Turn on gemm unit tests (#997)

This PR is to turn on a few gemm unit test with int8 input datatype. Before rocm4.4, int8 input data type requires matrix size to be no less than 4 in rocblas implementation. Because of this limitation, we turned off a few gemm unit tests with int8 input data type.

This limitation is removed in rocm4.4, so after we upgrade to rocm4.5, we can turn on these unit tests. Also we change to unit test conv_bn_add to adding instructions to module instead of program.
Co-authored-by: kahmed10 <15948690+kahmed10@users.noreply.github.com>

test/verify/main.cpp

@@ -45,14 +45,6 @@ int main(int argc, const char* argv[])
     run_verify rv;
     rv.add_validation_for("gpu", &validate_gpu);
     rv.disable_test_for("cpu", {"test_if_lp", "test_if_param", "test_if_literal"});
-    rv.disable_test_for("gpu",
-                        {"batch_quant_dot_2",
-                         "batch_quant_dot_3",
-                         "batch_quant_dot_5",
-                         "quant_dot_3args_1",
-                         "quant_dot_3args_2",
-                         "quant_dot_3args_3",
-                         "quant_dot_3args_4",
-                         "quant_dot_3args_5"});
+    rv.disable_test_for("gpu", {"test_conv_bn_add"});
     rv.run(argc, argv);
 }

test/verify/test_conv_bn_add.cpp

@@ -2,44 +2,44 @@
 #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& m,
+                                            migraphx::instruction_ref x,
+                                            std::size_t channels,
+                                            std::size_t seed = 1)
+    {
+        migraphx::shape vars{migraphx::shape::float_type, {channels}};
+        auto scale    = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 1 + seed)));
+        auto bias     = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 2 + seed)));
+        auto mean     = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 3 + seed)));
+        auto variance = m.add_literal(migraphx::abs(migraphx::generate_literal(vars, 4 + seed)));
+        return m.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;
+        auto* mm              = p.get_main_module();
+        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::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);
+        mm->add_instruction(migraphx::make_op("relu"), sum);
+        return p;
+    }
+};