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Commit bebce09f authored by 宋柯's avatar 宋柯
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模型调试

parent 3be3af30
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train/train_service_sk_tf2_distibute.py
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...@@ -229,9 +229,9 @@ wideAndDeepModel = tf.estimator.DNNLinearCombinedClassifier(model_dir = MODEL_BA ...@@ -229,9 +229,9 @@ wideAndDeepModel = tf.estimator.DNNLinearCombinedClassifier(model_dir = MODEL_BA
# early_stopping = tf.contrib.estimator.stop_if_no_decrease_hook(wideAndDeepModel, eval_dir = wideAndDeepModel.eval_dir(), metric_name='auc', max_steps_without_decrease=1000, min_steps = 100) # early_stopping = tf.contrib.estimator.stop_if_no_decrease_hook(wideAndDeepModel, eval_dir = wideAndDeepModel.eval_dir(), metric_name='auc', max_steps_without_decrease=1000, min_steps = 100)
# early_stopping = tf.contrib.estimator.stop_if_no_increase_hook(wideAndDeepModel, metric_name = 'auc', max_steps_without_increase = 1000, min_steps = 1000) early_stopping = tf.contrib.estimator.stop_if_no_increase_hook(wideAndDeepModel, metric_name = 'auc', max_steps_without_increase = 1000, min_steps = 1000)
hooks = [] hooks = [early_stopping]
train_spec = tf.estimator.TrainSpec(input_fn = lambda: input_fn(BASE_DIR + 'train_samples.csv', 100, True, 2048), hooks = hooks) train_spec = tf.estimator.TrainSpec(input_fn = lambda: input_fn(BASE_DIR + 'train_samples.csv', 100, True, 2048), hooks = hooks)
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