Xiuyu-Li

Python     1 hr 18 mins   ██████████▊░░░░░░░░░░  51.5%
HTML       45 mins        ██████▎░░░░░░░░░░░░░░  30.1%
Bash       19 mins        ██▋░░░░░░░░░░░░░░░░░░  12.6%
YAML       7 mins         ▉░░░░░░░░░░░░░░░░░░░░   4.6%
JSON       1 min          ▏░░░░░░░░░░░░░░░░░░░░   0.9%

Xiuyu-Li

#!/bin/bash
#SBATCH -J <name>  # Job name
#SBATCH -o <filename>%j.log  # Name of stdout output file (%j expands to jobId)
#SBATCH -e <filename>%j.err  # Name of stderr output file
#SBATCH --mail-type=ALL
#SBATCH --mail-user=<netid>@cornell.edu
#SBATCH -N 1  # Total number of CPU nodes requested
#SBATCH -n 4  # Total number of CPU cores requrested
#SBATCH -t 24:00:00  # Run time (hh:mm:ss)
#SBATCH --mem=20000  # CPU Memory pool for all cores

Xiuyu-Li

import numpy as np
from typing import Tuple
import tensorflow as tf
import torch
import torchvision
import torchvision.transforms as transforms

# Set verbosity.
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)