Spaces:
Running
on
Zero
Running
on
Zero
import os | |
import numpy as np | |
import sys | |
import json | |
def read_text_lines(filepath): | |
with open(filepath, 'r') as f: | |
lines = f.readlines() | |
lines = [l.rstrip() for l in lines] | |
return lines | |
def check_path(path): | |
if not os.path.exists(path): | |
os.makedirs(path, exist_ok=True) # explicitly set exist_ok when multi-processing | |
def save_command(save_path, filename='command_train.txt'): | |
check_path(save_path) | |
command = sys.argv | |
save_file = os.path.join(save_path, filename) | |
# Save all training commands when resuming training | |
with open(save_file, 'a') as f: | |
f.write(' '.join(command)) | |
f.write('\n\n') | |
def save_args(args, filename='args.json'): | |
args_dict = vars(args) | |
check_path(args.checkpoint_dir) | |
save_path = os.path.join(args.checkpoint_dir, filename) | |
# Save all training args when resuming training | |
with open(save_path, 'a') as f: | |
json.dump(args_dict, f, indent=4, sort_keys=False) | |
f.write('\n\n') | |
def int_list(s): | |
"""Convert string to int list""" | |
return [int(x) for x in s.split(',')] | |