codeislife99 commented on a change in pull request #7126:
URL: https://github.com/apache/tvm/pull/7126#discussion_r550291956



##########
File path: src/relay/op/tensor/transform.cc
##########
@@ -1553,6 +1553,65 @@ RELAY_REGISTER_OP("meshgrid")
     .set_attr<FTVMCompute>("FTVMCompute", MeshgridCompute)
     .set_attr<TOpPattern>("TOpPattern", kInjective);
 
+TVM_REGISTER_NODE_TYPE(SparseFillEmptyRowsAttrs);
+
+bool SparseFillEmptyRowsRel(const Array<Type>& types, int num_inputs, const 
Attrs& attrs,
+                            const TypeReporter& reporter) {
+  // types: [ sparse_indices, sparse_values, default_values, result]
+  ICHECK_EQ(types.size(), 4) << "SparseFillEmptyRowsRel expects 4 arguments 
but provided "
+                             << types.size();
+  std::vector<Type> fields;
+  auto sparse_indices = types[0].as<TensorTypeNode>();
+  auto default_value = types[2].as<TensorTypeNode>();
+  const auto* param = attrs.as<SparseFillEmptyRowsAttrs>();
+  ICHECK(param != nullptr);
+
+  Array<IndexExpr> sp_ordered_output_shape;
+  sp_ordered_output_shape.push_back(param->dense_shape[0] + 
sparse_indices->shape[0]);
+  if (sparse_indices->shape.size() > 1) {
+    sp_ordered_output_shape.push_back(sparse_indices->shape[1]);
+  }
+  fields.push_back(TensorType(sp_ordered_output_shape, sparse_indices->dtype));
+  fields.push_back(TensorType(Array<PrimExpr>{param->dense_shape[0]}, 
tvm::DataType::Bool()));
+  fields.push_back(TensorType(Array<PrimExpr>{sp_ordered_output_shape[0]}, 
default_value->dtype));
+  fields.push_back(TensorType(Array<PrimExpr>{1}, tvm::DataType::Int(32)));
+  reporter->Assign(types[3], TupleType(Array<Type>(fields)));
+  return true;
+}
+
+Array<te::Tensor> SparseFillEmptyRowsCompute(const Attrs& attrs, const 
Array<te::Tensor>& inputs,
+                                             const Type& out_type) {
+  ICHECK_EQ(inputs.size(), 3) << "SparseFillEmptyRowsCompute expects 3 
arguments but provided "
+                              << inputs.size();
+  const auto* param = attrs.as<SparseFillEmptyRowsAttrs>();
+  ICHECK(param != nullptr);
+  return {topi::SparseFillEmptyRows(inputs[0], inputs[1], inputs[2], 
param->dense_shape)};
+}
+
+Expr MakeSparseFillEmptyRows(Expr sparse_indices, Expr sparse_values, Expr 
default_value,
+                             Array<Integer> dense_shape) {
+  auto attrs = make_object<SparseFillEmptyRowsAttrs>();
+  attrs->dense_shape = std::move(dense_shape);
+  static const Op& op = Op::Get("sparse_fill_empty_rows");
+  return Call(op, {sparse_indices, sparse_values, default_value}, 
Attrs(attrs), {});
+}
+
+TVM_REGISTER_GLOBAL("relay.op._make.sparse_fill_empty_rows")
+    .set_body_typed(MakeSparseFillEmptyRows);
+
+RELAY_REGISTER_OP("sparse_fill_empty_rows")
+    .describe(R"code(Return representation of a sparse tensor with empty rows 
filled with default 
+    value.)code" TVM_ADD_FILELINE)
+    .set_num_inputs(3)
+    .set_attrs_type<SparseFillEmptyRowsAttrs>()
+    .add_argument("sparse_indices", "Tensor", "The first tensor")

Review comment:
       Done.




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