refactor(//tests): Fixing batchnorm false test

Signed-off-by: Naren Dasan <[email protected]>
Signed-off-by: Naren Dasan <[email protected]>

Author: narendasan

tests/core/conversion/converters/test_batch_norm.cpp

@@ -40,29 +40,27 @@ TEST(Converters, ATenBatchNormAffineFalseConvertsCorrectly) {
   // BatchNorm(ch, affine=False)
   const auto graph = R"IR(
       graph(%0 : Tensor,
-            %1: NoneType = prim::Constant(),
-            %2: NoneType = prim::Constant(),
             %3: Float(5, strides=[1]),
             %4: Float(5, strides=[1])):
+        %1 : None = prim::Constant()
         %5 : bool = prim::Constant[value=0]()
         %6 : float = prim::Constant[value=1.0000000000000001e-05]()
         %7 : float = prim::Constant[value=0.10000000000000001]()
-        %8 : Tensor = aten::batch_norm(%0, %1, %2, %3, %4, %5, %6, %7, %5)
+        %8 : Tensor = aten::batch_norm(%0, %1, %1, %3, %4, %5, %6, %7, %5)
         return (%8))IR";
 
   auto g = std::make_shared<torch::jit::Graph>();
   torch::jit::parseIR(graph, g.get());
 
   auto in = at::randint(1, 10, {1, 5, 5, 5}, {at::kCUDA});
 
-  torch::jit::IValue gamma, beta; // NoneType
   auto mean = at::randint(1, 10, {5}, {at::kCUDA});
   auto var = at::randint(1, 10, {5}, {at::kCUDA});
 
-  auto params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {gamma, beta, mean, var});
+  auto params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {mean, var});
   auto jit_results = torch_tensorrt::tests::util::RunGraph(g, params, {in});
 
-  params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {gamma, beta, mean, var});
+  params = torch_tensorrt::core::ir::get_static_params(g->inputs(), {mean, var});
   auto trt_results = torch_tensorrt::tests::util::RunGraphEngine(g, params, {in});
 
   ASSERT_TRUE(