Which is the best way to test a new architecture



I followed all the tutorials and everything worked, but when I try to import a very specific NN architecture of mine I receive several errors. I’ve tried to import an implementation from Keras and from TensorFlow but both had unsupported characteristics. So I am thinking of reimplementing the architecture to work with TVM, but my question is: is it better to write it directly with the TVM framework? If so, where can I found some examples of it? If it is better to use another framework, which one has better support for import to TVM?

Thank you!


It’s better to write in other frameworks because currently tvm does not support training.

I think MXNet has the best compatability. You can find some examples in this folder https://github.com/dmlc/tvm/blob/94acff30e82f9352e1652bd81be260b672419aea/nnvm/python/nnvm/testing/dqn.py#L29
Most of them are ported from mxnet.

If the “unsupported characteristics” are new operators, you can try to add these operators to tvm.