diff --git a/test/GenericLayerTests.cpp b/test/GenericLayerTests.cpp
index c66854f..63198b4 100644
--- a/test/GenericLayerTests.cpp
+++ b/test/GenericLayerTests.cpp
@@ -25,7 +25,7 @@
         supported = _supported;
     };
 
-    neuralnetworks::V1_0::Model model0 = {};
+    V1_0::Model model0 = {};
 
     // Add operands
     int32_t actValue      = 0;
@@ -41,7 +41,7 @@
     model0.operations.resize(1);
 
     // Make a correct fully connected operation
-    model0.operations[0].type    = neuralnetworks::V1_0::OperationType::FULLY_CONNECTED;
+    model0.operations[0].type    = V1_0::OperationType::FULLY_CONNECTED;
     model0.operations[0].inputs  = hidl_vec<uint32_t>{0, 1, 2, 3};
     model0.operations[0].outputs = hidl_vec<uint32_t>{4};
 
@@ -50,7 +50,7 @@
     BOOST_TEST(supported.size() == (size_t)1);
     BOOST_TEST(supported[0] == true);
 
-    neuralnetworks::V1_0::Model model1 = {};
+    V1_0::Model model1 = {};
 
     AddInputOperand (model1, hidl_vec<uint32_t>{1, 3});
     AddTensorOperand(model1, hidl_vec<uint32_t>{1, 3}, weightValue);
@@ -61,14 +61,14 @@
     model1.operations.resize(2);
 
     // Make a correct fully connected operation
-    model1.operations[0].type    = neuralnetworks::V1_0::OperationType::FULLY_CONNECTED;
+    model1.operations[0].type    = V1_0::OperationType::FULLY_CONNECTED;
     model1.operations[0].inputs  = hidl_vec<uint32_t>{0, 1, 2, 3};
     model1.operations[0].outputs = hidl_vec<uint32_t>{4};
 
     // Add an incorrect fully connected operation
     AddIntOperand   (model1, actValue);
     AddOutputOperand(model1, hidl_vec<uint32_t>{1, 1});
-    model1.operations[1].type    = neuralnetworks::V1_0::OperationType::FULLY_CONNECTED;
+    model1.operations[1].type    = V1_0::OperationType::FULLY_CONNECTED;
     model1.operations[1].inputs  = hidl_vec<uint32_t>{4}; // Only 1 input operand, expected 4
     model1.operations[1].outputs = hidl_vec<uint32_t>{5};
 
@@ -89,7 +89,7 @@
 #endif
 
     // Test Broadcast on add/mul operators
-    neuralnetworks::V1_0::Model model2 = {};
+    V1_0::Model model2 = {};
 
     AddInputOperand (model2, hidl_vec<uint32_t>{1, 1, 3, 4});
     AddInputOperand (model2, hidl_vec<uint32_t>{4});
@@ -99,11 +99,11 @@
 
     model2.operations.resize(2);
 
-    model2.operations[0].type    = neuralnetworks::V1_0::OperationType::ADD;
+    model2.operations[0].type    = V1_0::OperationType::ADD;
     model2.operations[0].inputs  = hidl_vec<uint32_t>{0, 1, 2};
     model2.operations[0].outputs = hidl_vec<uint32_t>{3};
 
-    model2.operations[1].type    = neuralnetworks::V1_0::OperationType::MUL;
+    model2.operations[1].type    = V1_0::OperationType::MUL;
     model2.operations[1].inputs  = hidl_vec<uint32_t>{0, 1, 2};
     model2.operations[1].outputs = hidl_vec<uint32_t>{4};
 
@@ -113,7 +113,7 @@
     BOOST_TEST(supported[0] == true);
     BOOST_TEST(supported[1] == true);
 
-    neuralnetworks::V1_0::Model model3 = {};
+    V1_0::Model model3 = {};
 
     AddInputOperand (model3, hidl_vec<uint32_t>{1, 1, 1, 8});
     AddIntOperand   (model3, 2);
@@ -122,7 +122,7 @@
     model3.operations.resize(1);
 
     // Add unsupported operation, should return no error but we don't support it
-    model3.operations[0].type    = neuralnetworks::V1_0::OperationType::DEPTH_TO_SPACE;
+    model3.operations[0].type    = V1_0::OperationType::DEPTH_TO_SPACE;
     model3.operations[0].inputs  = hidl_vec<uint32_t>{0, 1};
     model3.operations[0].outputs = hidl_vec<uint32_t>{2};
 
@@ -131,14 +131,14 @@
     BOOST_TEST(supported.size() == (size_t)1);
     BOOST_TEST(supported[0] == false);
 
-    neuralnetworks::V1_0::Model model4 = {};
+    V1_0::Model model4 = {};
 
     AddIntOperand(model4, 0);
 
     model4.operations.resize(1);
 
     // Add invalid operation
-    model4.operations[0].type    = static_cast<neuralnetworks::V1_0::OperationType>(100);
+    model4.operations[0].type    = static_cast<V1_0::OperationType>(100);
     model4.operations[0].outputs = hidl_vec<uint32_t>{0};
 
     driver->getSupportedOperations(model4, cb);
@@ -162,7 +162,7 @@
         supported = _supported;
     };
 
-    neuralnetworks::V1_0::Model model = {};
+    V1_0::Model model = {};
 
     // Operands
     int32_t actValue      = 0;
@@ -170,11 +170,11 @@
     float   biasValue[]   = {4};
 
     // HASHTABLE_LOOKUP is unsupported at the time of writing this test, but any unsupported layer will do
-    AddInputOperand (model, hidl_vec<uint32_t>{1, 1, 3, 4}, neuralnetworks::V1_0::OperandType::TENSOR_INT32);
-    AddInputOperand (model, hidl_vec<uint32_t>{4},          neuralnetworks::V1_0::OperandType::TENSOR_INT32);
+    AddInputOperand (model, hidl_vec<uint32_t>{1, 1, 3, 4}, V1_0::OperandType::TENSOR_INT32);
+    AddInputOperand (model, hidl_vec<uint32_t>{4},          V1_0::OperandType::TENSOR_INT32);
     AddInputOperand (model, hidl_vec<uint32_t>{1, 1, 3, 4});
     AddOutputOperand(model, hidl_vec<uint32_t>{1, 1, 3, 4});
-    AddOutputOperand(model, hidl_vec<uint32_t>{1, 1, 3, 4}, neuralnetworks::V1_0::OperandType::TENSOR_QUANT8_ASYMM);
+    AddOutputOperand(model, hidl_vec<uint32_t>{1, 1, 3, 4}, V1_0::OperandType::TENSOR_QUANT8_ASYMM);
 
     // Fully connected is supported
     AddInputOperand (model, hidl_vec<uint32_t>{1, 3});
@@ -189,17 +189,17 @@
     model.operations.resize(3);
 
     // Unsupported
-    model.operations[0].type    = neuralnetworks::V1_0::OperationType::HASHTABLE_LOOKUP;
+    model.operations[0].type    = V1_0::OperationType::HASHTABLE_LOOKUP;
     model.operations[0].inputs  = hidl_vec<uint32_t>{0, 1, 2};
     model.operations[0].outputs = hidl_vec<uint32_t>{3, 4};
 
     // Supported
-    model.operations[1].type    = neuralnetworks::V1_0::OperationType::FULLY_CONNECTED;
+    model.operations[1].type    = V1_0::OperationType::FULLY_CONNECTED;
     model.operations[1].inputs  = hidl_vec<uint32_t>{5, 6, 7, 8};
     model.operations[1].outputs = hidl_vec<uint32_t>{9};
 
     // Unsupported
-    model.operations[2].type    = neuralnetworks::V1_0::OperationType::EMBEDDING_LOOKUP;
+    model.operations[2].type    = V1_0::OperationType::EMBEDDING_LOOKUP;
     model.operations[2].inputs  = hidl_vec<uint32_t>{1, 2};
     model.operations[2].outputs = hidl_vec<uint32_t>{10};
 
@@ -227,7 +227,7 @@
         supported = _supported;
     };
 
-    neuralnetworks::V1_0::Model model = {};
+    V1_0::Model model = {};
 
     model.pools = hidl_vec<hidl_memory>{hidl_memory("Unsuported hidl memory type", nullptr, 0)};