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Contents
## 0.2.3 (2020-04-28) - Added `show_config` and `parallel_info` methods - Added `initial_seed` and `seed` methods to `Random` - Improved data loader - Build with MKL-DNN and NNPACK when available - Fixed `inspect` for modules ## 0.2.2 (2020-04-27) - Added support for saving tensor lists - Added `ndim` and `ndimension` methods to tensors ## 0.2.1 (2020-04-26) - Added support for saving and loading models - Improved error messages - Reduced gem size ## 0.2.0 (2020-04-22) - No longer experimental - Updated libtorch to 1.5.0 - Added support for GPUs and OpenMP - Added adaptive pooling layers - Tensor `dtype` is now based on Numo type for `Torch.tensor` - Improved support for boolean tensors - Fixed error with unbiased linear model ## 0.1.8 (2020-01-17) - Updated libtorch to 1.4.0 ## 0.1.7 (2020-01-10) - Fixed installation error with Ruby 2.7 ## 0.1.6 (2019-12-09) - Added recurrent layers - Added more pooling layers - Added normalization layers ## 0.1.5 (2019-12-06) - Added many more functions - Added tensor classes - `FloatTensor`, `LongTensor`, etc - Improved modules ## 0.1.4 (2019-12-01) - Added distance functions - Added more activations - Added more linear layers - Added more loss functions - Added more init methods - Added support for tensor assignment ## 0.1.3 (2019-11-30) - Changed to BSD 3-Clause license to match PyTorch - Added many optimizers - Added `StepLR` learning rate scheduler - Added dropout - Added embedding - Added support for `bool` type - Improved performance of `from_numo` ## 0.1.2 (2019-11-27) - Added SGD optimizer - Added support for gradient to `backward` method - Added `argmax`, `eq`, `leaky_relu`, `prelu`, and `reshape` methods - Improved indexing - Fixed `zero_grad` - Fixed error with infinite values ## 0.1.1 (2019-11-26) - Added support for `uint8` and `int8` types - Fixed `undefined symbol` error on Linux - Fixed C++ error messages ## 0.1.0 (2019-11-26) - First release
Version data entries
1 entries across 1 versions & 1 rubygems
Version | Path |
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torch-rb-0.2.3 | CHANGELOG.md |