Version v1.0.11 Release

• Fix pointer arithmetic and handling of half type
• Add functions: IsInf, IsNaN, ResetNaN, ResetInf, and Where
• Feature/20190121 build with python35
• Print error for cuda ver less than 7
• Use dedicated function to determine workspace size for alogorithm.
• Add CuDNN max and average pooling for 3D case.
• Serialization of SolverState
• Fix CuDNN reduction for output shape equal input shape.
• Fix binary functions

Install the latest nnabla by:

pip install nnabla
pip install nnabla_ext_cuda  # For CUDA users

Users with python <= 3.4 may experience errors with pip install nnabla and pip install nnabla-ext-cuda.
■ Workaround
Please install matplotlib == 2.2.3 and re-install nnabla, nnabla_ext_cuda.

pip install matplotlib==2.2.3
pip install nnabla
pip install nnabla_ext_cuda

Note that CUDA 9.2 and cuDNN 7.3 are set as default if versions are not specified. You can also install the cuda extension with specific versions from one of the following. See also FAQ

• nnabla-ext-cuda80 (CUDA 8.0 x cuDNN 7.1)
• nnabla-ext-cuda90 (CUDA 9.0 x cuDNN 7.3)
• nnabla-ext-cuda92 (CUDA 9.2 x cuDNN 7.3)
• nnabla-ext-cuda100 (CUDA 10.0 x cuDNN 7.3)

pip install nnabla
pip install nnabla_ext_cuda92  # For CUDA 9.2 x cuDNN 7.3 users

Additional setup may be required depending on your OS or environment. Please check Python Package Installation Guide for details.

Install Guide

To use C++ inference feature, follow the demonstration on MNIST inference in C++.

Demonstration

For distributed training, you need to build a binary from source. See the guide for building multi-GPU training package.

Build Guide