645c7c386e62d2fb1d50f4621c1a52645a13869f,time_sequence_prediction/train.py,,,#,40

Before Change


        future = 1000
        pred = seq(test_input, future = future)
        loss = criterion(pred[:, :-future], test_target)
        print("test loss:", loss.data.numpy()[0])
        y = pred.data.numpy()
        // draw the result
        plt.figure(figsize=(30,10))
        plt.title("Predict future values for time sequences\n(Dashlines are predicted values)", fontsize=30)

After Change


            pred = seq(test_input, future=future)
            loss = criterion(pred[:, :-future], test_target)
            print("test loss:", loss.item())
            y = pred.detach().numpy()
        // draw the result
        plt.figure(figsize=(30,10))
        plt.title("Predict future values for time sequences\n(Dashlines are predicted values)", fontsize=30)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 2

Instances


Project Name: pytorch/examples
Commit Name: 645c7c386e62d2fb1d50f4621c1a52645a13869f
Time: 2018-04-24
Author: soumith@gmail.com
File Name: time_sequence_prediction/train.py
Class Name:
Method Name:


Project Name: dmlc/dgl
Commit Name: 7156c7163b046686064d7c9de445041870e672bc
Time: 2018-12-01
Author: minjie.wang@nyu.edu
File Name: tutorials/1_first.py
Class Name:
Method Name:


Project Name: Zhaoyi-Yan/Shift-Net_pytorch
Commit Name: 8f6a6f153781d0908fb0904349aae844494026ea
Time: 2018-12-03
Author: yanzhaoyi@outlook.com
File Name: models/shiftnet_model.py
Class Name: ShiftNetModel
Method Name: initialize