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/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);