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148 lines
3.2 KiB
148 lines
3.2 KiB
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "d0ce4228",
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"metadata": {},
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"source": [
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"# plot activation functions\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b3c8093a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Importing the required libraries\n",
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"import math\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a134fb45",
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"metadata": {},
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"outputs": [],
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"source": [
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"# The definition of activation functions mathematically\n",
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"# Sigmoid Function\n",
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"def sigmoid(x):\n",
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" a = []\n",
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" for i in x:\n",
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" a.append(1/(1+math.exp(-i)))\n",
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" return a"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "954c32ed",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Hyperbolic Tanjant Function\n",
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"def tanh(x, derivative=False):\n",
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" if (derivative == True):\n",
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" return (1 - (x ** 2))\n",
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" return np.tanh(x)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "2c0e5136",
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"metadata": {},
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"outputs": [],
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"source": [
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"# ReLU Function\n",
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"def re(x):\n",
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" b = []\n",
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" for i in x:\n",
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" if i<0:\n",
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" b.append(0)\n",
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" else:\n",
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" b.append(i)\n",
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" return b"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f29cac64",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Leaky ReLU Function\n",
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"def lr(x):\n",
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" b = []\n",
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" for i in x:\n",
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" if i<0:\n",
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" b.append(i/10)\n",
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" else:\n",
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" b.append(i)\n",
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" return b\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1854dc7b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Determining the intervals to be created for the graph\n",
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"x = np.arange(-3., 3., 0.1)\n",
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"sig = sigmoid(x)\n",
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"tanh = tanh(x)\n",
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"relu = re(x)\n",
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"leaky_relu = lr(x)\n",
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"swish = sig*x"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "9c535ccb",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Displaying the functions\n",
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"line_1, = plt.plot(x,sig, label='Sigmoid')\n",
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"line_2, = plt.plot(x,tanh, label='Tanh')\n",
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"line_3, = plt.plot(x,relu, label='ReLU')\n",
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"line_4, = plt.plot(x,leaky_relu, label='Leaky ReLU')\n",
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"line_5, = plt.plot(x,swish, label='Swish')\n",
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"plt.legend(handles=[line_1, line_2, line_3, line_4, line_5])\n",
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"plt.axhline(y=0, color='k')\n",
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"plt.axvline(x=0, color='k')\n",
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"plt.show()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.16"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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