add onnx test for reduce_mean

src/onnx/onnx.cpp

@@ -96,6 +96,7 @@ struct onnx_parser
         add_mem_op("LSTM", &onnx_parser::parse_lstm);
         add_mem_op("Pad", &onnx_parser::parse_pad);
         add_mem_op("ReduceSum", &onnx_parser::parse_reduce_sum);
+        add_mem_op("ReduceMean", &onnx_parser::parse_reduce_mean);
 
         // init the activation function map
         init_actv_func();
@@ -1321,6 +1322,39 @@ struct onnx_parser
         }
     }
 
+    instruction_ref parse_reduce_mean(const std::string&,
+                                     attribute_map attributes,
+                                     std::vector<instruction_ref> args)
+    {
+        std::size_t n_dim = args.front()->get_shape().lens().size();
+
+        // default to reduce over all dimensions
+        std::vector<int64_t> axes(n_dim);
+        std::iota(axes.begin(), axes.end(), 0);
+        if(contains(attributes, "axes"))
+        {
+            axes.clear();
+            auto&& attr_axes = attributes["axes"].ints();
+            axes             = std::vector<int64_t>(attr_axes.begin(), attr_axes.end());
+        }
+
+        int keep_dims = 1;
+        if(contains(attributes, "keepdims"))
+        {
+            keep_dims = parse_value(attributes.at("keepdims")).at<int>();
+        }
+
+        if(keep_dims == 1)
+        {
+            return prog.add_instruction(op::reduce_mean{axes}, std::move(args));
+        }
+        else
+        {
+            auto ins = prog.add_instruction(op::reduce_mean{axes}, std::move(args));
+            return prog.add_instruction(op::squeeze{axes}, ins);
+        }
+    }
+
     void parse_from(std::istream& is)
     {
         onnx::ModelProto model;

test/onnx/onnx_test.cpp

@@ -862,8 +862,8 @@ TEST_CASE(reducemean_test1)
 TEST_CASE(reducemean_test2)
 {
     migraphx::program p;
-    auto l0 = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
-    auto l1 = p.add_instruction(migraphx::op::reduce_sum{{2}}, l0);
+    auto l0   = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
+    p.add_instruction(migraphx::op::reduce_mean{{2}}, l0);
     auto prog = migraphx::parse_onnx("reducemean_test2.onnx");
 
     EXPECT(p == prog);