[WIP]init trainer log

[littletomatodonkey]

att, the log will also be saved into os.path.join(save_path, "train.log")

• usage

import time
import auto_log
from auto_log import TrainerLogger

logger = TrainerLogger("./output")

logger.add_record_info("acc")

run_cost = time.time()
reader_cost = time.time()
loss = 0.0
for idx in range(100):
    time.sleep(0.001)
    reader_cost = time.time() - reader_cost
    run_cost = time.time()
    time.sleep(0.01)
    loss = (100 - idx) * 0.01
    run_cost = time.time() - run_cost
    
    logger.update(
        32,
        reader_cost,
        run_cost,
        loss,
        acc = idx * 0.1,
    )
    if idx % 10 == 0:
        logger.log(0, idx)
    
    reader_cost = time.time()
    
logger.log(0)

• output

[2021/12/04 05:16:12] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010657 sec, avg_batch_cost: 0.0111225 sec, loss: 1.0000000 , acc: 0.0000000 , avg_ips: 2877.0600416 images/sec
[2021/12/04 05:16:12] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010534 sec, avg_batch_cost: 0.0111082 sec, loss: 0.9450000 , acc: 0.5500000 , avg_ips: 2880.7589432 images/sec
[2021/12/04 05:16:12] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010544 sec, avg_batch_cost: 0.0111082 sec, loss: 0.8450000 , acc: 1.5500000 , avg_ips: 2880.7651263 images/sec
[2021/12/04 05:16:12] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010545 sec, avg_batch_cost: 0.0111093 sec, loss: 0.7450000 , acc: 2.5500000 , avg_ips: 2880.4807321 images/sec
[2021/12/04 05:16:12] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010543 sec, avg_batch_cost: 0.0111051 sec, loss: 0.6450000 , acc: 3.5500000 , avg_ips: 2881.5567798 images/sec
[2021/12/04 05:16:13] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010532 sec, avg_batch_cost: 0.0111079 sec, loss: 0.5450000 , acc: 4.5500000 , avg_ips: 2880.8331419 images/sec
[2021/12/04 05:16:13] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010535 sec, avg_batch_cost: 0.0111083 sec, loss: 0.4450000 , acc: 5.5500000 , avg_ips: 2880.7403941 images/sec
[2021/12/04 05:16:13] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010543 sec, avg_batch_cost: 0.0111100 sec, loss: 0.3450000 , acc: 6.5500000 , avg_ips: 2880.2952878 images/sec
[2021/12/04 05:16:13] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010542 sec, avg_batch_cost: 0.0111101 sec, loss: 0.2450000 , acc: 7.5500000 , avg_ips: 2880.2582019 images/sec
[2021/12/04 05:16:13] root INFO: [epoch 0, batch_idx 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010561 sec, avg_batch_cost: 0.0111109 sec, loss: 0.1450000 , acc: 8.5500000 , avg_ips: 2880.0604261 images/sec
[2021/12/04 05:16:13] root INFO: [end of epoch 0][TRAIN]avg_samples: 32.0 , avg_reader_cost: 0.0010601 sec, avg_batch_cost: 0.0111144 sec, loss: 0.5050000 , acc: 4.9500000 , avg_ips: 2879.1405077 images/sec