[GitHub] [tvm] Tantalus13A98B5F commented on pull request #8605: [TOPI] [Relay] Sparse Conv2d Implementation for 3x3 kernels

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Tantalus13A98B5F commented on pull request #8605:
URL: https://github.com/apache/tvm/pull/8605#issuecomment-1039458148


   Hi @mengbingrock 
   Not sure how long have you been going, but `bsr_conv2d.convert2` is merely for graph & param transformation, and it assumes well-padded shapes (0 for 1x1 and 1 for 3x3). Maybe you will want to tweak the implementation of this.
   
   `spconv2d_3x3_nhwc` is the target-specialized implementation for the operator. In TVM, for every operator, we will want to [register it with Relay](https://tvm.apache.org/docs/dev/how_to/relay_add_op.html) so that we can use the operator in a graph. For the case of sparse operators, we would also like to provide transformations like `bsr_conv2d.convert2` to generate sparse graphs out of dense graphs. If we want our implementation to be visible for users, we have to fix all the code along the way.
   
   For early-stage testing purposes, it's not necessary to do all the stuff at once. You can directly pass ndarrays to a scheduled template; if you have finished the Relay integration you can then manually compose a sparse graph for testing; once you've done the former steps you can consider tweaking the convert function.


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