import pickle import sys from tensorboardX import SummaryWriter import time import torch import torch.nn as nn from config import SearchConfig from data_loader import load_dataset import genotypes as gts from search_cnn import SearchCNN import utils config = SearchConfig() config.alpha_dir = os.path.join(config.stage_dir, "alphas") os.system("mkdir -p {}".format(config.alpha_dir)) device = torch.device("cuda") # tensorboard writer = SummaryWriter(log_dir=config.log_dir) writer.add_text("config", config.as_markdown(), 0) logger = utils.get_logger( os.path.join(config.log_dir, "{}_{}.log".format( config.name, config.stage))) config.print_args(logger.info) def train(data_loader,
import os import pickle import sys from tensorboardX import SummaryWriter import time import torch import torch.nn as nn from augment_cnn import AugmentCNN from config import SearchConfig from data_loader import load_dataset import utils config = SearchConfig() config.alpha_dir = os.path.join(config.save_dir, "search2/alphas") device = torch.device("cuda") # tensorboard writer = SummaryWriter(log_dir=config.log_dir) writer.add_text("config", config.as_markdown(), 0) logger = utils.get_logger( os.path.join(config.log_dir, "{}_{}.log".format( config.name, config.stage))) config.print_args(logger.info) def train(data_loader, model, criterion, optimizer, epoch): loss = utils.AverageMeter()