Hello @haozech. There are two ways you can go about benchmarking a single operator. You can either 1. benchmark a specific implementation of the operator or 2. benchmark all implementations of the operator.
For 1, follow the [Tuning High Performance Convolution on NVIDIA GPUs](https://tvm.apache.org/docs/tutorials/autotvm/tune_conv2d_cuda.html) tutorial, but skip section 1. In section two, replace `"tutorial/conv2d_no_batching"` in `task = autotvm.task.create("tutorial/conv2d_no_batching", args=(N, H, W, CO, CI, KH, KW, strides, padding), target="cuda")` with the name of the implementation you want to benchmark. You can find the name of the implementation by greping the codebase for `@autotvm.register_topi_compute`. You'll also have to modify the inputs to they match what the function is expecting. Furthermore, you'll have to change `conv2d_no_batching` and `conv2d_nchw_python` in the last code block with the correct function names (these should be the name of the function annotated with `@autotvm.register_topi_compute`). For 2, follow the [Auto-tuning a convolutional network for NVIDIA GPU](https://tvm.apache.org/docs/tutorials/autotvm/tune_relay_cuda.html) tutorial. Replace `get_network` with a function that returns a relay function with a single operator like so: ``` x = relay.Var("x", tvm.relay.TensorType([40, 40])) y = relay.Var("y", tvm.relay.TensorType([40, 40])) mod = relay.Function( [x, y], relay.my_function(x, y) ) ``` --- [Visit Topic](https://discuss.tvm.apache.org/t/how-can-i-test-the-performance-of-a-single-operator/8362/2) 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/b74575d4c7f5d2b0894f8cf942f2ce25244e267cad638a71bc9b4cf1da48c22c).
