srkreddy1238 commented on code in PR #13834:
URL: https://github.com/apache/tvm/pull/13834#discussion_r1087433807
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src/runtime/contrib/clml/clml_runtime.cc:
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@@ -1151,13 +1159,14 @@ class CLMLRuntime : public JSONRuntimeBase {
cl_arithmetic_mode_qcom cl_arithmetic_mode = MakeCLArithMode(cl_dtype);
int inputSize = input_.size();
auto output = MakeCLMLTensorFromJSONNode(node,
CL_TENSOR_LAYOUT_OPTIMAL_QCOM, cl_dtype);
+ cl_uint axis =
std::stoi(node.GetAttr<std::vector<std::string>>("axis")[0]);
cl_ml_tensor_qcom* concatInputs = new cl_ml_tensor_qcom[inputSize];
for (int i = 0; i < inputSize; i++) {
auto input = MakeCLMLTensorFromJSONEntry(node.GetInputs()[i], {},
CL_TENSOR_LAYOUT_OPTIMAL_QCOM,
cl_dtype);
concatInputs[i] = input->tensor;
}
- cl_ml_op_concat_desc_qcom concatDesc = {1, (cl_uint)inputSize,
cl_arithmetic_mode};
+ cl_ml_op_concat_desc_qcom concatDesc = {axis, (cl_uint)inputSize,
cl_arithmetic_mode};
Review Comment:
Till them probably we can limit it in frontend ```clml.py``` and let it take
TVM path for ```axis != 1``` instead of failing at run time.
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