Tudor

When Scott and Nicole Delmoro renovated their 1939 Park Hill Tudor a decade ago to add 1,300 square feet, they planned to stay in the home forever. But when Phillips 66 purchased Scott Delmoro’s employer DCP Midstream this year, he was promoted to interim chief financial officer and transferred to Houston. So the family listed the 6,281-square-foot house on the 6400 block of East 17th Avenue Parkway for $3.8 million. “We love the house,” Delmoro said. “We never thought we’d leave it but we need to relocate.” The Delmoros…

Designed by Fisher & Fisher, who also designed the Phipps Mansion on the 2300 block of East Alameda Avenue, was built in 1932 as a wedding gift for former Gov. John Evans’ eldest daughter. Since then, the 8,000-square-foot mansion has been extensively renovated but retains many original details. Listed at $6.8 million, the mansion sits inside a private enclave with a security gate on 1.3 acres overlooking the Denver Country Club and with views of the downtown skyline. Owned by retired attorney Gary Pierson and his…

If you are searching for a way to organize, manage and log the steps and operations during a training process and don’t want to use PyTorch Lightning, look no morePhoto by Marcel Strauß on UnsplashWe are going to split the training manager’s logic into several stages by following the classic hierarchy of a training setup:The most high-level stage is the training run, which covers the entire training for one set of hyper-parameters (number of epochs, model-config, learning rate, optimizer, etc.)Next, we have the epoch,…

This article will discuss the reasoning and the steps of implementing a PyTorch dataset that uses memory-mapped filesPhoto by Eléonore Kemmel on UnsplashIntroductionWhen training a neural network one of the most common speed-related bottlenecks is represented by the data loading module. If we are bringing the data over the network, besides prefetching and caching there aren’t any other easy optimizations that we can apply.However, if the data is in a local storage we can optimize the file reading operations by combining…

This article will show you the challenges, components, and steps you need to make/overcome to create a basic deep learning frameworkPhoto by Vlado Paunovic on UnsplashLet's start by defining what we want to create and figure out what components we need: we want a framework that supports automatic differentiation to compute the gradient for several operations, a standardized way to build neural network layers using the aforementioned operations with a modular approach to combine them in a larger neural network model, and…