alper111

import torch
import torchvision

class VGGPerceptualLoss(torch.nn.Module):
    def __init__(self, resize=True):
        super(VGGPerceptualLoss, self).__init__()
        blocks = []
        blocks.append(torchvision.models.vgg16(pretrained=True).features[:4].eval())
        blocks.append(torchvision.models.vgg16(pretrained=True).features[4:9].eval())
        blocks.append(torchvision.models.vgg16(pretrained=True).features[9:16].eval())

lostsh

Including iframe of an github (gists) embled script

So for include a github embled iframe into an iframe You may use hex code

see this exemple :
The github embled link : <script src="https://gist.github.com/lostsh/dfb8a51aeb3ad5d7e3cefbc66d72fa53.js"></script> and ths iframe who contain this embled :

tvst

"""Hack to add per-session state to Streamlit.

Usage
-----

>>> import SessionState
>>>
>>> session_state = SessionState.get(user_name='', favorite_color='black')
>>> session_state.user_name
''

karpathy

"""
stable diffusion dreaming
creates hypnotic moving videos by smoothly walking randomly through the sample space

example way to run this script:

$ python stablediffusionwalk.py --prompt "blueberry spaghetti" --name blueberry

to stitch together the images, e.g.:
$ ffmpeg -r 10 -f image2 -s 512x512 -i blueberry/frame%06d.jpg -vcodec libx264 -crf 10 -pix_fmt yuv420p blueberry.mp4

trygvebw

import torch
import numpy as np
import k_diffusion as K

from PIL import Image
from torch import autocast
from einops import rearrange, repeat

def pil_img_to_torch(pil_img, half=False):
    image = np.array(pil_img).astype(np.float32) / 255.0

a-r-r-o-w

#!/bin/bash

compile_flags=("" "--compile")
fuse_qkv_flags=("" "--fuse_qkv")
# quantizations=("fp16" "bf16" "fp8" "fp8_e4m3" "fp8_e5m2" "fp6" "int8wo" "int8dq" "int4dq" "int4wo" "autoquant" "sparsify")
quantizations=("fp16" "bf16" "fp6" "int8wo" "int8dq" "int4dq" "int4wo" "autoquant" "sparsify")
device="cuda"

# Check if completed.txt exists and read it into an array
if [ -f completed.txt ]; then