mirror of
https://github.com/zebrajr/pytorch.git
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53 lines
1.6 KiB
Python
53 lines
1.6 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import datetime
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import time
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from collections import OrderedDict
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'''
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Utilities for logging experiment run stats, such as accuracy
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and loss over time for different runs. Runtime arguments are stored
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in the log.
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'''
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class ModelTrainerLog():
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def __init__(self, expname, runtime_args):
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now = datetime.datetime.fromtimestamp(time.time())
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self.experiment_id = now.strftime('%Y%m%d_%H%M%S')
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self.filename = "%s_%s.log" % (expname, self.experiment_id)
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self.logstr("# %s" % str(runtime_args))
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self.headers = None
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self.start_time = time.time()
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def logstr(self, str):
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with open(self.filename, "a") as f:
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f.write(str + "\n")
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f.close()
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print(str)
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def log(self, input_count, batch_count, additional_values):
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logdict = OrderedDict()
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logdict['time'] = time.time() - self.start_time
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logdict['input_counter'] = input_count
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logdict['batch_count'] = batch_count
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if logdict['time'] > 0:
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logdict['inputs_per_sec'] = input_count / logdict['time']
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else:
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logdict['inputs_per_sec'] = 0.0
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for k in sorted(additional_values.keys()):
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logdict[k] = additional_values[k]
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# Write the headers if they are not written yet
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if self.headers is None:
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self.headers = logdict.keys()[:]
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self.logstr(",".join(self.headers))
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self.logstr(",".join([str(v) for v in logdict.values()]))
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