1108 lines
47 KiB
Plaintext
1108 lines
47 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "HxtCFj1hfXw6"
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},
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"source": [
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"# 0. Instalacja i importowanie modułów"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "enDE5aTIgN-v"
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},
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"source": [
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"##### 0.1. Ogólne"
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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": 1,
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"metadata": {
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"id": "D7_8XDfpfH-X"
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: tflearn==0.5 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from -r requirements.txt (line 1)) (0.5.0)\n",
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"Requirement already satisfied: tensorflow in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from -r requirements.txt (line 2)) (2.4.1)\n",
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"Requirement already satisfied: pystempel==1.2 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from -r requirements.txt (line 3)) (1.2.0)\n",
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"Requirement already satisfied: six in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tflearn==0.5->-r requirements.txt (line 1)) (1.15.0)\n",
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"Requirement already satisfied: Pillow in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tflearn==0.5->-r requirements.txt (line 1)) (8.0.1)\n",
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"Requirement already satisfied: numpy in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tflearn==0.5->-r requirements.txt (line 1)) (1.19.2)\n",
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"Requirement already satisfied: flatbuffers~=1.12.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (1.12)\n",
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"Requirement already satisfied: gast==0.3.3 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (0.3.3)\n",
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"Requirement already satisfied: tensorflow-estimator<2.5.0,>=2.4.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (2.4.0)\n",
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"Requirement already satisfied: grpcio~=1.32.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (1.32.0)\n",
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"Requirement already satisfied: wheel~=0.35 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tensorflow->-r requirements.txt (line 2)) (0.35.1)\n",
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"Requirement already satisfied: wrapt~=1.12.1 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (1.12.1)\n",
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"Requirement already satisfied: termcolor~=1.1.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (1.1.0)\n",
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"Requirement already satisfied: google-pasta~=0.2 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (0.2.0)\n",
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"Requirement already satisfied: absl-py~=0.10 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (0.12.0)\n",
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"Requirement already satisfied: tensorboard~=2.4 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (2.4.1)\n",
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"Requirement already satisfied: astunparse~=1.6.3 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (1.6.3)\n",
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"Requirement already satisfied: opt-einsum~=3.3.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (3.3.0)\n",
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"Requirement already satisfied: typing-extensions~=3.7.4 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tensorflow->-r requirements.txt (line 2)) (3.7.4.3)\n",
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"Requirement already satisfied: h5py~=2.10.0 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tensorflow->-r requirements.txt (line 2)) (2.10.0)\n",
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"Requirement already satisfied: keras-preprocessing~=1.1.2 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (1.1.2)\n",
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"Requirement already satisfied: protobuf>=3.9.2 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorflow->-r requirements.txt (line 2)) (3.15.6)\n",
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"Requirement already satisfied: sortedcontainers in c:\\users\\annad\\anaconda3\\lib\\site-packages (from pystempel==1.2->-r requirements.txt (line 3)) (2.2.2)\n",
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"Requirement already satisfied: tqdm in c:\\users\\annad\\anaconda3\\lib\\site-packages (from pystempel==1.2->-r requirements.txt (line 3)) (4.50.2)\n",
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"Requirement already satisfied: markdown>=2.6.8 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (3.3.4)\n",
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"Requirement already satisfied: requests<3,>=2.21.0 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (2.24.0)\n",
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"Requirement already satisfied: google-auth<2,>=1.6.3 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (1.28.0)\n",
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"Requirement already satisfied: setuptools>=41.0.0 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (50.3.1.post20201107)\n",
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"Requirement already satisfied: werkzeug>=0.11.15 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (1.0.1)\n",
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"Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (1.8.0)\n",
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"Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (0.4.3)\n",
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"Requirement already satisfied: idna<3,>=2.5 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (2.10)\n",
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"Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (2020.6.20)\n",
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"Requirement already satisfied: chardet<4,>=3.0.2 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (3.0.4)\n",
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"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in c:\\users\\annad\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (1.25.11)\n",
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"Requirement already satisfied: rsa<5,>=3.1.4; python_version >= \"3.6\" in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (4.7.2)\n",
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"Requirement already satisfied: pyasn1-modules>=0.2.1 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (0.2.8)\n",
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"Requirement already satisfied: cachetools<5.0,>=2.0.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (4.2.1)\n",
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"Requirement already satisfied: requests-oauthlib>=0.7.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (1.3.0)\n",
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"Requirement already satisfied: pyasn1>=0.1.3 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from rsa<5,>=3.1.4; python_version >= \"3.6\"->google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (0.4.8)\n",
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"Requirement already satisfied: oauthlib>=3.0.0 in c:\\users\\annad\\appdata\\roaming\\python\\python38\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow->-r requirements.txt (line 2)) (3.1.0)\n",
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"Package Version\n",
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"---------------------------------- -------------------\n",
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"absl-py 0.12.0\n",
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"alabaster 0.7.12\n",
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"anaconda-client 1.7.2\n",
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"anaconda-navigator 1.10.0\n",
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"anaconda-project 0.8.3\n",
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"argh 0.26.2\n",
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"argon2-cffi 20.1.0\n",
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"asn1crypto 1.4.0\n",
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"astroid 2.4.2\n",
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"astropy 4.0.2\n",
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"astunparse 1.6.3\n",
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"async-generator 1.10\n",
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"atomicwrites 1.4.0\n",
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"attrs 20.3.0\n",
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"autopep8 1.5.4\n",
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"Babel 2.8.1\n",
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"backcall 0.2.0\n",
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"backports.functools-lru-cache 1.6.1\n",
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"backports.shutil-get-terminal-size 1.0.0\n",
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"backports.tempfile 1.0\n",
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"backports.weakref 1.0.post1\n",
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"bcrypt 3.2.0\n",
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"beautifulsoup4 4.9.3\n",
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"bitarray 1.6.1\n",
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"bkcharts 0.2\n",
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"bleach 3.2.1\n",
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"bokeh 2.2.3\n",
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"boto 2.49.0\n",
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"Bottleneck 1.3.2\n",
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"brotlipy 0.7.0\n",
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"cachetools 4.2.1\n",
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"certifi 2020.6.20\n",
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"cffi 1.14.3\n",
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"chardet 3.0.4\n",
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"click 7.1.2\n",
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"cloudpickle 1.6.0\n",
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"clyent 1.2.2\n",
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"colorama 0.4.4\n",
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"comtypes 1.1.7\n",
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"conda 4.9.2\n",
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"conda-build 3.20.5\n",
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"conda-package-handling 1.7.2\n",
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"conda-verify 3.4.2\n",
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"contextlib2 0.6.0.post1\n",
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"cryptography 3.1.1\n",
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"cycler 0.10.0\n",
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"Cython 0.29.21\n",
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"cytoolz 0.11.0\n",
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"dask 2.30.0\n",
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"decorator 4.4.2\n",
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"defusedxml 0.6.0\n",
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"diff-match-patch 20200713\n",
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"distributed 2.30.1\n",
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"docutils 0.16\n",
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"entrypoints 0.3\n",
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"et-xmlfile 1.0.1\n",
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"fastcache 1.1.0\n",
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"filelock 3.0.12\n",
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"flake8 3.8.4\n",
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"Flask 1.1.2\n",
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"flatbuffers 1.12\n",
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"fsspec 0.8.3\n",
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"future 0.18.2\n",
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"gast 0.3.3\n",
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"gevent 20.9.0\n",
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"glob2 0.7\n",
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"google-auth 1.28.0\n",
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"google-auth-oauthlib 0.4.3\n",
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"google-pasta 0.2.0\n",
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"greenlet 0.4.17\n",
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"grpcio 1.32.0\n",
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"h5py 2.10.0\n",
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"HeapDict 1.0.1\n",
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"html5lib 1.1\n",
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"idna 2.10\n",
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"imageio 2.9.0\n",
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"imagesize 1.2.0\n",
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"importlib-metadata 2.0.0\n",
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"iniconfig 1.1.1\n",
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"intervaltree 3.1.0\n",
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"ipykernel 5.3.4\n",
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"ipython 7.19.0\n",
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"ipython-genutils 0.2.0\n",
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"ipywidgets 7.5.1\n",
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"isort 5.6.4\n",
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"itsdangerous 1.1.0\n",
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"jdcal 1.4.1\n",
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"jedi 0.17.1\n",
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"Jinja2 2.11.2\n",
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"joblib 0.17.0\n",
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"json5 0.9.5\n",
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"jsonschema 3.2.0\n",
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"jupyter 1.0.0\n",
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"jupyter-client 6.1.7\n",
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"jupyter-console 6.2.0\n",
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"jupyter-core 4.6.3\n",
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"jupyterlab 2.2.6\n",
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"jupyterlab-pygments 0.1.2\n",
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"jupyterlab-server 1.2.0\n",
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"Keras-Preprocessing 1.1.2\n",
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"keyring 21.4.0\n",
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"kiwisolver 1.3.0\n",
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"lazy-object-proxy 1.4.3\n",
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"libarchive-c 2.9\n",
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"llvmlite 0.34.0\n",
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"locket 0.2.0\n",
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"lxml 4.6.1\n",
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"Markdown 3.3.4\n",
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"MarkupSafe 1.1.1\n",
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"matplotlib 3.3.2\n",
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"mccabe 0.6.1\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"menuinst 1.4.16\n",
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"mistune 0.8.4\n",
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"mkl-fft 1.2.0\n",
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"mkl-random 1.1.1\n",
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"mkl-service 2.3.0\n",
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"mock 4.0.2\n",
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"more-itertools 8.6.0\n",
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"mpmath 1.1.0\n",
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"msgpack 1.0.0\n",
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"multipledispatch 0.6.0\n",
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"navigator-updater 0.2.1\n",
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"nbclient 0.5.1\n",
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"nbconvert 6.0.7\n",
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"nbformat 5.0.8\n",
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"nest-asyncio 1.4.2\n",
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"networkx 2.5\n",
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"nltk 3.5\n",
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"nose 1.3.7\n",
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"notebook 6.1.4\n",
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"numba 0.51.2\n",
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"numexpr 2.7.1\n",
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"numpy 1.19.2\n",
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"numpydoc 1.1.0\n",
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"oauthlib 3.1.0\n",
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"olefile 0.46\n",
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"openpyxl 3.0.5\n",
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"opt-einsum 3.3.0\n",
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"packaging 20.4\n",
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"pandas 1.1.3\n",
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"pandocfilters 1.4.3\n",
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"paramiko 2.7.2\n",
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"parso 0.7.0\n",
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"partd 1.1.0\n",
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"path 15.0.0\n",
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"pathlib2 2.3.5\n",
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"pathtools 0.1.2\n",
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"patsy 0.5.1\n",
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"pep8 1.7.1\n",
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"pexpect 4.8.0\n",
|
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"pickleshare 0.7.5\n",
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"Pillow 8.0.1\n",
|
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"pip 20.2.4\n",
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"pkginfo 1.6.1\n",
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"pluggy 0.13.1\n",
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"ply 3.11\n",
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"prometheus-client 0.8.0\n",
|
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"prompt-toolkit 3.0.8\n",
|
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"protobuf 3.15.6\n",
|
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"psutil 5.7.2\n",
|
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"py 1.9.0\n",
|
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"pyasn1 0.4.8\n",
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"pyasn1-modules 0.2.8\n",
|
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"pycodestyle 2.6.0\n",
|
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"pycosat 0.6.3\n",
|
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"pycparser 2.20\n",
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"pycurl 7.43.0.6\n",
|
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"pydocstyle 5.1.1\n",
|
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"pyflakes 2.2.0\n",
|
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"Pygments 2.7.2\n",
|
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"pylint 2.6.0\n",
|
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"PyNaCl 1.4.0\n",
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"pyodbc 4.0.0-unsupported\n",
|
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"pyOpenSSL 19.1.0\n",
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"pyparsing 2.4.7\n",
|
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"pyreadline 2.1\n",
|
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"pyrsistent 0.17.3\n",
|
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"PySocks 1.7.1\n",
|
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"pystempel 1.2.0\n",
|
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"pytest 0.0.0\n",
|
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"python-dateutil 2.8.1\n",
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"python-jsonrpc-server 0.4.0\n",
|
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"python-language-server 0.35.1\n",
|
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"pytz 2020.1\n",
|
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"PyWavelets 1.1.1\n",
|
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"pywin32 227\n",
|
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"pywin32-ctypes 0.2.0\n",
|
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"pywinpty 0.5.7\n",
|
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"PyYAML 5.3.1\n",
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"pyzmq 19.0.2\n",
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"QDarkStyle 2.8.1\n",
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"QtAwesome 1.0.1\n",
|
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"qtconsole 4.7.7\n",
|
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"QtPy 1.9.0\n",
|
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"regex 2020.10.15\n",
|
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"requests 2.24.0\n",
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"requests-oauthlib 1.3.0\n",
|
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"rope 0.18.0\n",
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"rsa 4.7.2\n",
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"Rtree 0.9.4\n",
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"ruamel-yaml 0.15.87\n",
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"scikit-image 0.17.2\n",
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"scikit-learn 0.23.2\n",
|
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"scipy 1.5.2\n",
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"seaborn 0.11.0\n",
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"Send2Trash 1.5.0\n",
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"setuptools 50.3.1.post20201107\n",
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"simplegeneric 0.8.1\n",
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"singledispatch 3.4.0.3\n",
|
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"sip 4.19.13\n",
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"six 1.15.0\n",
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"snowballstemmer 2.0.0\n",
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"sortedcollections 1.2.1\n",
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"sortedcontainers 2.2.2\n",
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"soupsieve 2.0.1\n",
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"Sphinx 3.2.1\n",
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"sphinxcontrib-applehelp 1.0.2\n",
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"sphinxcontrib-devhelp 1.0.2\n",
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"sphinxcontrib-htmlhelp 1.0.3\n",
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"sphinxcontrib-jsmath 1.0.1\n",
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"sphinxcontrib-qthelp 1.0.3\n",
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"sphinxcontrib-serializinghtml 1.1.4\n",
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"sphinxcontrib-websupport 1.2.4\n",
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"spyder 4.1.5\n",
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"spyder-kernels 1.9.4\n",
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"SQLAlchemy 1.3.20\n",
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"statsmodels 0.12.0\n",
|
|
"sympy 1.6.2\n",
|
|
"tables 3.6.1\n",
|
|
"tblib 1.7.0\n",
|
|
"tensorboard 2.4.1\n",
|
|
"tensorboard-plugin-wit 1.8.0\n",
|
|
"tensorflow 2.4.1\n",
|
|
"tensorflow-estimator 2.4.0\n",
|
|
"termcolor 1.1.0\n",
|
|
"terminado 0.9.1\n",
|
|
"testpath 0.4.4\n",
|
|
"tflearn 0.5.0\n",
|
|
"threadpoolctl 2.1.0\n",
|
|
"tifffile 2020.10.1\n",
|
|
"toml 0.10.1\n",
|
|
"toolz 0.11.1\n",
|
|
"tornado 6.0.4\n",
|
|
"tqdm 4.50.2\n",
|
|
"traitlets 5.0.5\n",
|
|
"typing-extensions 3.7.4.3\n",
|
|
"ujson 4.0.1\n",
|
|
"unicodecsv 0.14.1\n",
|
|
"urllib3 1.25.11\n",
|
|
"watchdog 0.10.3\n",
|
|
"wcwidth 0.2.5\n",
|
|
"webencodings 0.5.1\n",
|
|
"Werkzeug 1.0.1\n",
|
|
"wheel 0.35.1\n",
|
|
"widgetsnbextension 3.5.1\n",
|
|
"win-inet-pton 1.1.0\n",
|
|
"win-unicode-console 0.5\n",
|
|
"wincertstore 0.2\n",
|
|
"wrapt 1.12.1\n",
|
|
"xlrd 1.2.0\n",
|
|
"XlsxWriter 1.3.7\n",
|
|
"xlwings 0.20.8\n",
|
|
"xlwt 1.3.0\n",
|
|
"xmltodict 0.12.0\n",
|
|
"yapf 0.30.0\n",
|
|
"zict 2.0.0\n",
|
|
"zipp 3.4.0\n",
|
|
"zope.event 4.5.0\n",
|
|
"zope.interface 5.1.2\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"!pip install -r requirements.txt --user\n",
|
|
"!pip list"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"metadata": {
|
|
"id": "GOGs4hL6fwwK"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"WARNING:tensorflow:From C:\\Users\\annad\\AppData\\Roaming\\Python\\Python38\\site-packages\\tensorflow\\python\\compat\\v2_compat.py:96: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version.\n",
|
|
"Instructions for updating:\n",
|
|
"non-resource variables are not supported in the long term\n",
|
|
"curses is not supported on this machine (please install/reinstall curses for an optimal experience)\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import numpy as np\n",
|
|
"import tflearn\n",
|
|
"import tensorflow\n",
|
|
"import random\n",
|
|
"import json\n",
|
|
"import nltk"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "Mr0ZD1L2gCWw"
|
|
},
|
|
"source": [
|
|
"##### 0.2. Angielski Stemmer: https://www.nltk.org/_modules/nltk/stem/lancaster.html"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {
|
|
"id": "jy4-9guXgBY3"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"[nltk_data] Downloading package punkt to\n",
|
|
"[nltk_data] C:\\Users\\annad\\AppData\\Roaming\\nltk_data...\n",
|
|
"[nltk_data] Package punkt is already up-to-date!\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"nltk.download('punkt')\n",
|
|
"from nltk.stem.lancaster import LancasterStemmer\n",
|
|
"stemmer_en = LancasterStemmer()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "uPpcNQa_ggUl"
|
|
},
|
|
"source": [
|
|
"##### 0.3. Polski Stemmer **(Docelowy)**: https://pypi.org/project/pystempel/"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 5,
|
|
"metadata": {
|
|
"id": "XBpvJXn1gBDi"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Loading: 92%|██████████████████████████████████████████████████▋ | 2051427/2225192 [00:01<00:00, 1634466.61bytes/s]"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"from stempel import StempelStemmer\n",
|
|
"\n",
|
|
"stemmer_pl = StempelStemmer.default() #.polimorf() #jest lepsza?"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "Lg_3MO_3hQV_"
|
|
},
|
|
"source": [
|
|
"# 1. Załadowanie plików **.json** z bazą słów"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "BzBo1657hn3w"
|
|
},
|
|
"source": [
|
|
"##### 1.1. Docelowa baza słów polskich do nauki modelu (10 rodzajów odp - PL)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 6,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "jKsIW7hHhepB",
|
|
"outputId": "09ba1cb1-bb0e-44ee-9d28-017209902934"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"{'intents': [{'tag': 'greeting', 'patterns': ['Cześć', 'Elo', 'Jesteś?', 'Hej', 'Dzień dobry', 'Sup', 'Witam', 'Hejka', 'Hej!'], 'responses': ['Cześć!', 'Dobrze Cię widzieć!', 'Hej, w czym mogę pomóc?'], 'context_set': ''}, {'tag': 'goodbye', 'patterns': ['narazie', 'Do zobaczenia', 'Dowidzenia', 'Dobranoc', 'Miłego dnia'], 'responses': ['Do zobaczenia później', 'Mam nadzieję, że później pogadamy', 'Narazie!'], 'context_set': ''}, {'tag': 'age', 'patterns': ['Ile masz lat', 'Ile lat ma Janet', 'Wiek', 'Jak stara jesteś', 'jaki jest twój wiek', 'Wieko', 'urodziny'], 'responses': ['Mam kilka dni', 'Urodziłam się 17.03.2021'], 'context_set': ''}, {'tag': 'name', 'patterns': ['Jak masz na imię', 'Jak Cię zwą?', 'twoje imie?', 'Imie', 'Jak cię nazywać', 'Kim jesteś'], 'responses': ['Możesz mnie nazywać Janet!', 'Jestem Janet', 'Jestem Janet, twój ulubiony chatbot'], 'context_set': ''}, {'tag': 'goout', 'patterns': ['Czy chcesz gdzieś wyjść?', 'zrobimy coś razem?', 'pójdziemy gdzieś razem?'], 'responses': ['Może kiedy indziej', 'Odezwę się latem'], 'context_set': ''}, {'tag': 'doing', 'patterns': ['Co robisz teraz?', 'co słychać', 'jakie masz plany?', 'jak się masz?'], 'responses': ['Gram w grę', 'Słucham muzyki', 'nie twój interes', 'nie mam czasu odpowiadać', ''], 'context_set': ''}, {'tag': 'game', 'patterns': ['a w co grasz?', 'a w co?', 'grasz?', 'jaka gra'], 'responses': ['nie interesuj się', 'a co cię to obchodzi', '...', 'w coś', 'W OSRS'], 'context_set': ''}, {'tag': 'music', 'patterns': ['czego?', 'czego słuchasz?', 'jakiej muzyki?', 'a czego?'], 'responses': ['Starego vinyla z 1995 roku', 'mojego ulubionego setu rejwowego', 'czegoś tam...'], 'context_set': ''}, {'tag': 'angry', 'patterns': ['bo co?', 'dlaczego?', 'jak to?'], 'responses': ['Czas zakończyć rozmowę', 'nie mam na to siły i czasu', 'zostaw mnie w spokoju'], 'context_set': ''}, {'tag': 'why', 'patterns': ['o co chodzi?', 'czemu jesteś zła', 'poczekaj'], 'responses': ['...', 'Nie pisz do mnie więcej', 'Nie lubię Cię'], 'context_set': ''}]}\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"with open(\"intents_pl.json\", encoding='utf-8') as file:\n",
|
|
" data_pl = json.load(file)\n",
|
|
"\n",
|
|
"print(data_pl)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "g94eHpqshoat"
|
|
},
|
|
"source": [
|
|
"##### 1.2. Skrócona baza słów (4 rodzaje odp - PL)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 7,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "gJbm_CtRhNOK",
|
|
"outputId": "157196fc-6a25-4a70-aca3-9d886c743f6c"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"{'intents': [{'tag': 'greeting', 'patterns': ['Cześć', 'Elo', 'Jesteś?', 'Hej', 'Dzień dobry', 'Sup'], 'responses': ['Cześć!', 'Dobrze Cię widzieć!', 'Hej, w czym mogę pomóc?'], 'context_set': ''}, {'tag': 'goodbye', 'patterns': ['narazie', 'Do zobaczenia', 'Dowidzenia', 'Dobranoc', 'Miłego dnia'], 'responses': ['Do zobaczenia później', 'Mam nadzieję, że później pogadamy', 'Narazie!'], 'context_set': ''}, {'tag': 'age', 'patterns': ['Ile masz lat', 'Ile lat ma Janet', 'Wiek', 'Jak stara jesteś', 'urodziny'], 'responses': ['Mam kilka dni', 'Urodziłam się 17.03.2021'], 'context_set': ''}, {'tag': 'name', 'patterns': ['Jak masz na imię', 'Jak Cię zwą?', 'twoje imie?', 'Imie', 'Jak cię nazywać', 'Kim jesteś'], 'responses': ['Możesz mnie nazywać Janet!', 'Jestem Janet', 'Jestem Janet, twój ulubiony chatbot'], 'context_set': ''}]}\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"with open(\"intents_pl_short.json\", encoding='utf-8') as file:\n",
|
|
" data_pl_short = json.load(file)\n",
|
|
"\n",
|
|
"print(data_pl_short)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "HjkIUMy2ho6C"
|
|
},
|
|
"source": [
|
|
"##### 1.3. Testowa baza słów angielskich (6 rodzajów odp - EN)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "vW5FyoRqhfIc",
|
|
"outputId": "378d8894-9c9c-46be-ade1-b6491f095179"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"{'intents': [{'tag': 'greeting', 'patterns': ['Hi', 'How are you', 'Is anyone there?', 'Hello', 'Good day', 'Whats up'], 'responses': ['Hello!', 'Good to see you again!', 'Hi there, how can I help?'], 'context_set': ''}, {'tag': 'goodbye', 'patterns': ['cya', 'See you later', 'Goodbye', 'I am Leaving', 'Have a Good day'], 'responses': ['Sad to see you go :(', 'Talk to you later', 'Goodbye!'], 'context_set': ''}, {'tag': 'age', 'patterns': ['how old', 'how old is tim', 'what is your age', 'how old are you', 'age?'], 'responses': ['I am 18 years old!', '18 years young!'], 'context_set': ''}, {'tag': 'name', 'patterns': ['what is your name', 'what should I call you', 'whats your name?'], 'responses': ['You can call me Tim.', \"I'm Tim!\", \"I'm Tim aka Tech With Tim.\"], 'context_set': ''}, {'tag': 'shop', 'patterns': ['Id like to buy something', 'whats on the menu', 'what do you reccommend?', 'could i get something to eat'], 'responses': ['We sell chocolate chip cookies for $2!', 'Cookies are on the menu!'], 'context_set': ''}, {'tag': 'hours', 'patterns': ['when are you guys open', 'what are your hours', 'hours of operation'], 'responses': ['We are open 7am-4pm Monday-Friday!'], 'context_set': ''}]}\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"with open(\"intents_en.json\", encoding='utf-8') as file:\n",
|
|
" data_en = json.load(file)\n",
|
|
"\n",
|
|
"print(data_en)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "4BnsOkqqjBlr"
|
|
},
|
|
"source": [
|
|
"# 2. Przygotowanie danych do nauki modelu"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"metadata": {
|
|
"id": "gy6p55-DjLyY"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"words = []\n",
|
|
"labels = []\n",
|
|
"docs_x = []\n",
|
|
"docs_y = []"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "XxZX-JQA5zjL"
|
|
},
|
|
"source": [
|
|
"##### 2.1 Stworzenie tablicy ze wszystkimi możliwymi inputami użytkownika (+ labele)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {
|
|
"id": "nBUKwSr_kVSd"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"for intent in data_pl[\"intents\"]: #Loop przez cały json\n",
|
|
" for pattern in intent[\"patterns\"]: #loop przez wszystkie możliwe rodzaje przykładowego inputu użytkownika\n",
|
|
" wrds = nltk.word_tokenize(pattern) #Tokenizing every word\n",
|
|
" words.extend(wrds) #Add every single tokenized word\n",
|
|
" docs_x.append(wrds) #Add the whole tokenized sentence\n",
|
|
" docs_y.append(intent[\"tag\"]) #Pattern x coresponds to the tag y. Potrzebne do ustalenia relacji słowa z odpowiedzią\n",
|
|
"\n",
|
|
" if intent[\"tag\"] not in labels:\n",
|
|
" labels.append(intent[\"tag\"]) #Add the tag"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {
|
|
"id": "wOyP5lbikV1e"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"words = [stemmer_pl.stem(w.lower()) for w in words if w not in \"?\"] #stemming -> take each word and bring it to the \"root\" form. Only the stemmed version of the word is important to us\n",
|
|
"words = sorted(list(set(words))) #Sorting\n",
|
|
"\n",
|
|
"labels = sorted(labels) #sorting\n",
|
|
"\n",
|
|
"training = []\n",
|
|
"output = []\n",
|
|
"\n",
|
|
"out_empty = [0 for _ in range(len(labels))]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 12,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Words:\n",
|
|
"['!', 'a', 'bo', 'chcieć', 'chodzić', 'co', 'coś', 'czec', 'czy', 'dlaczy', 'dnia', 'do', 'dobranoc', 'dobry', 'dowidzieć', 'dzień', 'elo', 'gra', 'grać', 'gć', 'hej', 'hejka', 'ile', 'imia', 'imie', 'jak', 'jaka', 'jaki', 'janet', 'jest', 'ki', 'lat', 'mieć', 'miłeon', 'muzy', 'na', 'narazie', 'nazywać', 'o', 'plany', 'poczekać', 'pójdziemy', 'raz', 'robić', 'się', 'star', 'supć', 'słuchać', 'słychać', 'teraa', 'to', 'twoj', 'twój', 'ty', 'urodziny', 'w', 'wiek', 'wieko', 'witać', 'wyjść', 'y', 'zobaczyć', 'zrobić', 'zwać', 'zła']\n",
|
|
"labels:\n",
|
|
"['age', 'angry', 'doing', 'game', 'goodbye', 'goout', 'greeting', 'music', 'name', 'why']\n",
|
|
"docs_y:\n",
|
|
"['greeting', 'greeting', 'greeting', 'greeting', 'greeting', 'greeting', 'greeting', 'greeting', 'greeting', 'goodbye', 'goodbye', 'goodbye', 'goodbye', 'goodbye', 'age', 'age', 'age', 'age', 'age', 'age', 'age', 'name', 'name', 'name', 'name', 'name', 'name', 'goout', 'goout', 'goout', 'doing', 'doing', 'doing', 'doing', 'game', 'game', 'game', 'game', 'music', 'music', 'music', 'music', 'angry', 'angry', 'angry', 'why', 'why', 'why']\n",
|
|
"docs_x:\n",
|
|
"[['Cześć'], ['Elo'], ['Jesteś', '?'], ['Hej'], ['Dzień', 'dobry'], ['Sup'], ['Witam'], ['Hejka'], ['Hej', '!'], ['narazie'], ['Do', 'zobaczenia'], ['Dowidzenia'], ['Dobranoc'], ['Miłego', 'dnia'], ['Ile', 'masz', 'lat'], ['Ile', 'lat', 'ma', 'Janet'], ['Wiek'], ['Jak', 'stara', 'jesteś'], ['jaki', 'jest', 'twój', 'wiek'], ['Wieko'], ['urodziny'], ['Jak', 'masz', 'na', 'imię'], ['Jak', 'Cię', 'zwą', '?'], ['twoje', 'imie', '?'], ['Imie'], ['Jak', 'cię', 'nazywać'], ['Kim', 'jesteś'], ['Czy', 'chcesz', 'gdzieś', 'wyjść', '?'], ['zrobimy', 'coś', 'razem', '?'], ['pójdziemy', 'gdzieś', 'razem', '?'], ['Co', 'robisz', 'teraz', '?'], ['co', 'słychać'], ['jakie', 'masz', 'plany', '?'], ['jak', 'się', 'masz', '?'], ['a', 'w', 'co', 'grasz', '?'], ['a', 'w', 'co', '?'], ['grasz', '?'], ['jaka', 'gra'], ['czego', '?'], ['czego', 'słuchasz', '?'], ['jakiej', 'muzyki', '?'], ['a', 'czego', '?'], ['bo', 'co', '?'], ['dlaczego', '?'], ['jak', 'to', '?'], ['o', 'co', 'chodzi', '?'], ['czemu', 'jesteś', 'zła'], ['poczekaj']]\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"#Podgląd zmiennych\n",
|
|
"print(f\"Words:\\n{words}\")\n",
|
|
"print(f\"labels:\\n{labels}\")\n",
|
|
"print(f\"docs_y:\\n{docs_y}\")\n",
|
|
"print(f\"docs_x:\\n{docs_x}\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "WewUeunf5_Za"
|
|
},
|
|
"source": [
|
|
"##### 3.2. Przypisywanie słów do danej kategorii (ie. \"Cześć\" do Greetings)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "1Q43_qtZ6KNP"
|
|
},
|
|
"source": [
|
|
"W przypadku data_pl_short są tylko 4 rodzaje odpowiedzi. \"Cześć\" które zostane przypisane do labela \"greeting\" będzie miało formę końcowego outputu \"1000\" jeżeli label \"greetings\" jest pierwszy do wyboru."
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "doFER5OS7CC_"
|
|
},
|
|
"source": [
|
|
"Warto też dodać, że sieć neuronowa nie przyjmuje teksu. To jest główny powód czemu przypisujemy słowa do kategorii"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 13,
|
|
"metadata": {
|
|
"id": "8FDKrjpjkYsE"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"for x, doc in enumerate(docs_x): #Przejście przez wszystkie słowa\n",
|
|
" bag =[]\n",
|
|
"\n",
|
|
" wrds = [stemmer_pl.stem(w).lower() for w in doc] #podział wszystkich słów w danym zdaniu\n",
|
|
"\n",
|
|
" for w in words:\n",
|
|
" if w in wrds:\n",
|
|
" bag.append(1) #this word exist\n",
|
|
" else:\n",
|
|
" bag.append(0) #do not exist\n",
|
|
" \n",
|
|
" output_row = out_empty[:] #kopia\n",
|
|
" output_row[labels.index(docs_y[x])] = 1\n",
|
|
"\n",
|
|
" training.append(bag) #dodajemy nowe wyrażenie zamienione na ciąg binarny\n",
|
|
" output.append(output_row)\n",
|
|
"\n",
|
|
"training = np.array(training) #Zbiór treningowy\n",
|
|
"output = np.array(output) #Zbiór outputów"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "cJKUjbkC72-f",
|
|
"outputId": "7e2bff96-78ce-49ff-b27b-eee77752228d"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"48"
|
|
]
|
|
},
|
|
"execution_count": 20,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"\n",
|
|
"Loading: 100%|███████████████████████████████████████████████████████| 2225192/2225192 [00:20<00:00, 1720623.81bytes/s]\u001b[A"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"len(training) #dla pl_short mamy 44 słowa"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 11,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "Kx43VDgS7-yN",
|
|
"outputId": "4fa6f6fe-dc58-4e76-bb26-38c1784ab79c"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"10"
|
|
]
|
|
},
|
|
"execution_count": 11,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"len(output[0]) #Które można przypisać do 4 kategorii"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 14,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"[[0 0 0 ... 0 0 0]\n",
|
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" [0 0 0 ... 0 0 0]\n",
|
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" [0 0 0 ... 0 0 0]\n",
|
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" ...\n",
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" [0 0 0 ... 0 0 0]\n",
|
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" [0 0 0 ... 0 0 1]\n",
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" [0 0 0 ... 0 0 0]]\n",
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|
"[[0 0 0 0 0 0 1 0 0 0]\n",
|
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" [0 0 0 0 0 0 1 0 0 0]\n",
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" [0 0 0 0 0 0 1 0 0 0]\n",
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" [0 0 0 0 0 0 1 0 0 0]\n",
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" [0 0 0 0 0 0 1 0 0 0]\n",
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" [0 0 0 0 0 0 1 0 0 0]\n",
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" [0 0 0 0 0 0 1 0 0 0]\n",
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" [0 0 0 0 0 0 1 0 0 0]\n",
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" [0 0 0 0 0 0 1 0 0 0]\n",
|
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" [0 0 0 0 1 0 0 0 0 0]\n",
|
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" [0 0 0 0 1 0 0 0 0 0]\n",
|
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" [0 0 0 0 1 0 0 0 0 0]\n",
|
|
" [0 0 0 0 1 0 0 0 0 0]\n",
|
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" [0 0 0 0 1 0 0 0 0 0]\n",
|
|
" [1 0 0 0 0 0 0 0 0 0]\n",
|
|
" [1 0 0 0 0 0 0 0 0 0]\n",
|
|
" [1 0 0 0 0 0 0 0 0 0]\n",
|
|
" [1 0 0 0 0 0 0 0 0 0]\n",
|
|
" [1 0 0 0 0 0 0 0 0 0]\n",
|
|
" [1 0 0 0 0 0 0 0 0 0]\n",
|
|
" [1 0 0 0 0 0 0 0 0 0]\n",
|
|
" [0 0 0 0 0 0 0 0 1 0]\n",
|
|
" [0 0 0 0 0 0 0 0 1 0]\n",
|
|
" [0 0 0 0 0 0 0 0 1 0]\n",
|
|
" [0 0 0 0 0 0 0 0 1 0]\n",
|
|
" [0 0 0 0 0 0 0 0 1 0]\n",
|
|
" [0 0 0 0 0 0 0 0 1 0]\n",
|
|
" [0 0 0 0 0 1 0 0 0 0]\n",
|
|
" [0 0 0 0 0 1 0 0 0 0]\n",
|
|
" [0 0 0 0 0 1 0 0 0 0]\n",
|
|
" [0 0 1 0 0 0 0 0 0 0]\n",
|
|
" [0 0 1 0 0 0 0 0 0 0]\n",
|
|
" [0 0 1 0 0 0 0 0 0 0]\n",
|
|
" [0 0 1 0 0 0 0 0 0 0]\n",
|
|
" [0 0 0 1 0 0 0 0 0 0]\n",
|
|
" [0 0 0 1 0 0 0 0 0 0]\n",
|
|
" [0 0 0 1 0 0 0 0 0 0]\n",
|
|
" [0 0 0 1 0 0 0 0 0 0]\n",
|
|
" [0 0 0 0 0 0 0 1 0 0]\n",
|
|
" [0 0 0 0 0 0 0 1 0 0]\n",
|
|
" [0 0 0 0 0 0 0 1 0 0]\n",
|
|
" [0 0 0 0 0 0 0 1 0 0]\n",
|
|
" [0 1 0 0 0 0 0 0 0 0]\n",
|
|
" [0 1 0 0 0 0 0 0 0 0]\n",
|
|
" [0 1 0 0 0 0 0 0 0 0]\n",
|
|
" [0 0 0 0 0 0 0 0 0 1]\n",
|
|
" [0 0 0 0 0 0 0 0 0 1]\n",
|
|
" [0 0 0 0 0 0 0 0 0 1]]\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"\r",
|
|
"Loading: 100%|███████████████████████████████████████████████████████| 2225192/2225192 [00:20<00:00, 1634466.61bytes/s]"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"print(training)\n",
|
|
"print(output)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "yCFKTbjZ12wh"
|
|
},
|
|
"source": [
|
|
"# 3. Model i jego ćwiczenie"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"metadata": {
|
|
"id": "MDA435sI1-Xl"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"training = np.array(training) #zamiana typu dla sieci neuronowej\n",
|
|
"output = np.array(output) #zamiana typu dla sieci neuronowej"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "SvBURQCc3PBj"
|
|
},
|
|
"source": [
|
|
"##### 3.1. Stworzenie DLN i inicjacja modelu"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 16,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "XaQJh1aG2hbj",
|
|
"outputId": "80420df0-3a78-4583-9563-2165e968713d"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"WARNING:tensorflow:From C:\\Users\\annad\\AppData\\Roaming\\Python\\Python38\\site-packages\\tflearn\\initializations.py:164: calling TruncatedNormal.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
|
|
"Instructions for updating:\n",
|
|
"Call initializer instance with the dtype argument instead of passing it to the constructor\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"tensorflow.compat.v1.reset_default_graph() #Reset na wszelki wypadek (w sumie nie wiem czy to jakaś super ważna linijka kodu)\n",
|
|
"\n",
|
|
"net = tflearn.input_data(shape=[None, len(training[0])]) #Input layer\n",
|
|
"net = tflearn.fully_connected(net, 8) #8 neurons for hidden layer\n",
|
|
"net = tflearn.fully_connected(net, 8) #8 neurons for hidden layer\n",
|
|
"#net = tflearn.fully_connected(net, 8) #8 neurons for hidden layer\n",
|
|
"net = tflearn.fully_connected(net, len(output[0]), activation=\"softmax\") #len(output) neurons for output layer + Softmax jako najlepsze wyjście dla tego typu danych\n",
|
|
"net = tflearn.regression(net)\n",
|
|
"\n",
|
|
"model = tflearn.DNN(net)\n",
|
|
"\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "Ktd1OcBa3PmQ"
|
|
},
|
|
"source": [
|
|
"##### 3.2. Trening Modelu"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 17,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "REzkJL_r2hwl",
|
|
"outputId": "7ab2b0c5-944f-4e22-d478-1e35b41f87db"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Training Step: 5999 | total loss: \u001b[1m\u001b[32m0.02785\u001b[0m\u001b[0m | time: 0.007s\n",
|
|
"| Adam | epoch: 1000 | loss: 0.02785 - acc: 0.9753 -- iter: 40/48\n",
|
|
"Training Step: 6000 | total loss: \u001b[1m\u001b[32m0.02583\u001b[0m\u001b[0m | time: 0.008s\n",
|
|
"| Adam | epoch: 1000 | loss: 0.02583 - acc: 0.9777 -- iter: 48/48\n",
|
|
"--\n",
|
|
"INFO:tensorflow:C:\\Users\\annad\\Desktop\\System Dialogowy Janet\\model.tflearn is not in all_model_checkpoint_paths. Manually adding it.\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"model.fit(training, output, n_epoch=1000, batch_size=8, show_metric=True)\n",
|
|
"\n",
|
|
"#Zapis Modelu\n",
|
|
"model.save(\"model.tflearn\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "G-L6TV_63iYs"
|
|
},
|
|
"source": [
|
|
"# 4. Input Użytkownika"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "c6UvIrWu-a38"
|
|
},
|
|
"source": [
|
|
"##### 4.1 Funkcja **\"bag_of_words(s, words)\"** do stemmowania twojego zdania, i przypisania mu formy binarnej"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 18,
|
|
"metadata": {
|
|
"id": "1IQyV1v33lC7"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def bag_of_words(s, words):\n",
|
|
" bag = [0 for _ in range(len(words))]\n",
|
|
"\n",
|
|
" s_words = nltk.word_tokenize(s)\n",
|
|
" s_words = [stemmer_pl.stem(word.lower()) for word in s_words]\n",
|
|
"\n",
|
|
" for se in s_words:\n",
|
|
" for i, w in enumerate(words):\n",
|
|
" if w == se:\n",
|
|
" bag[i] = 1\n",
|
|
" return np.array(bag)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "rXq-wj-F-5DE"
|
|
},
|
|
"source": [
|
|
"##### 4.2 Funkcja **\"chat()\"** do rozmowy z botem"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 19,
|
|
"metadata": {
|
|
"id": "Je6OSZ679-KL"
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"def chat():\n",
|
|
" print(\"Możesz rozpocząć rozmowę z Botem! (type quit to stop)\")\n",
|
|
" while True: #Ciągła rozmowa\n",
|
|
" inp = input(\"Ty: \")\n",
|
|
" if inp.lower() == \"quit\": #Quit by wyjść z loopa\n",
|
|
" break\n",
|
|
"\n",
|
|
" result = model.predict([bag_of_words(inp,words)]) #Predictowanie przy pomocy wyćwiczonego modelu\n",
|
|
" result_index = np.argmax(result)\n",
|
|
" tag = labels[result_index]\n",
|
|
" \n",
|
|
" for tg in data_pl[\"intents\"]: #znalezienie poprawnego tagu do zdania\n",
|
|
" if tg['tag'] == tag:\n",
|
|
" responses = tg['responses']\n",
|
|
" \n",
|
|
" print(random.choice(responses)) #Wyprintuj losową odpowiedz z danego zbioru odpowiedzi"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {
|
|
"id": "ifvjglbO_SEA"
|
|
},
|
|
"source": [
|
|
"# 5. Rozmowa z botem!"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {
|
|
"colab": {
|
|
"base_uri": "https://localhost:8080/"
|
|
},
|
|
"id": "VZf_aCUM-Amm",
|
|
"outputId": "9e3fcf7b-b9b3-47b0-acb5-48214f07f363"
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Możesz rozpocząć rozmowę z Botem! (type quit to stop)\n",
|
|
"Ty: elo\n",
|
|
"Cześć!\n",
|
|
"Ty: w co grasz\n",
|
|
"W OSRS\n",
|
|
"Ty: nara\n",
|
|
"Hej, w czym mogę pomóc?\n",
|
|
"Ty: narazie\n",
|
|
"Narazie!\n",
|
|
"Ty: do widzenia\n",
|
|
"Mam nadzieję, że później pogadamy\n",
|
|
"Ty: dowidzenia\n",
|
|
"Narazie!\n",
|
|
"Ty: ok\n",
|
|
"Hej, w czym mogę pomóc?\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"chat()"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"colab": {
|
|
"name": "DL_Chatbot_ver_1_0.ipynb",
|
|
"provenance": [],
|
|
"toc_visible": true
|
|
},
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.8.5"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 1
|
|
}
|