[GitHub] [tvm] AndrewZhaoLuo commented on a change in pull request #9329: [Relay/TOPI][ONNX/TFLite] Refactor MATRIX_SET_DIAG Operator for Relay…

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AndrewZhaoLuo commented on a change in pull request #9329:
URL: https://github.com/apache/tvm/pull/9329#discussion_r734250090



##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -4226,6 +4226,35 @@ def _impl_v1(cls, inputs, attr, params):
         return _expr.TupleWrapper(_expr.Tuple(result), len(result))
 
 
+class Trilu(OnnxOpConverter):
+    """Operator converter for Trilu"""
+    
+    @classmethod
+    def _impl_v1(cls, inputs, attr, params):

Review comment:
       this should be opset14 so _impl_v14

##########
File path: python/tvm/relay/frontend/onnx.py
##########
@@ -4226,6 +4226,35 @@ def _impl_v1(cls, inputs, attr, params):
         return _expr.TupleWrapper(_expr.Tuple(result), len(result))
 
 
+class Trilu(OnnxOpConverter):
+    """Operator converter for Trilu"""
+    
+    @classmethod
+    def _impl_v1(cls, inputs, attr, params):
+        upper = attr.get("upper")

Review comment:
       suggest attr.get("upper", 1) since this appears to be the default

##########
File path: include/tvm/topi/transform.h
##########
@@ -1776,12 +1775,10 @@ inline Tensor matrix_set_diag(const Tensor& input, const Tensor& diagonal, int k
           for (size_t i = 0; i < ndim - 1; i++) {
             diagonal_indices.push_back(iter_vars[i]);
           }
-          if (only_one_diagonal) {
-            k = k1;
-          } else {
+          auto multi_diagonals = [&]() {
             // Determining which diagonal/sub-diagonal/super-diagonal it is
             k = iter_vars[ndim] - iter_vars[ndim - 1];
-            diagonal_indices.push_back(k2 - k);
+            diagonal_indices.push_back(k2(0) - k);

Review comment:
       I believe (though please check) that you can just do k2() for 0-D tensor access.




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