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#!/usr/bin/env python |
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# -*- coding: utf-8 -*- |
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import os |
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import datetime |
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import logging as loggers |
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import deepy |
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logging = loggers.getLogger(__name__) |
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PROGRESS_LOG_PREFIX = "progress:" |
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EPOCH_LOG_PREFIX = "epoch:" |
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class TrainLogger(object): |
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def __init__(self): |
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self.log_pool = [] |
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self._progress = 0 |
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self._epoch = 0 |
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def load(self, model_path): |
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log_path = self._log_path(model_path) |
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if os.path.exists(log_path): |
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logging.info("Load training log from %s" % log_path) |
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for line in open(log_path).xreadlines(): |
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if line.startswith(EPOCH_LOG_PREFIX): |
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self._epoch = int(line.replace(EPOCH_LOG_PREFIX, "").strip()) |
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continue |
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if line.startswith(PROGRESS_LOG_PREFIX): |
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self._progress = int(line.replace(PROGRESS_LOG_PREFIX, "").strip()) |
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continue |
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self.log_pool.append(line.strip()) |
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def record(self, line): |
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time_mark = datetime.datetime.now().strftime("[%Y/%m/%d %H:%M:%S] ") |
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self.log_pool.append(time_mark + line) |
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def record_progress(self, progress): |
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""" |
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Record current progress in the training[1;3B]. |
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""" |
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self._progress = progress |
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def record_epoch(self, epoch): |
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self._epoch = epoch |
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def progress(self): |
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""" |
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Get loaded progress. |
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""" |
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return self._progress |
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def epoch(self): |
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return self._epoch |
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def save(self, model_path): |
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log_path = self._log_path(model_path) |
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# logging.info("Save training log to %s" % log_path) |
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with open(log_path, "w") as outf: |
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outf.write("# deepy version: %s\n" % deepy.__version__) |
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for line in self.log_pool: |
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outf.write(line + "\n") |
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if self._epoch > 0: |
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outf.write("%s %d\n" % (EPOCH_LOG_PREFIX, self._epoch)) |
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if self._progress > 0: |
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outf.write("%s %d\n" % (PROGRESS_LOG_PREFIX, self._progress)) |
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def _log_path(self, model_path): |
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log_path = model_path.rsplit(".", 1)[0] + ".log" |
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return log_path |
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