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ffm-baseline
Commit a84b77f8 authored by Your Name's avatar Your Name
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predict add sample id

parent 653e1f44
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Showing with 2 additions and 2 deletions
eda/esmm/Model_pipline/dist_predict.py
View file @ a84b77f8
...@@ -172,7 +172,7 @@ def main(te_file): ...@@ -172,7 +172,7 @@ def main(te_file):
ctcvr = [] ctcvr = []
for prob in preds: for prob in preds:
ctcvr.append(prob["sample_id"],prob['pctcvr']) ctcvr.append([prob["sample_id"],prob['pctcvr'][0]])
return ctcvr return ctcvr
# indices = [] # indices = []
......
eda/esmm/Model_pipline/train.py
View file @ a84b77f8
...@@ -363,7 +363,7 @@ def main(_): ...@@ -363,7 +363,7 @@ def main(_):
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"]) 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\t%s\n" % (prob['pctr'], prob['pcvr'], prob['pctcvr'], prob["sample_id"])) fo.write("%f\t%f\t%f\t%s\n" % (prob['pctr'], prob['pcvr'], prob['pctcvr'], prob["sample_id"][0]))
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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