本文整理匯總了Python中object_detection.model_lib.populate_experiment方法的典型用法代碼示例。如果您正苦於以下問題：Python model_lib.populate_experiment方法的具體用法？Python model_lib.populate_experiment怎麽用？Python model_lib.populate_experiment使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類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個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: test_experiment
# 需要導入模塊: from object_detection import model_lib [as 別名]
# 或者: from object_detection.model_lib import populate_experiment [as 別名]
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
# 需要導入模塊: from object_detection import model_lib [as 別名]
# 或者: from object_detection.model_lib import populate_experiment [as 別名]
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)