Wheest opened a new pull request #7050: URL: https://github.com/apache/tvm/pull/7050
This pull request adds sparse conv2d implementations to CPU for TOPI. I have implemented sparse GEMM convolution, and sparse direct convolution for the NCHW data layout, using the CSR sparse data format. The extension to the C++ runtime is pretty stable. The code for TOPI is not clean or very well integrated yet, but I am looking for some guidance from other developers. [This gist](https://gist.github.com/Wheest/94433f73ff3279669bf35adcc38b321d) has a simple example of running a single layer Conv2D network with sparsity. You can choose what algorithm the Relay strategy uses with the two environment variables: ``` export TVM_DIRECT_CONV=1 export TVM_GEMM_CONV=0 ``` Comments on how to improve the integration appreciated. Further pull requests could add other sparse algorithms, and sparse data formats. I am in the process of creating sparse versions for GPU runtimes, but am having some difficulties I am discussing on the [Discuss](https://discuss.tvm.apache.org/t/sparse-opencl-error-scheduling-sparse-computations-that-use-tir-ir-builder/). ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
