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ffm-baseline
Commit 48ec96ab authored by Your Name's avatar Your Name
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test features

parent 9b649d66
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eda/esmm/Model_pipline/train.py
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...@@ -132,7 +132,7 @@ def model_fn(features, labels, mode, params): ...@@ -132,7 +132,7 @@ def model_fn(features, labels, mode, params):
tag5_list = features['tag5_list'] tag5_list = features['tag5_list']
tag6_list = features['tag6_list'] tag6_list = features['tag6_list']
tag7_list = features['tag7_list'] tag7_list = features['tag7_list']
sample_id = features['number'] number = features['number']
if FLAGS.task_type != "infer": if FLAGS.task_type != "infer":
y = labels['y'] y = labels['y']
...@@ -156,6 +156,8 @@ def model_fn(features, labels, mode, params): ...@@ -156,6 +156,8 @@ def model_fn(features, labels, mode, params):
x_concat = tf.concat([tf.reshape(embedding_id, shape=[-1, common_dims]), app_id, level2, level3, tag1, x_concat = tf.concat([tf.reshape(embedding_id, shape=[-1, common_dims]), app_id, level2, level3, tag1,
tag2, tag3, tag4, tag5, tag6, tag7], axis=1) tag2, tag3, tag4, tag5, tag6, tag7], axis=1)
sample_id = tf.sparse.to_dense(number)
with tf.name_scope("CVR_Task"): with tf.name_scope("CVR_Task"):
if mode == tf.estimator.ModeKeys.TRAIN: if mode == tf.estimator.ModeKeys.TRAIN:
train_phase = True train_phase = True
......
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