Haste 0.4.0

Added

• New layer normalized GRU layer (LayerNormGRU).
• New IndRNN layer.
• CPU support for all PyTorch layers.
• Support for building PyTorch API on Windows.
• Added state argument to PyTorch layers to specify initial state.
• Added weight transforms to TensorFlow API (see docs for details).
• Added get_weights method to extract weights from RNN layers (TensorFlow).
• Added to_native_weights and from_native_weights to PyTorch API for LSTM and GRU layers.
• Validation tests to check for correctness.

Changed

• Performance improvements to GRU layer.
• BREAKING CHANGE: PyTorch layers default to CPU instead of GPU.
• BREAKING CHANGE: h must not be transposed before passing it to gru::BackwardPass::Iterate.

Fixed

• Multi-GPU training with TensorFlow caused by invalid sharing of cublasHandle_t.