change test file

tensnsorflow/multi.py

@@ -66,9 +66,9 @@ def feature_engineer():
     # TODO 上线后把下面train fliter 删除，因为最近一天的数据也要作为训练集
 
     train = rdd.filter(lambda x: x[1]!= validate_date)\
-        .map(lambda x: (app_list_func(x[0], app_list_map),[value_map[x[2]],value_map[x[1]]], x[3],x[4]))
+        .map(lambda x: (app_list_func(x[0], app_list_map),[value_map[x[2]],value_map[x[1]]], float(x[3]),float(x[4])))
     test = rdd.filter(lambda x: x[1]== validate_date)\
-        .map(lambda x: (app_list_func(x[0], app_list_map),[value_map[x[2]],value_map[x[1]]], x[3],x[4]))
+        .map(lambda x: (app_list_func(x[0], app_list_map),[value_map[x[2]],value_map[x[1]]], float(x[3]),float(x[4])))
 
     spark.createDataFrame(test).toDF("level2_ids","ids","y","z")\
         .repartition(1).write.format("tfrecords").save(path=path+"va/", mode="overwrite")
@@ -91,7 +91,7 @@ def get_predict(date,value_map,app_list_map):
     df = spark.sql(sql)
     df = df.na.fill(dict(zip(features, features)))
     rdd = df.select("level2_ids","ucity_id","device_id","cid_id","label", "y", "z") \
-        .rdd.map(lambda x: (app_list_func(x[0], app_list_map),x[1],x[2],x[3],x[4],x[5],x[6],
+        .rdd.map(lambda x: (app_list_func(x[0], app_list_map),x[1],x[2],x[3],x[4],float(x[5]),float(x[6]),
                             [value_map.get(x[1], 300000),value_map.get(date, 299999)]))
 
     rdd.persist()
@@ -145,12 +145,12 @@ if __name__ == '__main__':
     validate_date, value_map, app_list_map = feature_engineer()
     get_predict(validate_date, value_map, app_list_map)
 
-    df = spark.read.format("tfrecords").option("recordType", "Example").load("/strategy/va.tfrecord")
-    df.show(1)
-    print("aa")
-    print("aa")
-    df = spark.read.format("tfrecords").load("/strategy/esmm/va/part-r-00000")
-    df.show(1)
+    # df = spark.read.format("tfrecords").option("recordType", "Example").load("/strategy/va.tfrecord")
+    # df.show(1)
+    # print("aa")
+    # print("aa")
+    # df = spark.read.format("tfrecords").load("/strategy/esmm/va/part-r-00000")
+    # df.show(1)
 
 
 

tensnsorflow/train_multi.py

@@ -47,8 +47,8 @@ def input_fn(filenames, batch_size=32, num_epochs=1, perform_shuffle=False):
     print('Parsing', filenames)
     def _parse_fn(record):
         features = {
-            "y": tf.FixedLenFeature([], tf.int64),
-            "z": tf.FixedLenFeature([], tf.int64),
+            "y": tf.FixedLenFeature([], tf.float32),
+            "z": tf.FixedLenFeature([], tf.float32),
             "ids": tf.FixedLenFeature([FLAGS.field_size], tf.int64),
             "level2_ids": tf.VarLenFeature(tf.int64)
         }