UmerHA

UmerHA

dirs = ['^','>','v','<']
dir_map = {'^':0,'>':1,'v':2,'<':3}
delta = [(-1,0),(0,1),(1,0),(0,-1)]

def parse_grid(grid_str):
    grid = [list(line) for line in grid_str.split('\n')]
    rows, cols = len(grid), len(grid[0])
    gpos, gdir = None, None
    for r in range(rows):
        for c in range(cols):

UmerHA

class Snail:
  def __init__(self):
    self.speed = 0.001
    self.pos = 0
  
  def move(self):
    self.pos += self.speed
    print(f'moved to {self.pos}')
    
garry = Snail()

UmerHA

import os
import yaml
from pprint import pprint

def dir_structure(dir_path, nested=False):
    result = []

    if nested:
        # return directory structure as nested dict
        for item in os.listdir(dir_path):

UmerHA

# based on github.com/weifeng-Chen/prompt2prompt/ - shoutout to Weifeng Cheng!

# Create pipeline and run it once

import torch
import numpy as np
import matplotlib.pyplot as plt
from diffusers.pipelines import Prompt2PromptPipeline

pipe = Prompt2PromptPipeline.from_pretrained("CompVis/stable-diffusion-v1-4").to("cuda")