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I have trained a 3D convnet using mxnet. I saved the network architecture and parameters with an intention of testing more data with it to check its performance. Since I am not training, I do not want to obtain batches of the dataset. How do I get the network to read in the entire dataset as input? Just passing the network the dataset object directly is only a 4D tensor whereas the network wants 5D. Right now I am using the dataloader but setting batch size as the entire dataset, and I feel like there is a more efficient way to do this.

accAscrub
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1 Answers1

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DataLoader requires either a batch_size or a BatchSampler. In theory, you could write a BatchSampler that fetches the entire dataset as one batch, though I don't think you'll see a significant performance gain if your batch size is significantly large. Additionally, using batches is beneficial if you have more than one worker - have you considered using num_workers > 0 to take advantage of parallel processing?

Vishaal
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