While training CRNN for text prediction, I found that best path decoding predicts more properly and clearly compared to beam width. Beam width decoding results tended to be excessively messy.
paper link Key Points set forget bias to 1 when training LSTM layers to get GRU comparable results in language models, lstm is better than gru
from nvidia docs 2.3.1. Installing from a Tar File Navigate to your <cudnnpath> directory containing the cuDNN Tar file. Unzip the cuDNN package. $ tar -xzvf cudnn-9.0-linux-x64-v7.tgz Copy the following files into the CUDA Toolkit directory, and change the file permissions. $ sudo cp cuda/include/cudnn.h /usr/local/cuda/include $ sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64 Read more…