test esmm predict

eda/esmm/Model_pipline/dist_predict.py

 from datetime import date, timedelta
 import tensorflow as tf
+import time
 
 
 def model_fn(features, labels, mode, params):
@@ -134,7 +135,7 @@ def input_fn(filenames, batch_size=32, num_epochs=1, perform_shuffle=False):
     #print(batch_features,batch_labels)
     return batch_features, batch_labels
 
-def esmm_predict():
+def main():
     dt_dir = (date.today() + timedelta(-1)).strftime('%Y%m%d')
     model_dir = "hdfs://172.16.32.4:8020/strategy/esmm/model_ckpt/DeepCvrMTL/" + dt_dir
     te_files = ["hdfs://172.16.32.4:8020/strategy/esmm/part-r-00000"]
@@ -156,3 +157,11 @@ def esmm_predict():
     with open("/home/gmuser/esmm/nearby" + "/pred.txt", "w") as fo:
         for prob in preds:
             fo.write("%f\t%f\t%f\n" % (prob['pctr'], prob['pcvr'], prob['pctcvr']))
+
+
+if __name__ == "__main__":
+    b = time.time()
+    tf.logging.set_verbosity(tf.logging.INFO)
+    tf.app.run()
+    print("耗时(分钟)：")
+    print((time.time()-b)/60)
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