525 lines
14 KiB
Python
525 lines
14 KiB
Python
import os
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import sys
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import shutil
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import os.path as osp
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import json
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import time
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import datetime
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import tempfile
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from collections import defaultdict
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DEBUG = 10
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INFO = 20
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WARN = 30
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ERROR = 40
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DISABLED = 50
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class KVWriter(object):
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def writekvs(self, kvs):
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raise NotImplementedError
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class SeqWriter(object):
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def writeseq(self, seq):
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raise NotImplementedError
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class HumanOutputFormat(KVWriter, SeqWriter):
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def __init__(self, filename_or_file):
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if isinstance(filename_or_file, str):
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self.file = open(filename_or_file, 'wt')
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self.own_file = True
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else:
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assert hasattr(filename_or_file, 'read'), 'expected file or str, got %s' % filename_or_file
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self.file = filename_or_file
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self.own_file = False
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def writekvs(self, kvs):
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# Create strings for printing
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key2str = {}
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for (key, val) in sorted(kvs.items()):
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if isinstance(val, float):
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valstr = '%-8.3g' % (val,)
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else:
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valstr = str(val)
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key2str[self._truncate(key)] = self._truncate(valstr)
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# Find max widths
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if len(key2str) == 0:
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print('WARNING: tried to write empty key-value dict')
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return
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else:
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keywidth = max(map(len, key2str.keys()))
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valwidth = max(map(len, key2str.values()))
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# Write out the data
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dashes = '-' * (keywidth + valwidth + 7)
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lines = [dashes]
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for (key, val) in sorted(key2str.items()):
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lines.append('| %s%s | %s%s |' % (
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key,
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' ' * (keywidth - len(key)),
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val,
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' ' * (valwidth - len(val)),
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))
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lines.append(dashes)
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self.file.write('\n'.join(lines) + '\n')
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# Flush the output to the file
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self.file.flush()
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def _truncate(self, s):
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return s[:20] + '...' if len(s) > 23 else s
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def writeseq(self, seq):
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seq = list(seq)
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for (i, elem) in enumerate(seq):
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self.file.write(elem)
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if i < len(seq) - 1: # add space unless this is the last one
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self.file.write(' ')
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self.file.write('\n')
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self.file.flush()
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def close(self):
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if self.own_file:
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self.file.close()
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class JSONOutputFormat(KVWriter):
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def __init__(self, filename):
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self.file = open(filename, 'wt')
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def writekvs(self, kvs):
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for k, v in sorted(kvs.items()):
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if hasattr(v, 'dtype'):
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v = v.tolist()
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kvs[k] = float(v)
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self.file.write(json.dumps(kvs) + '\n')
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self.file.flush()
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def close(self):
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self.file.close()
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class CSVOutputFormat(KVWriter):
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def __init__(self, filename):
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self.file = open(filename, 'w+t')
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self.keys = []
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self.sep = ','
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def writekvs(self, kvs):
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# Add our current row to the history
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extra_keys = kvs.keys() - self.keys
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if extra_keys:
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self.keys.extend(extra_keys)
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self.file.seek(0)
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lines = self.file.readlines()
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self.file.seek(0)
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for (i, k) in enumerate(self.keys):
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if i > 0:
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self.file.write(',')
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self.file.write(k)
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self.file.write('\n')
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for line in lines[1:]:
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self.file.write(line[:-1])
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self.file.write(self.sep * len(extra_keys))
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self.file.write('\n')
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for (i, k) in enumerate(self.keys):
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if i > 0:
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self.file.write(',')
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v = kvs.get(k)
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if v is not None:
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self.file.write(str(v))
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self.file.write('\n')
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self.file.flush()
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def close(self):
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self.file.close()
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class TensorBoardOutputFormat(KVWriter):
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"""
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Dumps key/value pairs into TensorBoard's numeric format.
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"""
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def __init__(self, dir):
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os.makedirs(dir, exist_ok=True)
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self.dir = dir
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self.step = 1
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prefix = 'events'
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path = osp.join(osp.abspath(dir), prefix)
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import tensorflow as tf
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from tensorflow.python import pywrap_tensorflow
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from tensorflow.core.util import event_pb2
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from tensorflow.python.util import compat
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self.tf = tf
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self.event_pb2 = event_pb2
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self.pywrap_tensorflow = pywrap_tensorflow
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self.writer = pywrap_tensorflow.EventsWriter(compat.as_bytes(path))
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def writekvs(self, kvs):
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def summary_val(k, v):
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kwargs = {'tag': k, 'simple_value': float(v)}
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return self.tf.Summary.Value(**kwargs)
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summary = self.tf.Summary(value=[summary_val(k, v) for k, v in kvs.items()])
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event = self.event_pb2.Event(wall_time=time.time(), summary=summary)
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event.step = self.step # is there any reason why you'd want to specify the step?
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self.writer.WriteEvent(event)
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self.writer.Flush()
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self.step += 1
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def close(self):
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if self.writer:
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self.writer.Close()
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self.writer = None
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def make_output_format(format, ev_dir, log_suffix=''):
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os.makedirs(ev_dir, exist_ok=True)
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if format == 'stdout':
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return HumanOutputFormat(sys.stdout)
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elif format == 'log':
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return HumanOutputFormat(osp.join(ev_dir, 'log%s.txt' % log_suffix))
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elif format == 'json':
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return JSONOutputFormat(osp.join(ev_dir, 'progress%s.json' % log_suffix))
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elif format == 'csv':
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return CSVOutputFormat(osp.join(ev_dir, 'progress%s.csv' % log_suffix))
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elif format == 'tensorboard':
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return TensorBoardOutputFormat(osp.join(ev_dir, 'tb%s' % log_suffix))
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else:
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raise ValueError('Unknown format specified: %s' % (format,))
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# ================================================================
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# API
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# ================================================================
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def logkv(key, val):
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"""
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Log a value of some diagnostic
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Call this once for each diagnostic quantity, each iteration
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If called many times, last value will be used.
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"""
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Logger.CURRENT.logkv(key, val)
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def logkv_mean(key, val):
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"""
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The same as logkv(), but if called many times, values averaged.
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"""
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Logger.CURRENT.logkv_mean(key, val)
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def logkvs(d):
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"""
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Log a dictionary of key-value pairs
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"""
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for (k, v) in d.items():
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logkv(k, v)
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def dumpkvs():
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"""
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Write all of the diagnostics from the current iteration
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level: int. (see logger.py docs) If the global logger level is higher than
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the level argument here, don't print to stdout.
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"""
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Logger.CURRENT.dumpkvs()
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def getkvs():
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return Logger.CURRENT.name2val
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def log(*args, level=INFO):
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"""
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Write the sequence of args, with no separators, to the console and output files (if you've configured an output file).
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"""
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Logger.CURRENT.log(*args, level=level)
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def debug(*args):
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log(*args, level=DEBUG)
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def info(*args):
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log(*args, level=INFO)
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def warn(*args):
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log(*args, level=WARN)
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def error(*args):
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log(*args, level=ERROR)
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def set_level(level):
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"""
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Set logging threshold on current logger.
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"""
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Logger.CURRENT.set_level(level)
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def get_dir():
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"""
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Get directory that log files are being written to.
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will be None if there is no output directory (i.e., if you didn't call start)
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"""
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return Logger.CURRENT.get_dir()
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record_tabular = logkv
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dump_tabular = dumpkvs
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class ProfileKV:
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"""
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Usage:
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with logger.ProfileKV("interesting_scope"):
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code
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"""
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def __init__(self, n):
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self.n = "wait_" + n
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def __enter__(self):
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self.t1 = time.time()
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def __exit__(self, type, value, traceback):
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Logger.CURRENT.name2val[self.n] += time.time() - self.t1
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def profile(n):
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"""
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Usage:
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@profile("my_func")
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def my_func(): code
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"""
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def decorator_with_name(func):
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def func_wrapper(*args, **kwargs):
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with ProfileKV(n):
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return func(*args, **kwargs)
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return func_wrapper
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return decorator_with_name
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# ================================================================
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# Backend
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# ================================================================
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class Logger(object):
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DEFAULT = None # A logger with no output files. (See right below class definition)
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# So that you can still log to the terminal without setting up any output files
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CURRENT = None # Current logger being used by the free functions above
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def __init__(self, dir, output_formats):
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self.name2val = defaultdict(float) # values this iteration
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self.name2cnt = defaultdict(int)
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self.level = INFO
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self.dir = dir
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self.output_formats = output_formats
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# Logging API, forwarded
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# ----------------------------------------
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def logkv(self, key, val):
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self.name2val[key] = val
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def logkv_mean(self, key, val):
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if val is None:
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self.name2val[key] = None
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return
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oldval, cnt = self.name2val[key], self.name2cnt[key]
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self.name2val[key] = oldval * cnt / (cnt + 1) + val / (cnt + 1)
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self.name2cnt[key] = cnt + 1
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def dumpkvs(self):
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if self.level == DISABLED: return
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for fmt in self.output_formats:
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if isinstance(fmt, KVWriter):
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fmt.writekvs(self.name2val)
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self.name2val.clear()
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self.name2cnt.clear()
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def log(self, *args, level=INFO):
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if self.level <= level:
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self._do_log(args)
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# Configuration
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# ----------------------------------------
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def set_level(self, level):
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self.level = level
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def get_dir(self):
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return self.dir
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def close(self):
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for fmt in self.output_formats:
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fmt.close()
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# Misc
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# ----------------------------------------
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def _do_log(self, args):
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for fmt in self.output_formats:
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if isinstance(fmt, SeqWriter):
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fmt.writeseq(map(str, args))
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Logger.DEFAULT = Logger.CURRENT = Logger(dir=None, output_formats=[HumanOutputFormat(sys.stdout)])
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def configure(dir=None, format_strs=None):
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if dir is None:
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dir = os.getenv('OPENAI_LOGDIR')
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if dir is None:
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dir = osp.join(tempfile.gettempdir(),
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datetime.datetime.now().strftime("openai-%Y-%m-%d-%H-%M-%S-%f"))
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# dir = osp.join('../../logfile/Swimmer', "parabola_0.005")
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assert isinstance(dir, str)
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# if os.path.exists(dir):
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# # if exits dir then create a new dir dir_times_{n}
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# *folder, subfoldername = dir.split('/')
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# folder = '/'.join(folder)
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# subfolders = os.listdir(folder)
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# subfoldername += '_times_1'
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# while subfoldername in subfolders:
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# subfoldername = subfoldername[:-1] + str(int(subfoldername[-1]) + 1)
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# dir = osp.join(folder,subfoldername)
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os.makedirs(dir, exist_ok=True)
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log_suffix = ''
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from mpi4py import MPI
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rank = MPI.COMM_WORLD.Get_rank()
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if rank > 0:
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log_suffix = "-rank%03i" % rank
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if format_strs is None:
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if rank == 0:
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format_strs = os.getenv('OPENAI_LOG_FORMAT', 'stdout,log,csv').split(',')
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else:
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format_strs = os.getenv('OPENAI_LOG_FORMAT_MPI', 'log').split(',')
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format_strs = filter(None, format_strs)
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output_formats = [make_output_format(f, dir, log_suffix) for f in format_strs]
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Logger.CURRENT = Logger(dir=dir, output_formats=output_formats)
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log('Logging to \n%s' % dir)
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def reset():
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if Logger.CURRENT is not Logger.DEFAULT:
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Logger.CURRENT.close()
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Logger.CURRENT = Logger.DEFAULT
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log('Reset logger')
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class scoped_configure(object):
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def __init__(self, dir=None, format_strs=None):
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self.dir = dir
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self.format_strs = format_strs
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self.prevlogger = None
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def __enter__(self):
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self.prevlogger = Logger.CURRENT
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configure(dir=self.dir, format_strs=self.format_strs)
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def __exit__(self, *args):
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Logger.CURRENT.close()
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Logger.CURRENT = self.prevlogger
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# ================================================================
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def _demo():
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info("hi")
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debug("shouldn't appear")
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set_level(DEBUG)
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debug("should appear")
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dir = "/tmp/testlogging"
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if os.path.exists(dir):
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shutil.rmtree(dir)
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configure(dir=dir)
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logkv("a", 3)
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logkv("b", 2.5)
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dumpkvs()
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logkv("b", -2.5)
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logkv("a", 5.5)
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dumpkvs()
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info("^^^ should see a = 5.5")
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logkv_mean("b", -22.5)
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logkv_mean("b", -44.4)
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logkv("a", 5.5)
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dumpkvs()
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info("^^^ should see b = 33.3")
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logkv("b", -2.5)
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dumpkvs()
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logkv("a", "longasslongasslongasslongasslongasslongassvalue")
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dumpkvs()
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# ================================================================
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# Readers
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# ================================================================
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def read_json(fname):
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import pandas
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ds = []
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with open(fname, 'rt') as fh:
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for line in fh:
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ds.append(json.loads(line))
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return pandas.DataFrame(ds)
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def read_csv(fname):
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import pandas
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return pandas.read_csv(fname, index_col=None, comment='#')
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def read_tb(path):
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"""
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path : a tensorboard file OR a directory, where we will find all TB files
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of the form events.*
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"""
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import pandas
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import numpy as np
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from glob import glob
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from collections import defaultdict
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import tensorflow as tf
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if osp.isdir(path):
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fnames = glob(osp.join(path, "events.*"))
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elif osp.basename(path).startswith("events."):
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fnames = [path]
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else:
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raise NotImplementedError("Expected tensorboard file or directory containing them. Got %s" % path)
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tag2pairs = defaultdict(list)
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maxstep = 0
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for fname in fnames:
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for summary in tf.train.summary_iterator(fname):
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if summary.step > 0:
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for v in summary.summary.value:
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pair = (summary.step, v.simple_value)
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tag2pairs[v.tag].append(pair)
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maxstep = max(summary.step, maxstep)
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data = np.empty((maxstep, len(tag2pairs)))
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data[:] = np.nan
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tags = sorted(tag2pairs.keys())
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for (colidx, tag) in enumerate(tags):
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pairs = tag2pairs[tag]
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for (step, value) in pairs:
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data[step - 1, colidx] = value
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return pandas.DataFrame(data, columns=tags)
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if __name__ == "__main__":
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_demo()
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