| import argparse | |
| import logging | |
| from logging import Filter | |
| from logging.handlers import QueueHandler, QueueListener | |
| import torch | |
| import torch.distributed as dist | |
| import torch.multiprocessing as mp | |
| from torch.multiprocessing import Queue |
~/.bash_aliases file.function gdrive_download () {
CONFIRM=$(wget --quiet --save-cookies /tmp/cookies.txt --keep-session-cookies --no-check-certificate "https://docs.google.com/uc?export=download&id=$1" -O- | sed -rn 's/.*confirm=([0-9A-Za-z_]+).*/\1\n/p')
wget --load-cookies /tmp/cookies.txt "https://docs.google.com/uc?export=download&confirm=$CONFIRM&id=$1" -O $2
rm -rf /tmp/cookies.txt
}
| model.zero_grad() # Reset gradients tensors | |
| for i, (inputs, labels) in enumerate(training_set): | |
| predictions = model(inputs) # Forward pass | |
| loss = loss_function(predictions, labels) # Compute loss function | |
| loss = loss / accumulation_steps # Normalize our loss (if averaged) | |
| loss.backward() # Backward pass | |
| if (i+1) % accumulation_steps == 0: # Wait for several backward steps | |
| optimizer.step() # Now we can do an optimizer step | |
| model.zero_grad() # Reset gradients tensors | |
| if (i+1) % evaluation_steps == 0: # Evaluate the model when we... |
UPDATED 22.11.2022
It's been two years since the last update, so here's the updated working script as per the comments below.
Thanks to BryanHaley for this.
setInterval(function () {
video = document.getElementsByTagName('ytd-playlist-video-renderer')[0];
video.querySelector('#primary button[aria-label="Action menu"]').click();
CODE!