Deep Learning with PyTorch

Creating a dataset and loaders

We will use the same FeaturesDataset class that we created for ResNet and use it to create data loaders for the train and validation dataset in the following code:

# Create dataset for train and validation convolution featurestrn_feat_dset = FeaturesDataset(trn_features,trn_labels)val_feat_dset = FeaturesDataset(val_features,val_labels)# Create data loaders for batching the train and validation datasetstrn_feat_loader = DataLoader(trn_feat_dset,batch_size=64,shuffle=True,drop_last=True)val_feat_loader = DataLoader(val_feat_dset,batch_size=64)

Time to create the model and train it.