antimora opened a new issue #4587: [Feature] Support for 1D Convolution URL: https://github.com/apache/incubator-tvm/issues/4587 I was trying to import my ONNX model but it has failed with the following error: ``` $ /usr/bin/python3 /workspace/trouble_onnx.py Traceback (most recent call last): File "/workspace/trouble_onnx.py", line 15, in <module> mod, params = relay.frontend.from_onnx(onnx_model, shape_dict) File "/workspace/python/tvm/relay/frontend/onnx.py", line 1553, in from_onnx mod, params = g.from_onnx(graph, opset) File "/workspace/python/tvm/relay/frontend/onnx.py", line 1381, in from_onnx op = self._convert_operator(op_name, inputs, attr, opset) File "/workspace/python/tvm/relay/frontend/onnx.py", line 1481, in _convert_operator sym = convert_map[op_name](inputs, attrs, self._params) File "/workspace/python/tvm/relay/frontend/onnx.py", line 246, in _impl_v1 custom_check=dimension_constraint())(inputs[:2], attr, params) File "/workspace/python/tvm/relay/frontend/common.py", line 377, in __call__ raise RuntimeError("Check failed: {}".format(msg)) RuntimeError: Check failed: Only 2d kernel supported. ``` Code is the latest version (master@1900041447cc7fd4f23a857c4839acbf74cd890c) as of now. I noticed @tqchen closed [this related issue #3518](https://github.com/apache/incubator-tvm/issues/3518#event-2898116737) recently but not explanation was given. Could it be because [this related PR](https://github.com/apache/incubator-tvm/pull/4476) was merged? I would really love if TVM adds 1D Conv support. It would be tremendous for speech processing projects. To help with debugging and development, I am attaching onnx model and graph image. [trouble.zip](https://github.com/apache/incubator-tvm/files/4002130/trouble.zip) You can run the following python code to reproduce an error: ```python import onnx import numpy as np import tvm.relay as relay onnx_model = onnx.load('trouble.onnx') input1 = np.random.rand(1, 192, 100) input2 = np.random.rand(1) shape_dict = {'1': input1.shape, 'x.1': input2.shape} mod, params = relay.frontend.from_onnx(onnx_model, shape_dict) ```
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