Add new OperandType BOOL.

- Add new enum OperandType::BOOL.
- Add v1.2 Operand, OperandType.
- Add VTS validation tests for BOOL.

Bug: 117423393

Test: NeuralNetworksTest_static
Test: VtsHalNeuralnetworksV1_2TargetTest

Change-Id: I420e2afeb09b881a499eee6b138c1f26e9874f5a
Merged-In: I420e2afeb09b881a499eee6b138c1f26e9874f5a
(cherry picked from commit abad9eac448cc61582a9a658a231010358051b97)

4 files changed, 121 insertions, 8 deletions

diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
index 0050e52d..a64268f4 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.h
@@ -34,9 +34,11 @@ namespace hardware {
 namespace neuralnetworks {
 namespace V1_1 {
 
-using V1_0::Request;
 using V1_0::DeviceStatus;
 using V1_0::ErrorStatus;
+using V1_0::Operand;
+using V1_0::OperandType;
+using V1_0::Request;
 
 namespace vts {
 namespace functional {
diff --git a/neuralnetworks/1.2/Android.bp b/neuralnetworks/1.2/Android.bp
index d5ef49d4..5a661e06 100644
--- a/neuralnetworks/1.2/Android.bp
+++ b/neuralnetworks/1.2/Android.bp
@@ -17,6 +17,8 @@ hidl_interface {
     ],
     types: [
         "Model",
+        "Operand",
+        "OperandType",
         "Operation",
         "OperationType",
     ],
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index bed1d5ca..95e97c4b 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -16,10 +16,22 @@
 
 package android.hardware.neuralnetworks@1.2;
 
-import @1.0::Operand;
+import @1.0::DataLocation;
+import @1.0::OperandLifeTime;
+import @1.0::OperandType;
 import @1.0::PerformanceInfo;
 import @1.1::OperationType;
 
+enum OperandType : @1.0::OperandType {
+    /**
+     * An 8 bit boolean scalar value.
+     *
+     * Values of this operand type are either true or false. A zero value
+     * represents false; any other value represents true.
+     */
+    BOOL = 6,
+};
+
 /**
  * Operation types.
  *
@@ -102,6 +114,101 @@ struct Operation {
 };
 
 /**
+ * Describes one operand of the model's graph.
+ */
+struct Operand {
+    /**
+     * Data type of the operand.
+     */
+    OperandType type;
+
+    /**
+     * Dimensions of the operand.
+     *
+     * For a scalar operand, dimensions.size() must be 0.
+     *
+     * For a tensor operand, dimensions.size() must be at least 1;
+     * however, any of the dimensions may be unspecified.
+     *
+     * A tensor operand with all dimensions specified has "fully
+     * specified" dimensions. Whenever possible (i.e., whenever the
+     * dimensions are known at model construction time), a tensor
+     * operand should have (but is not required to have) fully
+     * specified dimensions, in order to enable the best possible
+     * performance.
+     *
+     * If a tensor operand's dimensions are not fully specified, the
+     * dimensions of the operand are deduced from the operand
+     * dimensions and values of the operation for which that operand
+     * is an output.
+     *
+     * In the following situations, a tensor operand's dimensions must
+     * be fully specified:
+     *
+     *     . The operand has lifetime CONSTANT_COPY or
+     *       CONSTANT_REFERENCE.
+     *
+     *     . The operand has lifetime MODEL_INPUT or MODEL_OUTPUT. Fully
+     *       specified dimensions must either be present in the
+     *       Operand or they must be provided in the corresponding
+     *       RequestArgument.
+     *       EXCEPTION: If the input or output is optional and omitted
+     *       (by setting the hasNoValue field of the corresponding
+     *       RequestArgument to true) then it need not have fully
+     *       specified dimensions.
+     *
+     * A tensor operand with some number of unspecified dimensions is
+     * represented by setting each unspecified dimension to 0.
+     */
+    vec<uint32_t> dimensions;
+
+    /**
+     * The number of times this operand appears as an operation input.
+     *
+     * (For example, if this operand appears once in one operation's
+     * input list, and three times in another operation's input list,
+     * then numberOfConsumers = 4.)
+     */
+    uint32_t numberOfConsumers;
+
+    /**
+     * Quantized scale of the operand.
+     *
+     * Only applicable if the operand is of type TENSOR_QUANT8_ASYMM or
+     * TENSOR_INT32.
+     */
+    float scale;
+
+    /**
+     * Quantized zero-point offset of the operand.
+     *
+     * Only applicable if the operand is of type TENSOR_QUANT8_ASYMM.
+     */
+    int32_t zeroPoint;
+
+    /**
+     * How the operand is used.
+     */
+    OperandLifeTime lifetime;
+
+    /**
+     * Where to find the data for this operand.
+     * If the lifetime is TEMPORARY_VARIABLE, MODEL_INPUT, MODEL_OUTPUT, or
+     * NO_VALUE:
+     * - All the fields must be 0.
+     * If the lifetime is CONSTANT_COPY:
+     * - location.poolIndex is 0.
+     * - location.offset is the offset in bytes into Model.operandValues.
+     * - location.length is set.
+     * If the lifetime is CONSTANT_REFERENCE:
+     * - location.poolIndex is set.
+     * - location.offset is the offset in bytes into the specified pool.
+     * - location.length is set.
+     */
+    DataLocation location;
+};
+
+/**
  * A Neural Network Model.
  *
  * This includes not only the execution graph, but also constant data such as
diff --git a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
index 7ec6ff18..5a8b8c59 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
@@ -26,9 +26,7 @@ namespace neuralnetworks {
 namespace V1_2 {
 
 using V1_0::IPreparedModel;
-using V1_0::Operand;
 using V1_0::OperandLifeTime;
-using V1_0::OperandType;
 using V1_1::ExecutionPreference;
 
 namespace vts {
@@ -131,10 +129,10 @@ static uint32_t addOperand(Model* model, OperandLifeTime lifetime) {
 ///////////////////////// VALIDATE MODEL OPERAND TYPE /////////////////////////
 
 static const int32_t invalidOperandTypes[] = {
-    static_cast<int32_t>(OperandType::FLOAT32) - 1,              // lower bound fundamental
-    static_cast<int32_t>(OperandType::TENSOR_QUANT8_ASYMM) + 1,  // upper bound fundamental
-    static_cast<int32_t>(OperandType::OEM) - 1,                  // lower bound OEM
-    static_cast<int32_t>(OperandType::TENSOR_OEM_BYTE) + 1,      // upper bound OEM
+    static_cast<int32_t>(OperandType::FLOAT32) - 1,          // lower bound fundamental
+    static_cast<int32_t>(OperandType::BOOL) + 1,             // upper bound fundamental
+    static_cast<int32_t>(OperandType::OEM) - 1,              // lower bound OEM
+    static_cast<int32_t>(OperandType::TENSOR_OEM_BYTE) + 1,  // upper bound OEM
 };
 
 static void mutateOperandTypeTest(const sp<IDevice>& device, const Model& model) {
@@ -157,6 +155,7 @@ static uint32_t getInvalidRank(OperandType type) {
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
+        case OperandType::BOOL:
             return 1;
         case OperandType::TENSOR_FLOAT32:
         case OperandType::TENSOR_INT32:
@@ -185,6 +184,7 @@ static float getInvalidScale(OperandType type) {
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
+        case OperandType::BOOL:
         case OperandType::TENSOR_FLOAT32:
             return 1.0f;
         case OperandType::TENSOR_INT32:
@@ -214,6 +214,7 @@ static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
+        case OperandType::BOOL:
         case OperandType::TENSOR_FLOAT32:
         case OperandType::TENSOR_INT32:
             return {1};
@@ -253,6 +254,7 @@ static void mutateOperand(Operand* operand, OperandType type) {
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
+        case OperandType::BOOL:
             newOperand.dimensions = hidl_vec<uint32_t>();
             newOperand.scale = 0.0f;
             newOperand.zeroPoint = 0;