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ffm-baseline
Commit a88f26d4 authored by Your Name's avatar Your Name
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predict add sample id

parent 48ec96ab
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Showing with 2 additions and 2 deletions
eda/esmm/Model_pipline/train.py
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...@@ -359,10 +359,10 @@ def main(_): ...@@ -359,10 +359,10 @@ def main(_):
for key,value in sorted(result.items()): for key,value in sorted(result.items()):
print('%s: %s' % (key,value)) print('%s: %s' % (key,value))
elif FLAGS.task_type == 'infer': elif FLAGS.task_type == 'infer':
preds = Estimator.predict(input_fn=lambda: input_fn(te_files, num_epochs=1, batch_size=FLAGS.batch_size), predict_keys=["pctcvr","pctr","pcvr"]) preds = Estimator.predict(input_fn=lambda: input_fn(te_files, num_epochs=1, batch_size=FLAGS.batch_size), predict_keys=["pctcvr","pctr","pcvr","sample_id"])
with open(FLAGS.local_dir + "/pred.txt", "w") as fo: with open(FLAGS.local_dir + "/pred.txt", "w") as fo:
for prob in preds: for prob in preds:
fo.write("%f\t%f\t%f\n" % (prob['pctr'], prob['pcvr'], prob['pctcvr'])) fo.write("%f\t%f\t%f\t%d\n" % (prob['pctr'], prob['pcvr'], prob['pctcvr'], prob["sample_id"]))
elif FLAGS.task_type == 'export': elif FLAGS.task_type == 'export':
print("Not Implemented, Do It Yourself!") print("Not Implemented, Do It Yourself!")
......
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