Related Issues (20)
- Implement conv2d, max pooling, flatten, dropout, batch norm layers
- Checkpoints and model save/load (.h5)
- CMake, GTest and CUDA
- Refactoring
- Python bindings
- Create our own tensors
- Improve dense layer HOT 2
- Use xtensor
- Autodiff engine (sequence, GAN models)
- Add tests and docs
- Add prophecy to pip package index
- Improve model
- Prophecy 2.0
- Implement a Dataset class
- Global refactoring
- Implement Conv2D, MaxPooling and Flatten layers
- Bug: depending on batch_size not all samples are used for the training
- Tensor implicit transpose
- Setup CUDA (op inplace, matmul, batch parallelization)
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