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()
