Formatting

src/onnx/onnx.cpp

@@ -105,7 +105,8 @@ struct onnx_parser
     parse_softmax(const std::string&, const attribute_map&, std::vector<instruction_ref> args)
     {
         auto dims = args.front()->get_shape().lens();
-        auto r = prog.add_instruction(op::reshape{{long(dims[0]), long(dims[1]), 1, 1}}, args.front());
+        auto r =
+            prog.add_instruction(op::reshape{{long(dims[0]), long(dims[1]), 1, 1}}, args.front());
         auto s = prog.add_instruction(op::softmax{}, r);
         return prog.add_instruction(op::reshape{{long(dims[0]), long(dims[1])}}, s);
     }
@@ -231,10 +232,10 @@ struct onnx_parser
     instruction_ref
     parse_batchnorm(const std::string&, attribute_map attributes, std::vector<instruction_ref> args)
     {
-        float epsilon                                 = 1e-5f;
-        float momentum                                = 0.9f;
+        float epsilon                                     = 1e-5f;
+        float momentum                                    = 0.9f;
         op::batch_norm_inference::bn_infer_mode_t bn_mode = op::batch_norm_inference::spatial;
-        bool is_test                                  = false;
+        bool is_test                                      = false;
         if(contains(attributes, "epsilon"))
         {
             epsilon = parse_value(attributes.at("epsilon")).at<float>();

test/onnx/onnx_test.cpp

@@ -72,7 +72,7 @@ void pytorch_conv_relu_maxpool_x2()
     auto l4       = p.add_instruction(migraph::op::broadcast{axis}, l3, l2);
     auto l5       = p.add_instruction(migraph::op::add{}, l3, l4);
     auto l6       = p.add_instruction(migraph::op::activation{"relu"}, l5);
-    auto l7       = p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
+    auto l7 = p.add_instruction(migraph::op::pooling{"max", {{0, 0}}, {{2, 2}}, {{2, 2}}}, l6);
 
     auto l8  = p.add_parameter("3", {migraph::shape::float_type, {1, 5, 5, 5}});
     auto l9  = p.add_parameter("4", {migraph::shape::float_type, {1}});

test/op_shape_test.cpp

@@ -117,16 +117,18 @@ void reshape_shape()
 void flatten_shape()
 {
     migraph::shape input{migraph::shape::float_type, {2, 4, 6, 8}};
-    expect_shape(
-        migraph::shape{migraph::shape::float_type, {1, 2 * 4 * 6 * 8}}, migraph::op::flatten{0}, input);
+    expect_shape(migraph::shape{migraph::shape::float_type, {1, 2 * 4 * 6 * 8}},
+                 migraph::op::flatten{0},
+                 input);
     expect_shape(
         migraph::shape{migraph::shape::float_type, {2, 4 * 6 * 8}}, migraph::op::flatten{1}, input);
     expect_shape(
         migraph::shape{migraph::shape::float_type, {2 * 4, 6 * 8}}, migraph::op::flatten{2}, input);
     expect_shape(
         migraph::shape{migraph::shape::float_type, {2 * 4 * 6, 8}}, migraph::op::flatten{3}, input);
-    expect_shape(
-        migraph::shape{migraph::shape::float_type, {2 * 4 * 6 * 8, 1}}, migraph::op::flatten{4}, input);
+    expect_shape(migraph::shape{migraph::shape::float_type, {2 * 4 * 6 * 8, 1}},
+                 migraph::op::flatten{4},
+                 input);
     throws_shape(migraph::op::flatten{5}, input);
 }