxhvLnn38qJ0+eVH788UclIiJCueWWW6znlEwT79u3r7J3715lzZo1St26dTWbJl6R9mVmZiqRkZFK27Ztlfj4+FLTUouKihRF0fY5XLx4sWI0GpX58+crhw8fVh555BHFz8/POmPtwQcfVF555RVr+a1btyouLi7KjBkzlLi4OGXq1KlXnSZe1mvSXiravnfffVdxc3NTvv/++1LPVcnfoKysLOWFF15QYmJilJMnTyrr169XbrrpJqVp06Z2TbYr275p06Ypv/76q3L8+HFl165dyogRIxR3d3fl0KFD1jKO9PwpSsXbWKJHjx7K8OHDrzjuaM9hVlaW9b0OUD788ENlz549yqlTpxRFUZRXXnlFefDBB63lS6aJv/jii0pcXJwya9asq04Tv97PrCpIglNBY8aMUYArbps2bbKWoXi9kBIWi0V5/fXXlaCgIMVoNCp9+vRRjh49WqreCxcuKPfff7/i5eWl+Pj4KOPGjSuVNNlLWXGcPHnyivYqiqJMnjxZCQsLU8xm8xV1/vLLL0qHDh0ULy8vpVatWkr79u2V2bNnX7WsPVS0jYmJicott9yi+Pv7K0ajUWnSpIny4osvlloHR1EUJSEhQRkwYIDi4eGhBAQEKM8//3ypadb2UtH2bdq06aq/04By8uRJRVG0fw5nzpypNGjQQHFzc1O6du2qbN++3fpYr169lDFjxpQqv2TJEqVZs2aKm5ub0rp1a+Xnn38u9Xh5XpP2VJH2NWzY8KrP1dSpUxVFUZTc3Fylb9++St26dRVXV1elYcOGyoQJE6r0jaOiKtK+Z5991lo2KChIGThwoLJ79+5S9Tna86coFf8dPXLkiAIoa9euvaIuR3sOr/U3oqRNY8aMUXr16nXFOR06dFDc3NyUiIiIUu+JJa73M6sKOkXRYK6uEEIIIYQNyTo4QgghhHA6kuAIIYQQwulIgiOEEEIIpyMJjhBCCCGcjiQ4QgghhHA6kuAIIYQQwulIgiOEEEIIpyMJjhBCCCGcjiQ4QgghhHA6kuAIIYQQwulIgiOEEEIIpyMJjhBCCCGczv8DGX9YiI4IBqYAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -183,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
diff --git a/docs/notebooks/train_mnist.ipynb b/docs/notebooks/train_mnist.ipynb
index 6cd26a3..69d1987 100644
--- a/docs/notebooks/train_mnist.ipynb
+++ b/docs/notebooks/train_mnist.ipynb
@@ -1,15 +1,5 @@
 {
   "cells": [
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
-      },
-      "source": [
-        "<a href=\"https://colab.research.google.com/github/ASEM000/serket/blob/main/docs/notebooks/train_mnist.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -30,10 +20,7 @@
     },
     {
       "cell_type": "code",
-      "source": [
-        "!pip install keras-core --quiet\n",
-        "!pip install git+https://github.com/ASEM000/serket --quiet"
-      ],
+      "execution_count": 1,
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
@@ -41,17 +28,10 @@
         "id": "HL0vQXylZmcw",
         "outputId": "b380b72a-649c-4897-a482-f260f63a6809"
       },
-      "execution_count": 1,
-      "outputs": [
-        {
-          "output_type": "stream",
-          "name": "stdout",
-          "text": [
-            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
-            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
-            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n"
-          ]
-        }
+      "outputs": [],
+      "source": [
+        "!pip install keras-core --quiet\n",
+        "!pip install git+https://github.com/ASEM000/serket --quiet"
       ]
     },
     {
@@ -66,17 +46,10 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
-          "text": [
-            "Using JAX backend.\n"
-          ]
-        },
-        {
           "output_type": "stream",
-          "name": "stderr",
           "text": [
-            "WARNING:jax._src.xla_bridge:No GPU/TPU found, falling back to CPU. (Set TF_CPP_MIN_LOG_LEVEL=0 and rerun for more info.)\n"
+            "Using JAX backend.\n"
           ]
         }
       ],
@@ -107,6 +80,17 @@
         "#### Data preparation"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "r2zMI_8OZkGG"
+      },
+      "source": [
+        "#### Model creation\n",
+        "\n",
+        "_**Style 1**_"
+      ]
+    },
     {
       "cell_type": "code",
       "execution_count": 3,
@@ -122,17 +106,6 @@
         "y_train = jnp.array_split(y_train, y_train.shape[0] // BATCH_SIZE)"
       ]
     },
-    {
-      "cell_type": "markdown",
-      "metadata": {
-        "id": "r2zMI_8OZkGG"
-      },
-      "source": [
-        "#### Model creation\n",
-        "\n",
-        "_**Style 1**_"
-      ]
-    },
     {
       "cell_type": "code",
       "execution_count": 4,
@@ -177,11 +150,12 @@
         "\n",
         "@sk.autoinit\n",
         "class ConvNet(sk.TreeClass):\n",
-        "    conv1: sk.nn.Conv2D = sk.nn.Conv2D(1, 32, 3, key=k1, padding=\"valid\")\n",
-        "    pool1: sk.nn.MaxPool2D = sk.nn.MaxPool2D(2, 2)\n",
-        "    conv2: sk.nn.Conv2D = sk.nn.Conv2D(32, 64, 3, key=k2, padding=\"valid\")\n",
-        "    pool2: sk.nn.MaxPool2D = sk.nn.MaxPool2D(2, 2)\n",
-        "    linear: sk.nn.Linear = sk.nn.Linear(1600, 10, key=k3)\n",
+        "    def __init__(self):\n",
+        "        self.conv1 = sk.nn.Conv2D(1, 32, 3, key=k1, padding=\"valid\")\n",
+        "        self.pool1 = sk.nn.MaxPool2D(2, 2)\n",
+        "        self.conv2 = sk.nn.Conv2D(32, 64, 3, key=k2, padding=\"valid\")\n",
+        "        self.pool2 = sk.nn.MaxPool2D(2, 2)\n",
+        "        self.linear = sk.nn.Linear(1600, 10, key=k3)\n",
         "\n",
         "    def __call__(self, x: jax.Array) -> jax.Array:\n",
         "        x = self.pool1(jax.nn.relu(self.conv1(x)))\n",
@@ -214,8 +188,8 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
+          "output_type": "stream",
           "text": [
             "depth=0\n",
             "┌────┬───────┬──────┬────────┐\n",
@@ -330,19 +304,21 @@
       },
       "outputs": [
         {
-          "output_type": "stream",
           "name": "stdout",
-          "text": []
+          "output_type": "stream",
+          "text": [
+            "Epoch: 001/001\tBatch: 468/468\tBatch loss: 1.916139e-01\tBatch accuracy: 0.984375\tTime: 21.053\r"
+          ]
         },
         {
-          "output_type": "display_data",
           "data": {
+            "image/png": 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",
             "text/plain": [
               "<Figure size 1000x400 with 10 Axes>"
-            ],
-            "image/png": 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\n"
+            ]
           },
-          "metadata": {}
+          "metadata": {},
+          "output_type": "display_data"
         }
       ],
       "source": [
@@ -360,8 +336,6 @@
         "            end=\"\\r\",\n",
         "        )\n",
         "\n",
-        "# Epoch: 001/001\tBatch: 467/468\tBatch loss: 2.040178e-01\tBatch accuracy: 0.984375\tTime: 19.284\n",
-        "\n",
         "# 6) un-mask the trained network\n",
         "nn = sk.tree_unmask(nn)\n",
         "\n",
@@ -382,6 +356,10 @@
     }
   ],
   "metadata": {
+    "colab": {
+      "include_colab_link": true,
+      "provenance": []
+    },
     "kernelspec": {
       "display_name": "dev-jax",
       "language": "python",
@@ -399,12 +377,8 @@
       "pygments_lexer": "ipython3",
       "version": "3.10.0"
     },
-    "orig_nbformat": 4,
-    "colab": {
-      "provenance": [],
-      "include_colab_link": true
-    }
+    "orig_nbformat": 4
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
\ No newline at end of file
+}
diff --git a/docs/notebooks/train_mp.ipynb b/docs/notebooks/train_mp.ipynb
index 5f8fffd..b4d0a16 100644
--- a/docs/notebooks/train_mp.ipynb
+++ b/docs/notebooks/train_mp.ipynb
@@ -13,20 +13,29 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "!pip install git+https://github.com/ASEM000/serket --quiet"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x160c1ead0>]"
+       "[<matplotlib.lines.Line2D at 0x286852a70>]"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -52,12 +61,14 @@
     "        in_features=1,\n",
     "        out_features=50,\n",
     "        dtype=mp_policy.param_dtype,  # +\n",
+    "        weight_init=\"he_normal\",\n",
     "    ),\n",
     "    jax.numpy.tanh,\n",
     "    sk.nn.Linear(\n",
     "        in_features=50,\n",
     "        out_features=1,\n",
     "        dtype=mp_policy.param_dtype,  # +\n",
+    "        weight_init=\"he_normal\",\n",
     "    ),\n",
     "    mp_policy.cast_to_output,  # +\n",
     ")\n",