IVGCVSW-1806 More Android NN Driver refactoring
* Changed #if defined to #ifdef
* Simplified the Android ML namespace resolution
* Fixed the relative path in some include directives
Change-Id: I46e46faff98559c8042c1a4b8b82007f462df57d
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)};