本文整理了Java中water.Job.start_time()
方法的一些代码示例,展示了Job.start_time()
的具体用法。这些代码示例主要来源于Github
/Stackoverflow
/Maven
等平台,是从一些精选项目中提取出来的代码,具有较强的参考意义,能在一定程度帮忙到你。Job.start_time()
方法的具体详情如下:
包路径:water.Job
类名称:Job
方法名:start_time
暂无
代码示例来源:origin: h2oai/h2o-3
private void updateTiming(Key<Job> job_key) {
final long now = System.currentTimeMillis();
long start_time_current_model = job_key.get().start_time();
total_training_time_ms = total_checkpointed_run_time_ms + (now - start_time_current_model);
checkTimingConsistency();
}
代码示例来源:origin: h2oai/h2o-3
void updateTiming(Key<Job> job_key) {
final long now = System.currentTimeMillis();
long start_time_current_model = job_key.get().start_time();
total_training_time_ms = total_checkpointed_run_time_ms + (now - start_time_current_model);
checkTimingConsistency();
}
代码示例来源:origin: h2oai/h2o-3
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(output._training_time_ms.get(row)));
table.set(row, col++, PrettyPrint.msecs(output._training_time_ms.get(row) - _job.start_time(),
true));
table.set(row, col++, row);
代码示例来源:origin: h2oai/h2o-3
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(_model._output._training_time_ms[i]));
table.set(row, col++, PrettyPrint.msecs(_model._output._training_time_ms[i] - _job.start_time(), true));
table.set(row, col++, i);
ScoreKeeper st = sks[i];
代码示例来源:origin: h2oai/h2o-3
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(output._training_time_ms[i]));
table.set(row, col++, PrettyPrint.msecs(output._training_time_ms[i]-_job.start_time(), true));
table.set(row, col++, i);
if (_parms._estimate_k)
代码示例来源:origin: h2oai/h2o-3
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(_training_time_ms[i]));
table.set(row, col++, PrettyPrint.msecs(_training_time_ms[i] - job.start_time(), true));
table.set(row, col++, i);
ScoreKeeper st = _scored_train[i];
代码示例来源:origin: h2oai/h2o-3
scoreTable.put("Principal Component #", model._output._history_eigenVectorIndex);
model._output._scoring_history = createScoringHistoryTableDR(scoreTable,
"Scoring History from Power SVD", _job.start_time());
} else if(_parms._svd_method == SVDParameters.Method.Randomized) {
qfrm = randSubIter(dinfo, model);
scoreTable.put("average SEE", model._output._history_average_SEE);
model._output._scoring_history = createScoringHistoryTableDR(scoreTable,
"Scoring History from Randomized SVD", _job.start_time());
} else
error("_svd_method", "Unrecognized SVD method " + _parms._svd_method);
代码示例来源:origin: h2oai/h2o-3
scoreTable.put("Timestamp", model._output._training_time_ms);
model._output._scoring_history = createScoringHistoryTableDR(scoreTable, "Scoring History for GramSVD",
_job.start_time());
代码示例来源:origin: h2oai/h2o-3
model.total_setup_time_ms += now - _job.start_time();
Log.info("Total setup time: " + PrettyPrint.msecs(model.total_setup_time_ms, true));
Log.info("Starting to train the Deep Learning model.");
代码示例来源:origin: h2oai/h2o-3
model.total_setup_time_ms += now - _job.start_time();
Log.info("Total setup time: " + PrettyPrint.msecs(model.total_setup_time_ms, true));
Log.info("Starting to train the Deep Learning model.");
代码示例来源:origin: ai.h2o/h2o-algos
void updateTiming(Key<Job> job_key) {
final long now = System.currentTimeMillis();
long start_time_current_model = job_key.get().start_time();
total_training_time_ms = total_checkpointed_run_time_ms + (now - start_time_current_model);
checkTimingConsistency();
}
代码示例来源:origin: ai.h2o/h2o-algos
private void updateTiming(Key<Job> job_key) {
final long now = System.currentTimeMillis();
long start_time_current_model = job_key.get().start_time();
total_training_time_ms = total_checkpointed_run_time_ms + (now - start_time_current_model);
checkTimingConsistency();
}
代码示例来源:origin: ai.h2o/h2o-algos
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(_model._output._training_time_ms[i]));
table.set(row, col++, PrettyPrint.msecs(_model._output._training_time_ms[i] - _job.start_time(), true));
table.set(row, col++, i);
ScoreKeeper st = sks[i];
代码示例来源:origin: ai.h2o/h2o-algos
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(output._training_time_ms.get(row)));
table.set(row, col++, PrettyPrint.msecs(output._training_time_ms.get(row) - _job.start_time(),
true));
table.set(row, col++, row);
代码示例来源:origin: ai.h2o/h2o-algos
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(output._training_time_ms[i]));
table.set(row, col++, PrettyPrint.msecs(output._training_time_ms[i]-_job.start_time(), true));
table.set(row, col++, i);
if (_parms._estimate_k)
代码示例来源:origin: ai.h2o/h2o-algos
DateTimeFormatter fmt = DateTimeFormat.forPattern("yyyy-MM-dd HH:mm:ss");
table.set(row, col++, fmt.print(_training_time_ms[i]));
table.set(row, col++, PrettyPrint.msecs(_training_time_ms[i] - job.start_time(), true));
table.set(row, col++, i);
ScoreKeeper st = _scored_train[i];
代码示例来源:origin: ai.h2o/h2o-algos
scoreTable.put("Principal Component #", model._output._history_eigenVectorIndex);
model._output._scoring_history = createScoringHistoryTableDR(scoreTable,
"Scoring History from Power SVD", _job.start_time());
} else if(_parms._svd_method == SVDParameters.Method.Randomized) {
qfrm = randSubIter(dinfo, model);
scoreTable.put("average SEE", model._output._history_average_SEE);
model._output._scoring_history = createScoringHistoryTableDR(scoreTable,
"Scoring History from Randomized SVD", _job.start_time());
} else
error("_svd_method", "Unrecognized SVD method " + _parms._svd_method);
代码示例来源:origin: ai.h2o/h2o-algos
scoreTable.put("Timestamp", model._output._training_time_ms);
model._output._scoring_history = createScoringHistoryTableDR(scoreTable, "Scoring History for GramSVD",
_job.start_time());
代码示例来源:origin: ai.h2o/h2o-algos
model.total_setup_time_ms += now - _job.start_time();
Log.info("Total setup time: " + PrettyPrint.msecs(model.total_setup_time_ms, true));
Log.info("Starting to train the Deep Learning model.");
代码示例来源:origin: ai.h2o/h2o-algos
model.total_setup_time_ms += now - _job.start_time();
Log.info("Total setup time: " + PrettyPrint.msecs(model.total_setup_time_ms, true));
Log.info("Starting to train the Deep Learning model.");
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