napronald opened a new pull request, #20053: URL: https://github.com/apache/tvm/pull/20053
## Summary Fixes two issues in the Relax ONNX `LpPool` converter: - Computes `|x|^p` instead of `x^p`, matching the [official ONNX reference implementation](https://github.com/onnx/onnx/blob/main/onnx/reference/ops/op_pool_common.py#L255). - Passes the TVM dtype directly to `relax.const`, avoiding a NumPy dtype conversion failure. ## Minimal reproduce ```python import onnx from tvm.relax.frontend.onnx import from_onnx model = onnx.helper.make_model( onnx.helper.make_graph( [ onnx.helper.make_node( "LpPool", ["x"], ["y"], kernel_shape=[2], strides=[1], p=1, ) ], "lppool_repro", [onnx.helper.make_tensor_value_info("x", onnx.TensorProto.FLOAT, [1, 1, 4])], [onnx.helper.make_tensor_value_info("y", onnx.TensorProto.FLOAT, [1, 1, 3])], ), opset_imports=[onnx.helper.make_opsetid("", 18)], ) print(from_onnx(model, opset=18).script()) ``` conversion failed with: ```text ValueError: Could not convert T.float32 to a NumPy dtype ``` -- 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. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
