text: #!/usr/bin/env python
  
  # Licensed to the Apache Software Foundation (ASF) under one
  # or more contributor license agreements.  See the NOTICE file
  # distributed with this work for additional information
  # regarding copyright ownership.  The ASF licenses this file
  # to you 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.
  
  """
  parse mxnet output log into a markdown table
  """
  import argparse
  import sys
  import re
  
  parser = argparse.ArgumentParser(description='Parse mxnet output log')
  parser.add_argument('logfile', nargs=1, type=str,
                      help = 'the log file for parsing')
  parser.add_argument('--format', type=str, default='markdown',
                      choices = ['markdown', 'none'],
                      help = 'the format of the parsed outout')
  parser.add_argument('--metric-names', type=str, nargs="+", default = ['accuracy'],
                      help='names of metrics in log which should be parsed')
  args = parser.parse_args()
  
  with open(args.logfile[0]) as f:
      lines = f.readlines()
  
  res = [re.compile('.*Epoch\[(\d+)\] Train-'+s+'.*=([.\d]+)') for s in args.metric_names]\
       + [re.compile('.*Epoch\[(\d+)\] Validation-'+s+'.*=([.\d]+)') for s in args.metric_names]\
       + [re.compile('.*Epoch\[(\d+)\] Time.*=([.\d]+)')]
  
  data = {}
  for l in lines:
      i = 0
      for r in res:
          m = r.match(l)
          if m is not None:
              break
          i += 1
      if m is None:
          continue
  
      assert len(m.groups()) == 2
      epoch = int(m.groups()[0])
      val = float(m.groups()[1])
  
      if epoch not in data:
          data[epoch] = [0] * len(res) * 2
  
      data[epoch][i*2] += val
      data[epoch][i*2+1] += 1
  
  if args.format == 'markdown':
      print("| epoch | " + " | ".join(['train-'+s for s in args.metric_names]) + " | " + " | ".join(['val-'+s for s in args.metric_names]) + " | time |")
      print("| --- "*(len(res)+1) + "|")
      for k, v in data.items():
          print("| %2d | " % (k+1)\
                + " | ".join(["%f" % (v[2*j]/v[2*j+1]) for j in range(2*len(args.metric_names))])\
                + " | %.1f |" % (v[-2]/v[-1]))
  elif args.format == 'none':
      print("\t".join(['epoch'] + ['train-' + s for s in args.metric_names] + ['val-' + s for s in args.metric_names] + ['time']))
      for k, v in data.items():
          print("\t".join(["%2d" % (k+1)] + ["%f" % (v[2*j]/v[2*j+1]) for j in range(2*len(args.metric_names))] + ["%.1f" % (v[-2]/v[-1])]))
  