Fix bn tests

src/generate.cpp

@@ -2,7 +2,7 @@
 
 namespace migraph {
 
-argument generate_argument(shape s, std::mt19937::result_type seed)
+argument generate_argument(shape s, unsigned long seed)
 {
     argument result;
     s.visit_type([&](auto as) {
@@ -13,7 +13,7 @@ argument generate_argument(shape s, std::mt19937::result_type seed)
     return result;
 }
 
-literal generate_literal(shape s, std::mt19937::result_type seed)
+literal generate_literal(shape s, unsigned long seed)
 {
     literal result;
     s.visit_type([&](auto as) {
@@ -24,4 +24,12 @@ literal generate_literal(shape s, std::mt19937::result_type seed)
     return result;
 }
 
+// TODO: Move to literal.cpp
+literal abs(literal l)
+{
+    return transform(l, [](auto x) {
+        return std::fabs(x);
+    });
+}
+
 } // namespace migraph

src/include/migraph/generate.hpp

@@ -8,7 +8,7 @@
 namespace migraph {
 
 template <class T, MIGRAPH_REQUIRES(std::is_floating_point<T>{})>
-T normalize(unsigned long z)
+constexpr T normalize(unsigned long z)
 {
     if(z == 0)
         return 0;
@@ -16,7 +16,7 @@ T normalize(unsigned long z)
 }
 
 template <class T, MIGRAPH_REQUIRES(std::is_signed<T>{} and not std::is_floating_point<T>{})>
-T normalize(unsigned long z)
+constexpr T normalize(unsigned long z)
 {
     const auto max      = std::numeric_limits<T>::max();
     const auto half_max = max / 2;
@@ -24,7 +24,7 @@ T normalize(unsigned long z)
 }
 
 template <class T, MIGRAPH_REQUIRES(not std::is_signed<T>{} and std::is_integral<T>{})>
-T normalize(unsigned long z)
+constexpr T normalize(unsigned long z)
 {
     const auto max = std::numeric_limits<T>::max();
     return z % max;
@@ -33,9 +33,10 @@ T normalize(unsigned long z)
 template <class T>
 struct xorshf96_generator
 {
+    unsigned long seed = 0;
     unsigned long x = 123456789;
     unsigned long y = 362436069;
-    unsigned long z = 521288629;
+    unsigned long z = 521288629 ^ seed;
 
     constexpr T operator()() noexcept
     {
@@ -53,16 +54,18 @@ struct xorshf96_generator
 };
 
 template <class T>
-std::vector<T> generate_tensor_data(const migraph::shape& s, std::mt19937::result_type)
+std::vector<T> generate_tensor_data(const migraph::shape& s, unsigned long seed = 0)
 {
     std::vector<T> result(s.elements());
-    std::generate(result.begin(), result.end(), xorshf96_generator<T>{});
+    std::generate(result.begin(), result.end(), xorshf96_generator<T>{seed});
     return result;
 }
 
-argument generate_argument(shape s, std::mt19937::result_type seed = 0);
+argument generate_argument(shape s, unsigned long seed = 0);
 
-literal generate_literal(shape s, std::mt19937::result_type seed = 0);
+literal generate_literal(shape s, unsigned long seed = 0);
+
+literal abs(literal l);
 
 } // namespace migraph
 

src/include/migraph/literal.hpp

@@ -94,6 +94,19 @@ struct literal : raw_data<literal>
     }
 };
 
+template<class F>
+literal transform(literal l, F f)
+{
+    literal result;
+    l.visit([&](auto x) {
+        using type = std::remove_cv_t<typename decltype(x)::value_type>;
+        std::vector<type> output(x.size(), 0.0);
+        std::transform(x.begin(), x.end(), output.begin(), f);
+        result = literal{l.get_shape(), output};
+    });
+    return result;
+}
+
 } // namespace migraph
 
 #endif

test/gpu/miopen.cpp

@@ -332,10 +332,10 @@ struct test_batchnorm_inference_2
         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);
+        auto mean     = p.add_literal(migraph::abs(migraph::generate_literal(vars, 0)));
+        auto variance = p.add_literal(migraph::abs(migraph::generate_literal(vars, 1)));
+        auto scale    = p.add_literal(migraph::abs(migraph::generate_literal(vars, 2)));
+        auto bias     = p.add_literal(migraph::abs(migraph::generate_literal(vars, 3)));
         p.add_instruction(migraph::batch_norm_inference{}, x, mean, variance, scale, bias);
         return p;
     }
@@ -355,10 +355,10 @@ struct test_batchnorm_inference
         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);
+        auto mean     = p.add_literal(migraph::abs(migraph::generate_literal(vars, 0)));
+        auto variance = p.add_literal(migraph::abs(migraph::generate_literal(vars, 1)));
+        auto scale    = p.add_literal(migraph::abs(migraph::generate_literal(vars, 2)));
+        auto bias     = p.add_literal(migraph::abs(migraph::generate_literal(vars, 3)));
         p.add_instruction(migraph::batch_norm_inference{}, x, mean, variance, scale, bias);
         return p;
     }