本文整理汇总了Python中object_detection.model_lib.populate_experiment方法的典型用法代码示例。如果您正苦于以下问题：Python model_lib.populate_experiment方法的具体用法？Python model_lib.populate_experiment怎么用？Python model_lib.populate_experiment使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类object_detection.model_lib的用法示例。
在下文中一共展示了model_lib.populate_experiment方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_experiment
# 需要导入模块: from object_detection import model_lib [as 别名]
# 或者: from object_detection.model_lib import populate_experiment [as 别名]
def test_experiment(self):
"""Tests that the `Experiment` object is constructed correctly."""
run_config = tf.estimator.RunConfig()
hparams = model_hparams.create_hparams(
hparams_overrides='load_pretrained=false')
pipeline_config_path = get_pipeline_config_path(MODEL_NAME_FOR_TEST)
experiment = model_lib.populate_experiment(
run_config,
hparams,
pipeline_config_path,
train_steps=10,
eval_steps=20)
self.assertEqual(10, experiment.train_steps)
self.assertEqual(None, experiment.eval_steps) 示例2: test_experiment
# 需要导入模块: from object_detection import model_lib [as 别名]
# 或者: from object_detection.model_lib import populate_experiment [as 别名]
def test_experiment(self):
"""Tests that the `Experiment` object is constructed correctly."""
run_config = tf.estimator.RunConfig()
hparams = model_hparams.create_hparams(
hparams_overrides='load_pretrained=false')
pipeline_config_path = get_pipeline_config_path(MODEL_NAME_FOR_TEST)
experiment = model_lib.populate_experiment(
run_config,
hparams,
pipeline_config_path,
train_steps=10,
eval_steps=20)
self.assertEqual(10, experiment.train_steps)
self.assertEqual(20, experiment.eval_steps)