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# Copyright 2017 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
from datetime import datetime
import json
import logging
import os
import tensorflow as tf
import tensorflow.contrib.slim as slim
def prepare_dirs_and_logger(config):
formatter = logging.Formatter('%(asctime)s:%(levelname)s::%(message)s')
logger = logging.getLogger('tensorflow')
for hdlr in logger.handlers:
logger.removeHandler(hdlr)
handler = logging.StreamHandler()
handler.setFormatter(formatter)
logger.addHandler(handler)
logger.setLevel(tf.logging.INFO)
config.log_dir = os.path.join(config.exp_dir, config.log_dir,
config.train_tag)
config.model_dir = os.path.join(config.exp_dir, config.model_dir,
config.train_tag)
config.output_dir = os.path.join(config.exp_dir, config.output_dir,
config.train_tag)
for path in [
config.log_dir, config.model_dir, config.output_dir
]:
if not os.path.exists(path):
os.makedirs(path)
config.data_files = {
'train': os.path.join(config.data_dir, config.train_data_file),
'dev': os.path.join(config.data_dir, config.dev_data_file),
'test': os.path.join(config.data_dir, config.test_data_file)
}
return config
def get_time():
return datetime.now().strftime('%Y-%m-%d_%H-%M-%S')
def show_all_variables():
model_vars = tf.trainable_variables()
slim.model_analyzer.analyze_vars(model_vars, print_info=True)
def save_config(config):
param_path = os.path.join(config.model_dir, 'params.json')
tf.logging.info('log dir: %s' % config.log_dir)
tf.logging.info('model dir: %s' % config.model_dir)
tf.logging.info('param path: %s' % param_path)
tf.logging.info('output dir: %s' % config.output_dir)
with open(param_path, 'w') as f:
f.write(json.dumps(config.__dict__, indent=4, sort_keys=True))
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