File size: 6,860 Bytes
52a9452 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 |
import os
import logging
import functools
import json
import time
from datetime import datetime
from tensorboardX import SummaryWriter
import yaml
import cv2
import numpy as np
from concern.config import Configurable, State
class Logger(Configurable):
SUMMARY_DIR_NAME = 'summaries'
VISUALIZE_NAME = 'visualize'
LOG_FILE_NAME = 'output.log'
ARGS_FILE_NAME = 'args.log'
METRICS_FILE_NAME = 'metrics.log'
database_dir = State(default='./outputs/')
log_dir = State(default='workspace')
verbose = State(default=False)
level = State(default='info')
log_interval = State(default=100)
def __init__(self, **kwargs):
self.load_all(**kwargs)
self._make_storage()
cmd = kwargs['cmd']
self.name = cmd['name']
self.log_dir = os.path.join(self.log_dir, self.name)
try:
self.verbose = cmd['verbose']
except:
print('verbose:', self.verbose)
if self.verbose:
print('Initializing log dir for', self.log_dir)
if not os.path.exists(self.log_dir):
os.makedirs(self.log_dir)
self.message_logger = self._init_message_logger()
summary_path = os.path.join(self.log_dir, self.SUMMARY_DIR_NAME)
self.tf_board_logger = SummaryWriter(summary_path)
self.metrics_writer = open(os.path.join(
self.log_dir, self.METRICS_FILE_NAME), 'at')
self.timestamp = time.time()
self.logged = -1
self.speed = None
self.eta_time = None
def _make_storage(self):
application = os.path.basename(os.getcwd())
storage_dir = os.path.join(
self.database_dir, self.log_dir, application)
if not os.path.exists(storage_dir):
os.makedirs(storage_dir)
if not os.path.exists(self.log_dir):
os.symlink(storage_dir, self.log_dir)
def save_dir(self, dir_name):
return os.path.join(self.log_dir, dir_name)
def _init_message_logger(self):
message_logger = logging.getLogger('messages')
message_logger.setLevel(
logging.DEBUG if self.verbose else logging.INFO)
formatter = logging.Formatter(
'[%(levelname)s] [%(asctime)s] %(message)s')
std_handler = logging.StreamHandler()
std_handler.setLevel(message_logger.level)
std_handler.setFormatter(formatter)
file_handler = logging.FileHandler(
os.path.join(self.log_dir, self.LOG_FILE_NAME))
file_handler.setLevel(message_logger.level)
file_handler.setFormatter(formatter)
message_logger.addHandler(std_handler)
message_logger.addHandler(file_handler)
return message_logger
def report_time(self, name: str):
if self.verbose:
self.info(name + " time :" + str(time.time() - self.timestamp))
self.timestamp = time.time()
def report_eta(self, steps, total, epoch):
self.logged = self.logged % total + 1
steps = steps % total
if self.eta_time is None:
self.eta_time = time.time()
speed = -1
else:
eta_time = time.time()
speed = eta_time - self.eta_time
if self.speed is not None:
speed = ((self.logged - 1) * self.speed + speed) / self.logged
self.speed = speed
self.eta_time = eta_time
seconds = (total - steps) * speed
hours = seconds // 3600
minutes = (seconds - (hours * 3600)) // 60
seconds = seconds % 60
print('%d/%d batches processed in epoch %d, ETA: %2d:%2d:%2d' %
(steps, total, epoch,
hours, minutes, seconds), end='\r')
def args(self, parameters=None):
if parameters is None:
with open(os.path.join(self.log_dir, self.ARGS_FILE_NAME), 'rt') as reader:
return yaml.load(reader.read())
with open(os.path.join(self.log_dir, self.ARGS_FILE_NAME), 'wt') as writer:
yaml.dump(parameters.dump(), writer)
def metrics(self, epoch, steps, metrics_dict):
results = {}
for name, a in metrics_dict.items():
results[name] = {'count': a.count, 'value': float(a.avg)}
self.add_scalar('metrics/' + name, a.avg, steps)
result_dict = {
str(datetime.now()): {
'epoch': epoch,
'steps': steps,
**results
}
}
string_result = yaml.dump(result_dict)
self.info(string_result)
self.metrics_writer.write(string_result)
self.metrics_writer.flush()
def named_number(self, name, num=None, default=0):
if num is None:
return int(self.has_signal(name)) or default
else:
with open(os.path.join(self.log_dir, name), 'w') as writer:
writer.write(str(num))
return num
epoch = functools.partialmethod(named_number, 'epoch')
iter = functools.partialmethod(named_number, 'iter')
def message(self, level, content):
self.message_logger.__getattribute__(level)(content)
def images(self, prefix, image_dict, step):
for name, image in image_dict.items():
self.add_image(prefix + '/' + name, image, step, dataformats='HWC')
def merge_save_images(self, name, images):
for i, image in enumerate(images):
if i == 0:
result = image
else:
result = np.concatenate([result, image], 0)
cv2.imwrite(os.path.join(self.vis_dir(), name+'.jpg'), result)
def vis_dir(self):
vis_dir = os.path.join(self.log_dir, self.VISUALIZE_NAME)
if not os.path.exists(vis_dir):
os.mkdir(vis_dir)
return vis_dir
def save_image_dict(self, images, max_size=1024):
for file_name, image in images.items():
height, width = image.shape[:2]
if height > width:
actual_height = min(height, max_size)
actual_width = int(round(actual_height * width / height))
else:
actual_width = min(width, max_size)
actual_height = int(round(actual_width * height / width))
image = cv2.resize(image, (actual_width, actual_height))
cv2.imwrite(os.path.join(self.vis_dir(), file_name+'.jpg'), image)
def __getattr__(self, name):
message_levels = set(['debug', 'info', 'warning', 'error', 'critical'])
if name == '__setstate__':
raise AttributeError('haha')
if name in message_levels:
return functools.partial(self.message, name)
elif hasattr(self.__dict__.get('tf_board_logger'), name):
return self.tf_board_logger.__getattribute__(name)
else:
super()
|