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dummy_example.py
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dummy_example.py
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# Copyright 2019 MLBenchmark Group. 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.
# ==============================================================================
import logging
import os
import sys
from mlperf_logging import mllog
def dummy_example():
"""Example usage of mllog"""
# Get the mllogger instance, this needs to be called in every module that
# needs logging
mllogger = mllog.get_mllogger()
# Customize mllogger configuration
# These configurations only need to be set Once in your entire program.
# Try tweaking the following configurations to see the difference.
# logger: Customize the underlying logger to change the logging behavior.
# filename: a log file to use. If set, a default file handler will be added
# to the logger so it can log to the specified file. For more advanced
# customizations, please set the 'logger' parameter instead.
# default_namespace: the default namespace to use if one isn't provided.
# default_stack_offset: the default depth to go into the stack to find
# the call site.
# default_clear_line: the default behavior of line clearing (i.e. print
# an extra new line to clear any pre-existing text in the log line).
# root_dir: directory prefix which will be trimmed when reporting calling
# file for logging.
# Customize the underlying logger to use a file in addition to stdout.
# 1. Simple way
# Provide a filename, this adds a log file with default behavior.
mllog.config(filename="example_simple.log")
# 2. Advanced way
# You may pass a logging.Logger instance to mllog.config().
# To use the advanced way, comment out the "Simple way" above and uncomment
# the followings:
#
# # Notice that proper log level needs to be set for both logger and handler.
# logger = logging.getLogger("custom_logger")
# logger.propagate = False
# logger.setLevel(logging.DEBUG)
# # add file handler for file logging
# _file_handler = logging.FileHandler("example_advanced.log")
# _file_handler.setLevel(logging.DEBUG)
# logger.addHandler(_file_handler)
# # add stream handler for stdout logging
# _stream_handler = logging.StreamHandler(stream=sys.stdout)
# _stream_handler.setLevel(logging.INFO)
# logger.addHandler(_stream_handler)
# mllog.config(logger=logger)
# Set other logger configurations
mllog.config(
default_namespace = "worker1",
default_stack_offset = 1,
default_clear_line = False,
root_dir = os.path.normpath(
os.path.join(os.path.dirname(os.path.realpath(__file__)), "..", "..")))
# Example log messages
# The methods to use are "start", "end", and "event".
# You may check out the detailed APIs in mllog.mllog.
# Try to use the keys from mllog.constants to avoid wrong keys.
mllogger.start(key=mllog.constants.RUN_START)
mllogger.event(key=mllog.constants.GLOBAL_BATCH_SIZE, value=1024)
mllogger.event(key=mllog.constants.EVAL_ACCURACY, value=0.99, clear_line=True)
mllogger.end(key=mllog.constants.RUN_STOP)
if __name__ == "__main__":
dummy_example()