8f420a3b35944dcfa470dee958ef61dee221ce02,implementations/dualgan/datasets.py,MNISTM,__getitem__,#MNISTM#Any#,60

Before Change



        // doing this so that it is consistent with all other datasets
        // to return a PIL Image
        img = Image.fromarray(img.squeeze().numpy(), mode="RGB")

        if self.transform is not None:
            img = self.transform(img)

After Change


        item_A = img_pair[:, :, :half_w]
        item_B = img_pair[:, :, half_w:]

        return {"A": item_A, "B": item_B}

    def __len__(self):
        return len(self.files)
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 3

Instances


Project Name: eriklindernoren/PyTorch-GAN
Commit Name: 8f420a3b35944dcfa470dee958ef61dee221ce02
Time: 2018-04-23
Author: eriklindernoren@gmail.com
File Name: implementations/dualgan/datasets.py
Class Name: MNISTM
Method Name: __getitem__


Project Name: rusty1s/pytorch_geometric
Commit Name: 675b7884c09875486fdddffa2d8a6a12247ab4d7
Time: 2020-05-31
Author: matthias.fey@tu-dortmund.de
File Name: torch_geometric/utils/convert.py
Class Name:
Method Name: to_networkx


Project Name: rusty1s/pytorch_geometric
Commit Name: a998e7a1fa996edb4bcc1b34a0df5967ed6ec9e2
Time: 2020-05-13
Author: matthias.fey@tu-dortmund.de
File Name: torch_geometric/utils/convert.py
Class Name:
Method Name: to_networkx