Author: Deep Learner

Slack

Markov-chain based chatbot which uses Slack messages as its corpus

Friendbot is a Markov-chain based chatbot which uses Slack messages as its corpus. It reads in messages from a Slack data export, generates a corpus from them, and feeds this to a markov chain generator to naively simulate a conversation. It is built with Flask, served by Gunicorn, cached by Redis, and run in Docker. The sentences which it generates can be accessed via an API which is designed to connect to the existing Slack API. Installation Download the docker-compose.yaml […]

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Structure

My notes on Data structure and Algos in golang implementation and python

My notes on Data structure and Algos in golang implementation and python Arrays Advantages of array Reading and writing is O(1) Disadvantages of array Insertion and deletion is O(n) Arrays are not dynamic If you need to store an extra element, you would have to create a new array and copy all the elements over. O(n) List Slicing in python [start:stop:step] Reverse a list list[::-1] LinkedList Linked lists are great for problems that require arbitrary insertion. Dynamic arrays allow inserting […]

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Voice

A package that assists in creating Voice Applications for Magenta Voice Platform

Magenta Voice Skill SDK for Python is a package that assists in creating Voice Applications for Magenta Voice Platform. About This is a reworked stack with explicit async/await concurrency and based on FastAPI ASGI framework. Old stable (Bottle/Gevent) 0.xx branch Installation Runtime Runtime installation: python -m pip install skill-sdk. Runtime (full) Runtime installation with Prometheus metrics exporter and distributed tracing adapter: python -m pip install skill-sdk[all]. Development Development installation: python -m pip install skill-sdk[dev]. Quickstart To bootstrap a new project, […]

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Asyncio

RabbitMQ asynchronous connector library for Python with built in RPC support

bunny-storm RabbitMQ connector library for Python that is fully integrated with the aio-pika framework. Introduction BunnyStorm is here to simplify working with RabbitMQ while using aio-pika.This library offers an asynchronous implementation of a RabbitMQ connector which is fully integrated with asyncio.BunnyStorm provides an all-in-one adapter with the following functionalities: publish – Publish a message. receive – Consume messages from a queue. Can automatically reply to desired routes if the received messagecontains a “reply_to” property. rpc – Implement RPC (Remote procedure […]

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PyTorch

Pushing the Limit of Post-Training Quantization by Block Reconstruction

Pytorch implementation of BRECQ, ICLR 2021 @inproceedings{ li&gong2021brecq, title={BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction}, author={Yuhang Li and Ruihao Gong and Xu Tan and Yang Yang and Peng Hu and Qi Zhang and Fengwei Yu and Wei Wang and Shi Gu}, booktitle={International Conference on Learning Representations}, year={2021}, url={https://openreview.net/forum?id=POWv6hDd9XH} } Pretrained models We provide all the pretrained models and they can be accessed via torch.hub For example: use res18 = torch.hub.load(‘yhhhli/BRECQ’, model=’resnet18′, pretrained=True) to get the pretrained ResNet-18 […]

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VSCode

Raspberry Pi Pico support for VS Code

Pico-Go provides code auto-completion and allows you to communicate with your Raspberry Pi Pico board using the built-in REPL console. Run a single file on your board, sync your entire project or directly type and execute commands. This software is originally a derivative product of Pymakr by Pycom Ltd under the terms of its GNU GPL Version 3+ license but it has now received significant rewrites. Non-RP2040 boards are not supported but may still work. Works with macOS, Linux, and […]

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Tutorial

Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification

Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you if: you’re new to few-shot learning and want to learn; or you’re looking for reliable, clear and easily usable code that you can use for your projects. Don’t get lost in large repositories with hundreds of methods and no explanation on how to use them. Here, we want each line of code to be covered by a tutorial. What’s in there?

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Rank

Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments

This is the Tensorflow implementation of ICLR 2021 paper Rank the Episodes: A Simple Approach for Exploration in Procedurally-Generated Environments. We propose a simple method RAPID for exploration through scroring the previous episodes and reproducing the good exploration behaviors with imitation learning. The implementation is based on OpenAI baselines. For all the experiments, add the option –disable_rapid to see the baseline result. RAPID can achieve better performance and sample efficiency than state-of-the-art exploration methods on MiniGrid environments. Cite This Work […]

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Python

Using Data Classes in Python

One new and exciting feature that came out in Python 3.7 was the data class. A data class is a class typically containing mainly data, although there aren’t really any restrictions. With data classes, you don’t have to write boilerplate code to get proper initialization, representation, and comparisons for your objects. In this course, you’ll learn how to: Define your own data classes Add default values to the fields in your data class Customize the ordering of data class objects […]

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