In addition to registering the compute and schedule to Relay op strategy, you also need to register them as an AutoTVM task so that they can be extracted via `extract_from_program` and tuned. Specifically, you need to add the following decorators to your compute and schedule functions. Here I use `conv2d_nchw.cuda` as an example.
```python @autotvm.register_topi_compute("conv2d_nchw.cuda") def conv2d_nchw(cfg, data, kernel, strides, padding, dilation, out_dtype="float32"): # Compute function. @autotvm.register_topi_schedule("conv2d_nchw.cuda") def schedule_conv2d_nchw(cfg, outs): # Schedule function. ``` In this example, we registered an AutoTVM task `conv2d_nchw.cuda`. Since we also have the corresponding op strategy at https://github.com/apache/incubator-tvm/blob/main/python/tvm/relay/op/strategy/cuda.py#L128, this task will be extracted by `extract_from_program`. --- [Visit Topic](https://discuss.tvm.apache.org/t/how-to-add-new-scheduler-in-auto-tvm/8433/3) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/4764e589ed6f7f1a75f4425f72c6ea1e00ffadff212387c4b77cee99b6fcc663).