Chatbot in 200 lines of code using TensorLayer

Last update: Dec 17, 2022

Overview

Seq2Seq Chatbot

This is a 200 lines implementation of Twitter/Cornell-Movie Chatbot, please read the following references before you read the code:

Prerequisites

Python 3.6
TensorFlow >= 2.0
TensorLayer >= 2.0

Model

Training

python3 main.py

Results

Query > happy birthday have a nice day
 > thank you so much
 > thank babe
 > thank bro
 > thanks so much
 > thank babe i appreciate it
Query > donald trump won last nights presidential debate according to snap online polls
 > i dont know what the fuck is that
 > i think he was a racist
 > he is not a racist
 > he is a liar
 > trump needs to be president

Comments

[WIP] Fix error in PR #16 Inference mode and TF compatibility

Hey @pskrunner14

Thanks for the great PR! We have rolled back the PR you recently submitted as the PR contains the error. Could you please have a look on it and we can merge it again? You can create a PR from your fork again or directly modify from here.

Cheers, Luo

opened by luomai 6
No module named 'tensorlayer.models.seq2seq'

Can someone share with me how to resolve this error? Thanks.

Traceback (most recent call last): File "D:\ChatBot\seq2seq-chatbot-master\main.py", line 11, in from tensorlayer.models.seq2seq import Seq2seq ModuleNotFoundError: No module named 'tensorlayer.models.seq2seq'

opened by geongm 5
Change seq2seq import names

Had the #37 problem. It looks like on in current version of tensorlayer import names changed.

These imports work with tensorflow 2.0.0-beta1 tensorlayer 2.1.0

opened by egens 4
TL2.0

Update model compatible with TensorLayer2.0. Rewrite the loss. cross_entropy_seq_with_mask and cross_entropy_seq. Need to run to see if it converges and produce desirable results

opened by ArnoldLIULJ 3
Inference mode and TF compatibility
Moved Inference code to a function.

Added optional arguments including running script in inference mode [usage python main.py --help].

Added tqdm progress bar for info while training.

Made the code compatible with TF v1.10.0 and TL v1.10.1.

Changed tf.contrib.rnn.BasicLSTMCell to tf.nn.rnn_cell.LSTMCell since the former is deprecated.

Moved session config to global scope.

Refactored code into relevant functions and reordered them so that the higher-level ones appear earlier in the code.

Renamed script to main.py for ease of use.

Updated README to add training and inference usage commands.

Added requirements.txt file.

Changed n.npz to model.npz since it is more standard.

Note: Fixes #12 and #15
opened by pskrunner14 3
Using the Chatbot

Hi there,

I trained the data for a few days and now the samples are returning good results to the predefined "Happy Birthday" and "Trump" requests.

Great job by you. Thanks so far.

Do you already have a small python program for using the chatbot? If I write a message, the chatbot should return a single answer.

Thanks Chris

opened by cpro90 3
Training is taking too much time

Training on CPU is taking too much time, so do you have any estimate how much time it will take? I have executed this 12 hours ago and now i am on just "Epoch[2/50] step:[600/2852] loss:5.684645 took:9.62770s". Can you please help me to boost this training.

opened by aqeellegalinc 3
Inference mode and TF compatibility (#16)

@pskrunner14

We have rolled back the PR you recently submitted as the PR contains the error. Could you please have a look on it and we can merge it again?

opened by luomai 2
Fixes TL global variables initializer deprecated issue and Code readability

Fixed TensorLayer initialize global vars deprecated issue #13, changed learning rate to 0.001 for faster convergence, improved code readability and removed redundant comments and code

opened by pskrunner14 2
Can't import data

ModuleNotFoundError Traceback (most recent call last) in () 8 9 ###============= prepare data ---> 10 from data.twitter import data 11 metadata, idx_q, idx_a = data.load_data(PATH='data/twitter/') # Twitter 12 # from data.cornell_corpus import data

ModuleNotFoundError: No module named 'data.twitter'

opened by georgexli 2
No module named twitter

File "main_simple_seq2seq.py", line 18, in from data.twitter import data ImportError: No module named twitter

Did I miss some files？ Can you please help me？Many thanks^ o^

opened by MProtoss 1
ModuleNotFoundError: No module named 'data.twitter'; 'data' is not a package

I am trying to write code for Chat Box, but encountering the error "ModuleNotFoundError: No module named 'data.twitter'; 'data' is not a package" when trying to execute "from data.twitter import data".

Please suggest , how to resolve the issue?

note: I am working on following environment: Python is 3.6 V Tensorflow : 2.0 Tensorlayer: 2.2 python-twitter

opened by mhmitalihalder 0
How could I get the "thought vector" using TensorLayer?

I am using the seq2seq model as an autoencoder. Given a test paragraph, I'd like to get the thought vector (using the terminology in the figure of README.md).

opened by munichong 0

Releases(0.1)

0.1(Sep 6, 2017)

Source code(tar.gz)
Source code(zip)

Owner

TensorLayer Community

A neutral open community to promote AI technology.

GitHub Repository https://github.com/tensorlayer/tensorlayer

QHack—the quantum machine learning hackathon

Official repo for QHack—the quantum machine learning hackathon

72 Dec 21, 2022

Image reconstruction done with untrained neural networks.

PyTorch Deep Image Prior An implementation of image reconstruction methods from Deep Image Prior (Ulyanov et al., 2017) in PyTorch. The point of the p

192 Nov 30, 2022

Learning to Predict Gradients for Semi-Supervised Continual Learning

Learning to Predict Gradients for Semi-Supervised Continual Learning Code for project: "Learning to Predict Gradients for Semi-Supervised Continual Le

2 Mar 05, 2022

Denoising Diffusion Probabilistic Models

Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel Paper: https://arxiv.org/abs/2006.11239 Website: https://hojonathanho.g

1.5k Jan 08, 2023

Tensorflow implementation of ID-Unet: Iterative Soft and Hard Deformation for View Synthesis.

ID-Unet: Iterative-view-synthesis(CVPR2021 Oral) Tensorflow implementation of ID-Unet: Iterative Soft and Hard Deformation for View Synthesis. Overvie

17 Aug 23, 2022

Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion

Improving Generalization Bounds for VC Classes Using the Hypergeometric Tail Inversion Preface This directory provides an implementation of the algori

0 Nov 03, 2021

[WACV21] Code for our paper: Samuel, Atzmon and Chechik, "From Generalized zero-shot learning to long-tail with class descriptors"

DRAGON: From Generalized zero-shot learning to long-tail with class descriptors Paper Project Website Video Overview DRAGON learns to correct the bias

25 Dec 06, 2022

RoFormer_pytorch

PyTorch RoFormer 原版Tensorflow权重(https://github.com/ZhuiyiTechnology/roformer) chinese_roformer_L-12_H-768_A-12.zip (提取码：xy9x) 已经转化为PyTorch权重 chinese_r

283 Dec 12, 2022

Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations

HierarchicyBandit Introduction This is the implementation of WSDM 2022 paper : Show Me the Whole World: Towards Entire Item Space Exploration for Inte

5 Sep 09, 2022

SEJE Pytorch implementation

SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. Contents Inst

0 Oct 21, 2021

this is a lite easy to use virtual keyboard project for anyone to use

virtual_Keyboard this is a lite easy to use virtual keyboard project for anyone to use motivation I made this for this year's recruitment for RobEn AA

3 Oct 23, 2021

Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.

MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data

6 Jan 02, 2023

Keras-tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation（Unfinished）

Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas

645 Dec 29, 2022

This is an open-source toolkit for Heterogeneous Graph Neural Network(OpenHGNN) based on DGL [Deep Graph Library] and PyTorch.

519 Jan 02, 2023