Custom dataset using libtorch review request

Hey everyone,

I am running into a bit of trouble with an undefined reference when creating a custom dataset class using libtorch. May I ask for a code review to help clarify some things?

here is my data.hpp:

#pragma once

#include <torch/torch.h>

namespace rock {
namespace data {
namespace datasets {

/// Random dataset.
class RandomDataset : public torch::data::Dataset<RandomDataset> {
     public:
          /// The mode in which the dataset is loaded.
          enum class Mode { kTrain, kTest };

          explicit RandomDataset(Mode mode = Mode::kTrain);

	      /// Returns the `Example` at the given `index`.
	     torch::data::Example<> get(size_t index) override;

	     /// Returns the size of the dataset.
	     torch::optional<size_t> size() const override;

	      /// Returns true if this is the training subset of MNIST.
          bool is_train() const noexcept;

          /// Returns all images stacked into a single tensor.
          const torch::Tensor& images() const;

          /// Returns all targets stacked into a single tensor.
          const torch::Tensor& labels() const;

     private:
	      torch::Tensor images_, labels_;
};
} // namespace datasets
} // namespace data
} // namespace rock

And my data.cpp:

#include <torch/torch.h>
#include "data.hpp"

namespace rock {
namespace data {
namespace datasets {
namespace {

constexpr uint32_t kTrainSize = 60000;
constexpr uint32_t kNumChannels = 3;
constexpr uint32_t kImageRows = 256;
constexpr uint32_t kImageColumns = 256;

// Create random images
torch::Tensor load_images() {
    torch::Tensor tensor = torch::randint(
        /*low=*/0, /*high=*/255, 
        {kTrainSize, kImageRows, kImageColumns, kNumChannels}
    ); 
    
    return tensor.to(torch::kFloat32).div_(255);
}

// Create labels - all ones.
torch::Tensor load_labels() {
    torch::Tensor tensor = torch::ones({kTrainSize}, torch::kInt);
    return tensor.to(torch::kInt64);
}
} // namespace

RandomDataset::RandomDataset(Mode mode)
    : images_(load_images()),
      labels_(load_labels()) {}

torch::data::Example<> RandomDataset::get(size_t index) {
    return {images_[index], labels_[index]};
}

torch::optional<size_t> RandomDataset::size() const {
    return images_.size(0);
}

bool RandomDataset::is_train() const noexcept {
    return images_.size(0) == kTrainSize;
}

const torch::Tensor& RandomDataset::images() const {
    return images_;
}

const torch::Tensor& RandomDataset::labels() const {
    return labels_;
}

} // namespace datasets
} // namespace data
} // namespace rock

I saw that @mhubii linked a good reference implementation for a custom dataset here: (libtorch) How to use torch::data::datasets for custom dataset? . Not quite sure where I am getting stuck on this reference.

I was structuring my code to be similar to the mnist.cpp.

I appreciate your help and comments!

Messed up my CMakeLists.txt :man_facepalming:. That took care of the reference. Everything compiles fine, but now seems to hang when initializing that dataset:

auto dataset = rock::data::datasets::RandomDataset()
    .map(torch::data::transforms::Stack<>());

And another false alarm, I was creating random tensors of shape {60_000, 256, 256, 3} and my workstation was taking longer than expected. Everything is running well!

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