Rename BufferRole.frequency -> probability -- HAL.

"Frenquency" often refers to the number of occurrences over a period of
time, while "probability" refers to the number of occurrences of one
event over the number of occurrences of all events. "Probability" is a
better name for this field.

Fixes: 183117895
Test: VtsHalNeuralnetworksTargetTest
Test: NNT_static
Change-Id: Ic86f73b8be2aed567ae4ca17bdb3a57c658fb349
Merged-In: Ic86f73b8be2aed567ae4ca17bdb3a57c658fb349
(cherry picked from commit 46bf892f46aac0f3269970267e6ab7ed0d7d61a3)
diff --git a/neuralnetworks/1.3/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index 9788fe1..8b45f71 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -244,7 +244,7 @@
     return BufferRole{
             .modelIndex = bufferRole.modelIndex,
             .ioIndex = bufferRole.ioIndex,
-            .frequency = bufferRole.frequency,
+            .probability = bufferRole.frequency,
     };
 }
 
@@ -577,7 +577,7 @@
     return BufferRole{
             .modelIndex = bufferRole.modelIndex,
             .ioIndex = bufferRole.ioIndex,
-            .frequency = bufferRole.frequency,
+            .frequency = bufferRole.probability,
     };
 }
 
diff --git a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferRole.aidl b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferRole.aidl
index f18e92a..10a6b75 100644
--- a/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferRole.aidl
+++ b/neuralnetworks/aidl/aidl_api/android.hardware.neuralnetworks/current/android/hardware/neuralnetworks/BufferRole.aidl
@@ -36,5 +36,5 @@
 parcelable BufferRole {
   int modelIndex;
   int ioIndex;
-  float frequency;
+  float probability;
 }
diff --git a/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferRole.aidl b/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferRole.aidl
index 0d7f678..c444851 100644
--- a/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferRole.aidl
+++ b/neuralnetworks/aidl/android/hardware/neuralnetworks/BufferRole.aidl
@@ -35,5 +35,5 @@
      * used in the specified role. This is provided as a hint to optimize the case when multiple
      * roles prefer different buffer locations or data layouts.
      */
-    float frequency;
+    float probability;
 }
diff --git a/neuralnetworks/aidl/utils/src/Conversions.cpp b/neuralnetworks/aidl/utils/src/Conversions.cpp
index c47ba0e..45bc005 100644
--- a/neuralnetworks/aidl/utils/src/Conversions.cpp
+++ b/neuralnetworks/aidl/utils/src/Conversions.cpp
@@ -472,7 +472,7 @@
     return BufferRole{
             .modelIndex = static_cast<uint32_t>(bufferRole.modelIndex),
             .ioIndex = static_cast<uint32_t>(bufferRole.ioIndex),
-            .frequency = bufferRole.frequency,
+            .probability = bufferRole.probability,
     };
 }
 
@@ -718,7 +718,7 @@
     return BufferRole{
             .modelIndex = static_cast<int32_t>(bufferRole.modelIndex),
             .ioIndex = static_cast<int32_t>(bufferRole.ioIndex),
-            .frequency = bufferRole.frequency,
+            .probability = bufferRole.probability,
     };
 }
 
diff --git a/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
index 2dd02dd..1440429 100644
--- a/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/aidl/vts/functional/GeneratedTestHarness.cpp
@@ -102,7 +102,7 @@
         ASSERT_NE(result, nullptr);
 
         // Prepare arguments.
-        BufferRole role = {.modelIndex = 0, .ioIndex = index, .frequency = 1.0f};
+        BufferRole role = {.modelIndex = 0, .ioIndex = index, .probability = 1.0f};
         std::vector<BufferRole> inputRoles, outputRoles;
         if constexpr (ioType == IOType::INPUT) {
             inputRoles = {role};
diff --git a/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp b/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
index 627c26a..596f8ae 100644
--- a/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
+++ b/neuralnetworks/aidl/vts/functional/MemoryDomainTests.cpp
@@ -337,18 +337,18 @@
                               const std::shared_ptr<IPreparedModel>& model2) {
         validateAllocate({
                 .preparedModels = {model1, model2},
-                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
-                               {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f},
+                               {.modelIndex = 1, .ioIndex = 0, .probability = 1.0f}},
         });
         validateAllocate({
                 .preparedModels = {model1, model2},
-                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
-                .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
+                .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .probability = 1.0f}},
         });
         validateAllocate({
                 .preparedModels = {model1, model2},
-                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
-                                {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f},
+                                {.modelIndex = 1, .ioIndex = 0, .probability = 1.0f}},
         });
     }
 };
@@ -370,13 +370,13 @@
     // Test with nullptr prepared model as input role.
     validateAllocate({
             .preparedModels = {nullptr},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
 
     // Test with nullptr prepared model as output role.
     validateAllocate({
             .preparedModels = {nullptr},
-            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
 }
 
@@ -387,13 +387,13 @@
     // Test with invalid prepared model as input role.
     validateAllocate({
             .preparedModels = {invalidPreparedModel},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
 
     // Test with invalid prepared model as output role.
     validateAllocate({
             .preparedModels = {invalidPreparedModel},
-            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
 }
 
@@ -404,13 +404,13 @@
     // This should fail, because the model index is out of bound.
     validateAllocate({
             .preparedModels = {preparedModel},
-            .inputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 1, .ioIndex = 0, .probability = 1.0f}},
     });
 
     // This should fail, because the model index is out of bound.
     validateAllocate({
             .preparedModels = {preparedModel},
-            .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .probability = 1.0f}},
     });
 }
 
@@ -421,30 +421,30 @@
     // This should fail, because the model only has one input.
     validateAllocate({
             .preparedModels = {preparedModel},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 1, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 1, .probability = 1.0f}},
     });
 
     // This should fail, because the model only has one output.
     validateAllocate({
             .preparedModels = {preparedModel},
-            .outputRoles = {{.modelIndex = 0, .ioIndex = 1, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 1, .probability = 1.0f}},
     });
 }
 
-TEST_P(MemoryDomainAllocateTest, InvalidFrequency) {
+TEST_P(MemoryDomainAllocateTest, InvalidProbability) {
     auto preparedModel = createConvPreparedModel(kTestOperand);
     if (preparedModel == nullptr) return;
 
     for (float invalidFreq : {10.0f, 0.0f, -0.5f}) {
-        // Test with invalid frequency for input roles.
+        // Test with invalid probability for input roles.
         validateAllocate({
                 .preparedModels = {preparedModel},
-                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = invalidFreq}},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = invalidFreq}},
         });
-        // Test with invalid frequency for output roles.
+        // Test with invalid probability for output roles.
         validateAllocate({
                 .preparedModels = {preparedModel},
-                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = invalidFreq}},
+                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = invalidFreq}},
         });
     }
 }
@@ -456,25 +456,25 @@
     // Same role with same model index.
     validateAllocate({
             .preparedModels = {preparedModel},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
-                           {.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f},
+                           {.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
     validateAllocate({
             .preparedModels = {preparedModel},
-            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
-                            {.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f},
+                            {.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
 
     // Different model indexes, but logically referring to the same role.
     validateAllocate({
             .preparedModels = {preparedModel, preparedModel},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
-                           {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f},
+                           {.modelIndex = 1, .ioIndex = 0, .probability = 1.0f}},
     });
     validateAllocate({
             .preparedModels = {preparedModel, preparedModel},
-            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
-                            {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f},
+                            {.modelIndex = 1, .ioIndex = 0, .probability = 1.0f}},
     });
 }
 
@@ -553,12 +553,12 @@
     validateAllocate({
             .dimensions = badDimensions,
             .preparedModels = {preparedModel},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
     validateAllocate({
             .dimensions = badDimensions,
             .preparedModels = {preparedModel},
-            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
 }
 
@@ -572,12 +572,12 @@
     validateAllocate({
             .dimensions = badDimensions,
             .preparedModels = {preparedModel},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
     validateAllocate({
             .dimensions = badDimensions,
             .preparedModels = {preparedModel},
-            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .probability = 1.0f}},
     });
 }
 
@@ -590,7 +590,7 @@
     validateAllocate({
             .dimensions = {1},
             .preparedModels = {preparedModel},
-            .inputRoles = {{.modelIndex = 0, .ioIndex = 2, .frequency = 1.0f}},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 2, .probability = 1.0f}},
     });
 }
 
@@ -624,7 +624,7 @@
 
         std::vector<BufferRole> inputRoles(inputIndexes.size()), outputRoles(outputIndexes.size());
         auto trans = [](int32_t ind) -> BufferRole {
-            return {.modelIndex = 0, .ioIndex = ind, .frequency = 1.0f};
+            return {.modelIndex = 0, .ioIndex = ind, .probability = 1.0f};
         };
         std::transform(inputIndexes.begin(), inputIndexes.end(), inputRoles.begin(), trans);
         std::transform(outputIndexes.begin(), outputIndexes.end(), outputRoles.begin(), trans);