Added test but not working

test/gpu/miopen.cpp

@@ -215,6 +215,82 @@ struct test_transpose
     }
 };
 
+struct test_batchnorm_inference
+{
+    const size_t width    = 3;
+    const size_t height   = 3;
+    const size_t channels = 3;
+    const size_t batches  = 4;
+
+    migraph::program create_program() const
+    {
+        migraph::program p;
+
+        migraph::shape s{migraph::shape::float_type, {batches, channels, height, width}};
+        migraph::shape vars{migraph::shape::float_type, {channels}};
+        auto x        = p.add_parameter("x", s);
+        auto mean     = p.add_parameter("mean", vars);
+        auto variance = p.add_parameter("variance", vars);
+        auto scale    = p.add_parameter("scale", vars);
+        auto bias     = p.add_parameter("bias", vars);
+        p.add_instruction(migraph::batch_norm_inference{}, x, mean, variance, scale, bias);
+        return p;
+    }
+
+    migraph::program::parameter_map create_params() const
+    {
+        migraph::program::parameter_map m;
+        migraph::shape s{migraph::shape::float_type, {batches, channels, height, width}};
+        migraph::shape vars{migraph::shape::float_type, {channels}};
+        m["x"]        = migraph::generate_argument(s);
+        m["mean"]     = migraph::generate_argument(vars);
+        m["variance"] = migraph::generate_argument(vars);
+        m["scale"]    = migraph::generate_argument(vars);
+        m["bias"]     = migraph::generate_argument(vars);
+        return m;
+    }
+};
+
+void batch_norm_inference_test()
+{
+    migraph::program p;
+    const size_t width = 2, height = 2, channels = 4, batches = 2;
+    const float x_val = 8.0f, mean_val = 2.0f, variance_val = 4.0f, scale_val = 2.0f,
+                bias_val   = 1.0f;
+    const float output_val = scale_val * (x_val - mean_val) / (std::sqrt(variance_val)) + bias_val;
+
+    migraph::shape s{migraph::shape::float_type, {batches, channels, height, width}};
+    migraph::shape vars{migraph::shape::float_type, {channels}};
+    std::vector<float> x_data(width * height * channels * batches);
+    std::vector<float> scale_data(channels);
+    std::vector<float> bias_data(channels);
+    std::vector<float> mean_data(channels);
+    std::vector<float> variance_data(channels);
+
+    std::fill(x_data.begin(), x_data.end(), x_val);
+    std::fill(mean_data.begin(), mean_data.end(), mean_val);
+    std::fill(variance_data.begin(), variance_data.end(), variance_val);
+    std::fill(scale_data.begin(), scale_data.end(), scale_val);
+    std::fill(bias_data.begin(), bias_data.end(), bias_val);
+
+    auto x        = p.add_literal(migraph::literal{s, x_data});
+    auto scale    = p.add_literal(migraph::literal{vars, scale_data});
+    auto bias     = p.add_literal(migraph::literal{vars, bias_data});
+    auto mean     = p.add_literal(migraph::literal{vars, mean_data});
+    auto variance = p.add_literal(migraph::literal{vars, variance_data});
+
+    p.add_instruction(migraph::batch_norm_inference{}, x, mean, variance, scale, bias);
+    p.compile(migraph::gpu::target{});
+    auto result = p.eval({});
+
+    std::vector<float> result_vector(width * height * channels * batches);
+    std::vector<float> gold(width * height * channels * batches);
+    std::fill(gold.begin(), gold.end(), output_val);
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+
+    EXPECT(test::verify_range(result_vector, gold));
+}
+
 int main()
 {
     verify_program<test_add>();
@@ -224,4 +300,6 @@ int main()
     verify_program<test_gemm>();
     verify_program<test_contiguous>();
     verify_program<test_transpose>();
+    // verify_program<test_batchnorm_inference>();
+    // batch_norm_inference_test();
 }