AWS Lambda with Docker – revisited

There are various ways to leverage docker to develop AWS lambda serverless functions. One recent method is to deploy Python Lambda functions with container images (as specified here). Another method is to develop the Lambda package from within an Amazon Linux docker container and then upload it to AWS Lambda (more details here). A summary …

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Linux on Windows 10 via Docker

Wanting to run Linux command line under windows usually brings you to one of two options: Install WSL (Windows Subsystem for Linux) – the main advantage here is performance optimizations made by Microsoft to take the most advantage of the hardware and OS infrastructure. Install Docker for Windows 10 and then create a Linux container …

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Training “cat or dog” on Windows without GPU

I was curious to see how much slower the training of chapter 1 of would be on my GPU-less home desktop vs. a basic cloud GPU servers. The first issue was to get the code running after installing torch, torchvision and fastai modules. Apparently, there are some code modifications to make to get things …

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cannot import name ‘mobilenet_v2’ from ‘torchvision.models’

This was the error I received when trying to import fastbook to study the excellent course. I had Python 3.9.1 installed and used pip to install the latest versions of torch, torchvision, and fastai To spare the reader from boring war stories, here’s the bottom line: Download the latest version of torchvision for your …

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Compiling PHP 7.3 with MySQL support for AWS Lambda

This is probably easier to do for PHP 7.4, but I wanted PHP 7.3 to make sure everything is compatible with existing code. The code below assumes you are doing this in an interactive shell in a Docker container build for creating binaries for AWS Lambda. Doing this is explained here First, install the necessary …

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Duplicated log lines using Python in AWS Lambda

The short version: logname = ‘processing’ formatter = logging.Formatter(fmt=’%(asctime)s %(levelname)-8s %(message)s’, datefmt=’%Y-%m-%d %H:%M:%S’) handler = logging.StreamHandler() handler.setFormatter(formatter) logger = logging.getLogger(logname) logger.setLevel(logging.DEBUG) logger.handlers = [] # === Make sure to add this line logger.addHandler(handler) logger.propagate = False # === and this line For details, check out this link