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ffm-baseline
Commit cef1c8a8 authored by Your Name's avatar Your Name
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test dist predict

parent f55f775b
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Showing with 16 additions and 16 deletions
eda/esmm/Model_pipline/dist_predict.py
View file @ cef1c8a8
......@@ -203,22 +203,22 @@ if __name__ == "__main__":
df = spark.read.format("tfrecords").load(path+"test_native/part-r-00000")
df.show()
te_files = []
for i in range(0,10):
te_files.append([path + "test_native/part-r-0000" + str(i)])
for i in range(10,100):
te_files.append([path + "test_native/part-r-000" + str(i)])
rdd_te_files = spark.sparkContext.parallelize(te_files)
print("-"*100)
print(rdd_te_files.collect())
print("-" * 100)
indices = rdd_te_files.repartition(100).map(lambda x: main(x))
print(indices.take(1))
te_result_dataframe = spark.createDataFrame(indices.flatMap(lambda x: x.split(";")).map(lambda l: Row(sample_id=l.split(":")[0],ctcvr=l.split(":")[1])))
te_result_dataframe.show()
te_result_dataframe.toPandas().to_csv("/home/gmuser/esmm/native/pred.txt", header=True)
# te_files = []
# for i in range(0,10):
# te_files.append([path + "test_native/part-r-0000" + str(i)])
# for i in range(10,100):
# te_files.append([path + "test_native/part-r-000" + str(i)])
#
# rdd_te_files = spark.sparkContext.parallelize(te_files)
# print("-"*100)
# print(rdd_te_files.collect())
# print("-" * 100)
# indices = rdd_te_files.repartition(100).map(lambda x: main(x))
# print(indices.take(1))
#
# te_result_dataframe = spark.createDataFrame(indices.flatMap(lambda x: x.split(";")).map(lambda l: Row(sample_id=l.split(":")[0],ctcvr=l.split(":")[1])))
# te_result_dataframe.show()
# te_result_dataframe.toPandas().to_csv("/home/gmuser/esmm/native/pred.txt", header=True)
......
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