uranusjr

依賴解析器 Alpha 版本：相關資訊與測試指引

摘譯 The alpha dependency resolver: context and how to test，最後更新於 2020-04-21 03:14 UTC+8。

pip 20.1 中包含了一個 alpha 版本的依賴解析器全新實作。這個功能尚不穩定，不適合日常使用。本文將根據我們已知的測試需求滾動更新；若有任何回饋，請使用這個表單。

如之前公告，pip 開發團隊正在實作一個新的依賴解析器。我們在即日起釋出的新版本 pip 中包含了一個初步版本（alpha），讓使用者進行測試。

由於該功能預設關閉，要進行測試，需要在使用 pip 時加上 --unstable-feature=resolver。正常的 pip 使用情境不會受到新的解析器影響。

peteflorence

Here's a simple implementation of bilinear interpolation on tensors using PyTorch.

I wrote this up since I ended up learning a lot about options for interpolation in both the numpy and PyTorch ecosystems. More generally than just interpolation, too, it's also a nice case study in how PyTorch magically can put very numpy-like code on the GPU (and by the way, do autodiff for you too).

For interpolation in PyTorch, this open issue calls for more interpolation features. There is now a nn.functional.grid_sample() feature but at least at first this didn't look like what I needed (but we'll come back to this later).

In particular I wanted to take an image, W x H x C, and sample it many times at different random locations. Note also that this is different than upsampling which exhaustively samples and also doesn't give us fle

PurpleBooth

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

chrisgillis

package main

import (
    "fmt"
	  "log"
    "net"
    "net/mail"
	  "net/smtp"
    "crypto/tls"
)

evildmp

This document has now been incorporated into the uWSGI documentation:

http://uwsgi-docs.readthedocs.org/en/latest/tutorials/Django_and_nginx.html

Set up Django, nginx and uwsgi

Steps with explanations to set up a server using: