formatting

src/include/migraphx/op/convolution.hpp

@@ -83,7 +83,8 @@ struct convolution
         //          static_cast<std::size_t>(std::ceil(
         //              static_cast<double>(input.lens()[2] - weights.lens()[2] + 1) / stride[0])),
         //          static_cast<std::size_t>(std::ceil(
-        //              static_cast<double>(input.lens()[3] - weights.lens()[3] + 1) / stride[1]))}};
+        //              static_cast<double>(input.lens()[3] - weights.lens()[3] + 1) /
+        //              stride[1]))}};
         // }
         // else
         // {

src/include/migraphx/op/pooling.hpp

@@ -56,13 +56,13 @@ struct pooling
                     input.lens()[1],
                     std::size_t(std::max<std::ptrdiff_t>(
                         1,
-                            floor_divide<std::ptrdiff_t>(
-                                input.lens()[2] + 2 * padding[0] - lengths[0], stride[0]) +
+                        floor_divide<std::ptrdiff_t>(input.lens()[2] + 2 * padding[0] - lengths[0],
+                                                     stride[0]) +
                             1)),
                     std::size_t(std::max<std::ptrdiff_t>(
                         1,
-                            floor_divide<std::ptrdiff_t>(
-                                input.lens()[3] + 2 * padding[1] - lengths[1], stride[1]) +
+                        floor_divide<std::ptrdiff_t>(input.lens()[3] + 2 * padding[1] - lengths[1],
+                                                     stride[1]) +
                             1)),
                 }};
         // }
@@ -83,10 +83,12 @@ struct pooling
         //             input.lens()[1],
         //             std::size_t(std::max<std::ptrdiff_t>(
         //                 1,
-        //                 floor_divide<std::ptrdiff_t>(input.lens()[2] - lengths[0], stride[0]) + 1)),
+        //                 floor_divide<std::ptrdiff_t>(input.lens()[2] - lengths[0], stride[0]) +
+        //                 1)),
         //             std::size_t(std::max<std::ptrdiff_t>(
         //                 1,
-        //                 floor_divide<std::ptrdiff_t>(input.lens()[3] - lengths[1], stride[1]) + 1)),
+        //                 floor_divide<std::ptrdiff_t>(input.lens()[3] - lengths[1], stride[1]) +
+        //                 1)),
         //         }};
         // }
         // else

src/targets/gpu/device/pad.cpp

@@ -15,16 +15,14 @@ argument
 pad(hipStream_t stream, argument result, argument arg1, float value, std::vector<std::int64_t> pads)
 {
     std::size_t nelements = arg1.get_shape().elements();
-    if(float_equal(value,std::numeric_limits<float>::lowest()))
+    if(float_equal(value, std::numeric_limits<float>::lowest()))
     {
         visit_all(result)([&](auto output) {
             auto* outptr = device_cast(output.data());
-                auto val = device_cast(std::numeric_limits<typename
-                        decltype(output)::value_type>::lowest());
+            auto val =
+                device_cast(std::numeric_limits<typename decltype(output)::value_type>::lowest());
 
-                    gs_launch(stream, nelements)([=](auto i) {
-                        outptr[i] = val;
-                    });
+            gs_launch(stream, nelements)([=](auto i) { outptr[i] = val; });
         });
     }
 
@@ -32,9 +30,7 @@ pad(hipStream_t stream, argument result, argument arg1, float value, std::vector
     {
         visit_all(result)([&](auto output) {
             auto* outptr = device_cast(output.data());
-                    gs_launch(stream, nelements)([=](auto i) {
-                        outptr[i] = value;
-                    });
+            gs_launch(stream, nelements)([=](auto i) { outptr[i] = value; });
         });
     }