allene

import os
from azure.storage.blob import BlobServiceClient,ContainerClient, BlobClient
import datetime

# Assuming your Azure connection string environment variable set.
# If not, create BlobServiceClient using trl & credentials.
#Example: https://docs.microsoft.com/en-us/python/api/azure-storage-blob/azure.storage.blob.blobserviceclient 

connection_string = os.getenv("AZURE_STORAGE_CONNECTION_STRING")

yoelrc88

#Generate root password
import random, string
password = ''.join(random.choice(string.ascii_letters + string.digits) for i in range(20))

#Download ngrok
! wget -q -c -nc https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
! unzip -qq -n ngrok-stable-linux-amd64.zip
#Setup sshd
! apt-get install -qq -o=Dpkg::Use-Pty=0 openssh-server pwgen > /dev/null
#Set root password

kauffmanes

Thanks everyone for commenting/contributing! I made this in college for a class and I no longer really use the technology. I encourage you all to help each other, but I probably won't be answering questions anymore.

This article is also on my blog: https://emilykauffman.com/blog/install-anaconda-on-wsl

Note: $ denotes the start of a command. Don't actually type this.

Steps to Install Anaconda on Windows Ubuntu Terminal

1. Install WSL (Ubuntu for Windows - can be found in Windows Store). I recommend the latest version (I'm using 18.04) because there are some bugs they worked out during 14/16 (microsoft/WSL#785)
2. Go to https://repo.continuum.io/archive to find the list of Anaconda releases
3. Select the release you want. I have a 64-bit computer, so I chose the latest release ending in x86_64.sh. If I had a 32-bit computer, I'd select the x86.sh version. If you accidentally try to install the wrong one, you'll get a warning in the terminal. I chose `Anaconda3-5.2.0-Li

bshishov

import numpy as np

EPSILON = 1e-10


def _error(actual: np.ndarray, predicted: np.ndarray):
    """ Simple error """
    return actual - predicted

delta2323

The goal of this document is to explain the basic mechanism of the dataset in Chainer and how to prepare customized dataset that can work with Trainer.

See the official document for the full detail of the specifications.

Intarface of dataset

In order to make the dataset be able to work with the Trainer, it must have two methods:

• __getitem__, which is used for indexing like dataset[i] or slicing like dataset[i:j]
• __len__ , which enables us to feed it to len()

asielen

jukworks

import edu.emory.mathcs.jtransforms.fft.DoubleFFT_1D;

public class FftTest {
    public static void main(String[] args) {
        double[] input = new double[]{
                0.0176,
                -0.0620,
                0.2467,
                0.4599,
                -0.0582,