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prediction dict type

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Jason
2022-04-03 11:54:57 -07:00
parent da1667e241
commit 1aee72ace2
1 changed files with 7 additions and 2 deletions
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load_estimation_model.py
+7 -2
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@@ -53,11 +53,16 @@ def load_estimation_model(inputfilename, outputfilename, begin, end, csv_export=
model.load_state_dict(torch.load("em.pth")) model.load_state_dict(torch.load("em.pth"))
my_prediction = model.forward(data) my_prediction = model.forward(data)
my_prediction[0][0] = 1000 * float(my_prediction[0][0])
my_prediction[0][1] = 1000 * float(my_prediction[0][1])
my_prediction[0][2] = 1000 * float(my_prediction[0][2])
my_prediction[0][3] = 1000 * float(my_prediction[0][3])
if csv_export: if csv_export:
with open(outputfilename, "w") as wf: with open(outputfilename, "w") as wf:
wf.write("NAME,begin,end,F1,F2,F3,F4\n") wf.write("NAME,begin,end,F1,F2,F3,F4\n")
wf.write(name + "," + str(begin) + "," + str(end) + "," + \ wf.write(name + "," + str(begin) + "," + str(end) + "," + \
str(1000 * float(my_prediction[0][0])) + "," + str(1000 * float(my_prediction[0][1])) + "," + \ str(my_prediction[0][0]) + "," + str(my_prediction[0][1]) + "," + \
str(1000 * float(my_prediction[0][2])) + "," + str(1000 * float(my_prediction[0][3])) + "\n") str(my_prediction[0][2]) + "," + str(my_prediction[0][3]) + "\n")
return my_prediction return my_prediction