diff --git a/test/Concurrent.cpp b/test/Concurrent.cpp
index 92f6f8f..55a1a39 100644
--- a/test/Concurrent.cpp
+++ b/test/Concurrent.cpp
@@ -24,7 +24,7 @@
     ALOGI("ConcurrentExecute: entry");
 
     auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
-    neuralnetworks::V1_0::Model model = {};
+    V1_0::Model model = {};
 
     // add operands
     int32_t actValue      = 0;
@@ -39,7 +39,7 @@
 
     // make the fully connected operation
     model.operations.resize(1);
-    model.operations[0].type = neuralnetworks::V1_0::OperationType::FULLY_CONNECTED;
+    model.operations[0].type = V1_0::OperationType::FULLY_CONNECTED;
     model.operations[0].inputs  = hidl_vec<uint32_t>{0, 1, 2, 3};
     model.operations[0].outputs = hidl_vec<uint32_t>{4};
 
diff --git a/test/DriverTestHelpers.cpp b/test/DriverTestHelpers.cpp
index ded2459..3bc0a20 100644
--- a/test/DriverTestHelpers.cpp
+++ b/test/DriverTestHelpers.cpp
@@ -109,7 +109,7 @@
     memcpy(dst, data, size * sizeof(float));
 }
 
-android::sp<IPreparedModel> PrepareModelWithStatus(const neuralnetworks::V1_0::Model& model,
+android::sp<IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
                                                    armnn_driver::ArmnnDriver& driver,
                                                    ErrorStatus& prepareStatus,
                                                    ErrorStatus expectedStatus)
@@ -126,15 +126,15 @@
     return cb->GetPreparedModel();
 }
 
-#if defined(ARMNN_ANDROID_NN_V1_1) // Using ::android::hardware::neuralnetworks::V1_1.
+#ifdef ARMNN_ANDROID_NN_V1_1
 
-android::sp<IPreparedModel> PrepareModelWithStatus(const neuralnetworks::V1_1::Model& model,
+android::sp<IPreparedModel> PrepareModelWithStatus(const V1_1::Model& model,
                                                    armnn_driver::ArmnnDriver& driver,
                                                    ErrorStatus& prepareStatus,
                                                    ErrorStatus expectedStatus)
 {
     android::sp<PreparedModelCallback> cb(new PreparedModelCallback());
-    driver.prepareModel_1_1(model, neuralnetworks::V1_1::ExecutionPreference::LOW_POWER, cb);
+    driver.prepareModel_1_1(model, V1_1::ExecutionPreference::LOW_POWER, cb);
 
     prepareStatus = cb->GetErrorStatus();
     BOOST_TEST(prepareStatus == expectedStatus);
@@ -172,12 +172,12 @@
 OperandType TypeToOperandType<float>()
 {
     return OperandType::TENSOR_FLOAT32;
-};
+}
 
 template<>
 OperandType TypeToOperandType<int32_t>()
 {
     return OperandType::TENSOR_INT32;
-};
+}
 
 } // namespace driverTestHelpers
diff --git a/test/DriverTestHelpers.hpp b/test/DriverTestHelpers.hpp
index ce09ee6..cce220e 100644
--- a/test/DriverTestHelpers.hpp
+++ b/test/DriverTestHelpers.hpp
@@ -31,7 +31,7 @@
 namespace driverTestHelpers
 {
 
-std::ostream& operator<<(std::ostream& os, android::hardware::neuralnetworks::V1_0::ErrorStatus stat);
+std::ostream& operator<<(std::ostream& os, V1_0::ErrorStatus stat);
 
 struct ExecutionCallback : public IExecutionCallback
 {
@@ -172,14 +172,14 @@
     model.outputIndexes[model.outputIndexes.size() - 1] = model.operands.size() - 1;
 }
 
-android::sp<IPreparedModel> PrepareModelWithStatus(const ::android::hardware::neuralnetworks::V1_0::Model& model,
+android::sp<IPreparedModel> PrepareModelWithStatus(const V1_0::Model& model,
                                                    armnn_driver::ArmnnDriver& driver,
                                                    ErrorStatus& prepareStatus,
                                                    ErrorStatus expectedStatus = ErrorStatus::NONE);
 
-#if defined(ARMNN_ANDROID_NN_V1_1) // Using ::android::hardware::neuralnetworks::V1_1.
+#ifdef ARMNN_ANDROID_NN_V1_1
 
-android::sp<IPreparedModel> PrepareModelWithStatus(const ::android::hardware::neuralnetworks::V1_1::Model& model,
+android::sp<IPreparedModel> PrepareModelWithStatus(const V1_1::Model& model,
                                                    armnn_driver::ArmnnDriver& driver,
                                                    ErrorStatus& prepareStatus,
                                                    ErrorStatus expectedStatus = ErrorStatus::NONE);
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)};
 
diff --git a/test/Lstm.cpp b/test/Lstm.cpp
index fe6e5d0..f5d26b2 100644
--- a/test/Lstm.cpp
+++ b/test/Lstm.cpp
@@ -114,7 +114,7 @@
                   std::vector<float> outputValue)
 {
     auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::GpuAcc));
-    neuralnetworks::V1_0::Model model = {};
+    V1_0::Model model = {};
 
     // Inputs:
     // 00: The input: A 2-D tensor of ANEURALNETWORKS_TENSOR_FLOAT32, of shape [batch_size, input_size], where
@@ -198,7 +198,7 @@
 
     // make the lstm operation
     model.operations.resize(1);
-    model.operations[0].type = neuralnetworks::V1_0::OperationType::LSTM;
+    model.operations[0].type = V1_0::OperationType::LSTM;
     model.operations[0].inputs =
         hidl_vec<uint32_t> {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22};
     model.operations[0].outputs = hidl_vec<uint32_t> {23, 24, 25, 26};
diff --git a/test/Merger.cpp b/test/Merger.cpp
index a296d8d..118e0d6 100644
--- a/test/Merger.cpp
+++ b/test/Merger.cpp
@@ -30,7 +30,7 @@
                 ErrorStatus expectedExecStatus=ErrorStatus::NONE)
 {
     std::unique_ptr<ArmnnDriver> driver = std::make_unique<ArmnnDriver>(DriverOptions(computeDevice));
-    neuralnetworks::V1_0::Model model{};
+    V1_0::Model model{};
 
     hidl_vec<uint32_t> modelInputIds;
     modelInputIds.resize(inputs.size()+1);
@@ -45,7 +45,7 @@
 
     // make the concat operation
     model.operations.resize(1);
-    model.operations[0].type = neuralnetworks::V1_0::OperationType::CONCATENATION;
+    model.operations[0].type = V1_0::OperationType::CONCATENATION;
     model.operations[0].inputs  = modelInputIds;
     model.operations[0].outputs = hidl_vec<uint32_t>{static_cast<uint32_t>(inputs.size()+1)};
 
diff --git a/test/Tests.cpp b/test/Tests.cpp
index 865c6d0..5c388cb 100644
--- a/test/Tests.cpp
+++ b/test/Tests.cpp
@@ -31,9 +31,9 @@
     auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
 
     ErrorStatus error;
-    neuralnetworks::V1_0::Capabilities cap;
+    V1_0::Capabilities cap;
 
-    auto cb = [&](ErrorStatus status, const neuralnetworks::V1_0::Capabilities& capabilities)
+    auto cb = [&](ErrorStatus status, const V1_0::Capabilities& capabilities)
     {
         error = status;
         cap = capabilities;
diff --git a/test/UtilsTests.cpp b/test/UtilsTests.cpp
index 2bb81d8..6ac1ebb 100644
--- a/test/UtilsTests.cpp
+++ b/test/UtilsTests.cpp
@@ -96,7 +96,7 @@
     }
 
     std::string m_RequestInputsAndOutputsDumpDir;
-    neuralnetworks::V1_0::Model m_Model;
+    V1_0::Model m_Model;
 
 private:
     std::string m_FileName;