nousr’s gists

nousr / txt2img_k.py

Created September 29, 2022 02:23

	import argparse, os, sys, glob
	import torch
	import torch.nn as nn
	import numpy as np
	from omegaconf import OmegaConf
	from PIL import Image
	from tqdm import tqdm, trange
	from itertools import islice
	from einops import rearrange
	from torchvision.utils import make_grid

nousr / aws s3 ls embeddings

Last active October 8, 2022 04:42

nousr / results.json

Last active October 20, 2022 02:44

vit-h-14 embeddings sanity check

	[
	{
	"caption": "View Over Pyrenees Mountains, Spain",
	"url": "https://static1.bigstockphoto.com/thumbs/0/0/1/large2/100000799.jpg"
	},
	{
	"caption": "Mountain landscape with deer and forest at sunset",
	"url": "https://cdn.xxl.thumbs.canstockphoto.com/vector-illustration-of-mountain-landscape-with-deer-and-forest-at-sunset-clip-art-vector_csp56740268.jpg"
	},
	{

nousr / hf_upload.py

Created October 25, 2022 21:52

	import os
	import fsspec
	import click
	import huggingface_hub as hf_hub
	from time import perf_counter
	from braceexpand import braceexpand
	import multiprocessing as mp
	from tqdm import tqdm

nousr / prior.sh

Last active October 25, 2022 23:53

	LOCAL_ID=$SLURM_LOCALID
	GLOBAL_RANK=$SLURM_PROCID
	NODE_ID=$SLURM_NODEID
	NUM_PROCS=$SLURM_NTASKS
	CPUS=$SLURM_CPUS_PER_GPU
	NUM_NODES=$SLURM_NNODES
	MASTER_ADDR=$(scontrol show hostnames "$SLURM_JOB_NODELIST" \| head -n 1)

	if [ $GLOBAL_RANK == 0 ]
	then

nousr / train_t5_prior.py

Created November 11, 2022 19:57

	import wandb
	import torch
	from dalle2_pytorch import (
	T5OpenClipAdapter,
	DiffusionPriorNetwork,
	DiffusionPrior,
	)
	from dalle2_pytorch.trainer import DiffusionPriorTrainer
	from transformers import T5Tokenizer
	from accelerate import Accelerator

nousr / indexer.sh

Last active November 18, 2022 23:30

	#!/bin/bash

	# step 1: get environment variables
	# step 2: setup rank 0 to be the master and start the indexing python file (the last two operations happen in parallel)
	# step 3: setup rank 1-N to be the workers and start the worker script (they then will listen for work from the master)

	# get environment variables
	GLOBAL_RANK=$SLURM_PROCID
	CPUS=$SLURM_CPUS_PER_TASK
	MEM=$SLURM_MEM_PER_NODE # seems to be in MB

nousr / styles.csv

Created December 7, 2022 20:02

We can make this file beautiful and searchable if this error is corrected: Unclosed quoted field in line 4.

	name,prompt,negative_prompt
	None,,
	MDJ_style_base,"an extremely realistic digital painting of a (futuristic an alleyway) street in the style of cyberpunk, a photograph of a cyberpunk street alley at sunset, digital art trending on artstation, ((pixel art)), light rays shining","blurry, bad resolution, low quality, watermarked image, america, jpeg artifacts, background, words, font, text, boring, robot, human, full body, people in a street, purple"
	MDJ_street_car,"an extremely realistic digital painting of a (cyberpunk volkswagen r32) on the street in the style of cyberpunk, a photograph of a cyberpunk street alley at night, digital art trending on artstation, ((pixel art)), light rays shining","bad resolution, low quality, watermarked image, human, ((simple)), [dark], blurry, bad resolution, low quality, ((watermarked image)), america, jpeg artifacts, words, font, text, boring, robot, human, full body, people in a street stock photo AND alamy, shutterstock, pixabay, flickr AND picture frame, bad perspective,

nousr / load_safety.py

Created January 25, 2023 20:44

	@lru_cache(maxsize=None)
	def load_safety_model(clip_model):
	"""load the safety model"""
	import torch # pylint: disable=import-outside-toplevel
	import autokeras as ak # pylint: disable=import-outside-toplevel
	from tensorflow.keras.models import load_model # pylint: disable=import-outside-toplevel

	class H14_NSFW_Detector(nn.Module):
	def __init__(self, input_size=1024):
	super().__init__()

nousr / clap_load_timing.py

Last active February 16, 2023 01:17

	import torch
	import webdataset as wds
	from typing import Union, Sequence
	from time import perf_counter
	from accelerate import Accelerator

	def process(src):
	"""
	Filter empty samples from the clap dataset.

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