enable a gpu unit test

test/verify/test_conv_bn_add.cpp

@@ -2,44 +2,43 @@
 #include "verify_program.hpp"
 #include <migraphx/program.hpp>
 #include <migraphx/generate.hpp>
-#include <migraphx/op/common.hpp>
+#include <migraphx/make_op.hpp>
 
-// struct test_conv_bn_add : verify_program<test_conv_bn_add>
-// {
-//     static migraphx::instruction_ref add_bn(migraphx::program& p,
-//                                             migraphx::instruction_ref x,
-//                                             std::size_t channels,
-//                                             std::size_t seed = 1)
-//     {
-//         migraphx::shape vars{migraphx::shape::float_type, {channels}};
-//         auto scale    = mm->add_literal(migraphx::abs(migraphx::generate_literal(vars, 1 +
-//         seed))); auto bias     = mm->add_literal(migraphx::abs(migraphx::generate_literal(vars, 2
-//         + seed))); auto mean     = mm->add_literal(migraphx::abs(migraphx::generate_literal(vars,
-//         3 + seed))); auto variance =
-//         mm->add_literal(migraphx::abs(migraphx::generate_literal(vars, 4 + seed))); return
-//         mm->add_instruction(
-//             migraphx::op::batch_norm_inference{}, x, scale, bias, mean, variance);
-//     }
+struct test_conv_bn_add : verify_program<test_conv_bn_add>
+{
+    static migraphx::instruction_ref add_bn(migraphx::module_ref mm,
+                                            migraphx::instruction_ref x,
+                                            std::size_t channels,
+                                            std::size_t seed = 1)
+    {
+        migraphx::shape vars{migraphx::shape::float_type, {channels}};
+        auto scale    = mm->add_literal(migraphx::abs(migraphx::generate_literal(vars, 1 + seed))); 
+        auto bias     = mm->add_literal(migraphx::abs(migraphx::generate_literal(vars, 2 + seed))); 
+        auto mean     = mm->add_literal(migraphx::abs(migraphx::generate_literal(vars, 3 + seed))); 
+        auto variance = mm->add_literal(migraphx::abs(migraphx::generate_literal(vars, 4 + seed)));
+        return mm->add_instruction(migraphx::make_op("batch_norm_inference"), x, scale, bias, mean, variance);
+    }
 
-//     migraphx::program create_program() const
-//     {
-//         migraphx::program p;
-//         std::size_t ichannels = 64;
-//         std::size_t ochannels = 256;
-//         auto x     = mm->add_parameter("x", {migraphx::shape::float_type, {1, ichannels, 56,
-//         56}}); auto w     = mm->add_literal(migraphx::generate_literal(
-//             {migraphx::shape::float_type, {ochannels, ichannels, 1, 1}}, 1));
-//         auto y     = mm->add_parameter("y", {migraphx::shape::float_type, {1, ichannels, 56,
-//         56}}); auto v     = mm->add_literal(migraphx::generate_literal(
-//             {migraphx::shape::float_type, {ochannels, ichannels, 1, 1}}, 2));
-//         auto relu1 = mm->add_instruction(migraphx::op::relu{}, x);
-//         auto conv1 = mm->add_instruction(migraphx::op::convolution{}, relu1, w);
-//         auto bn1   = add_bn(p, conv1, ochannels, 1);
-//         auto relu2 = mm->add_instruction(migraphx::op::relu{}, y);
-//         auto conv2 = mm->add_instruction(migraphx::op::convolution{}, relu2, v);
-//         auto bn2   = add_bn(p, conv2, ochannels, 1);
-//         auto sum   = mm->add_instruction(migraphx::op::add{}, bn1, bn2);
-//         mm->add_instruction(migraphx::op::relu{}, sum);
-//         return p;
-//     }
-// };
+    migraphx::program create_program() const
+    {
+        migraphx::program p;
+        std::size_t ichannels = 64;
+        std::size_t ochannels = 256;
+        auto* mm = p.get_main_module();
+        auto x     = mm->add_parameter("x", {migraphx::shape::float_type, {1, ichannels, 56, 56}}); 
+        auto w     = mm->add_literal(migraphx::generate_literal({migraphx::shape::float_type, {ochannels, ichannels, 1, 1}}, 1));
+        auto y     = mm->add_parameter("y", {migraphx::shape::float_type, {1, ichannels, 56, 56}}); 
+        auto v     = mm->add_literal(migraphx::generate_literal({migraphx::shape::float_type, {ochannels, ichannels, 1, 1}}, 2));
+        auto relu1 = mm->add_instruction(migraphx::make_op("relu"), x);
+        auto conv1 = mm->add_instruction(migraphx::make_op("convolution"), relu1, w);
+        auto bn1   = add_bn(mm, conv1, ochannels, 1);
+        auto relu2 = mm->add_instruction(migraphx::make_op("relu"), y);
+        auto conv2 = mm->add_instruction(migraphx::make_op("convolution"), relu2, v);
+        auto bn2   = add_bn(mm, conv2, ochannels, 1);
+        auto sum   = mm->add_instruction(migraphx::make_op("add"), bn1, bn2);
+        auto r = mm->add_instruction(migraphx::make_op("relu"), sum);
+        mm->add_return({r});
+        
+        return p;
+    }
+};