Update documentation. Remove IntList.
As NDK council request, updated some documentation and removed
IntList. Other issues will be addressed in other CLs.
Bug: 63905942
Test: Compiled and ran the unit tests.
Change-Id: Iff6898737696daa6bbf41643b07d0a4508af4c0d
diff --git a/runtime/NeuralNetworks.cpp b/runtime/NeuralNetworks.cpp
index d27d939..b0f1e3f 100644
--- a/runtime/NeuralNetworks.cpp
+++ b/runtime/NeuralNetworks.cpp
@@ -20,13 +20,14 @@
#define LOG_TAG "NeuralNetworks"
+#include "NeuralNetworks.h"
+
#include "CompilationBuilder.h"
#include "Event.h"
#include "ExecutionBuilder.h"
-#include "NeuralNetworks.h"
-#include "NeuralNetworksOEM.h"
#include "Manager.h"
#include "Memory.h"
+#include "NeuralNetworksOEM.h"
#include "ModelBuilder.h"
#include <memory>
@@ -133,7 +134,8 @@
static_assert(static_cast<int32_t>(OperationType::ADD) == ANEURALNETWORKS_ADD,
"OperationType::ADD != ANEURALNETWORKS_ADD");
-static_assert(static_cast<int32_t>(OperationType::AVERAGE_POOL_2D) == ANEURALNETWORKS_AVERAGE_POOL_2D,
+static_assert(static_cast<int32_t>(OperationType::AVERAGE_POOL_2D) ==
+ ANEURALNETWORKS_AVERAGE_POOL_2D,
"OperationType::AVERAGE_POOL_2D != ANEURALNETWORKS_AVERAGE_POOL_2D");
static_assert(static_cast<int32_t>(OperationType::CONV_2D) == ANEURALNETWORKS_CONV_2D,
"OperationType::CONV_2D != ANEURALNETWORKS_CONV_2D");
@@ -215,10 +217,10 @@
static int ValidateOperandType(const ANeuralNetworksOperandType& type, const char* tag,
bool allowPartial) {
if (!allowPartial) {
- for (uint32_t i = 0; i < type.dimensions.count; i++) {
- if (type.dimensions.data[i] == 0) {
+ for (uint32_t i = 0; i < type.dimensionCount; i++) {
+ if (type.dimensions[i] == 0) {
LOG(ERROR) << tag << " OperandType invalid dimensions[" << i
- << "] = " << type.dimensions.data[i];
+ << "] = " << type.dimensions[i];
return ANEURALNETWORKS_BAD_DATA;
}
}
@@ -241,12 +243,12 @@
return ANEURALNETWORKS_NO_ERROR;
}
-static int ValidateOperandList(const ANeuralNetworksIntList& list, uint32_t count,
+static int ValidateOperandList(uint32_t count, const uint32_t* list, uint32_t operandCount,
const char* tag) {
- for (uint32_t i = 0; i < list.count; i++) {
- if (list.data[i] >= count) {
- LOG(ERROR) << tag << " invalid operand index at " << i << " = " << list.data[i]
- << ", count " << count;
+ for (uint32_t i = 0; i < count; i++) {
+ if (list[i] >= operandCount) {
+ LOG(ERROR) << tag << " invalid operand index at " << i << " = " << list[i]
+ << ", operandCount " << operandCount;
return ANEURALNETWORKS_BAD_DATA;
}
}
@@ -353,9 +355,9 @@
}
int ANeuralNetworksModel_addOperation(ANeuralNetworksModel* model,
- ANeuralNetworksOperationType type,
- ANeuralNetworksIntList* inputs,
- ANeuralNetworksIntList* outputs) {
+ ANeuralNetworksOperationType type, uint32_t inputCount,
+ const uint32_t* inputs, uint32_t outputCount,
+ const uint32_t* outputs) {
if (!model || !inputs || !outputs) {
LOG(ERROR) << "ANeuralNetworksModel_addOperation passed a nullptr";
return ANEURALNETWORKS_UNEXPECTED_NULL;
@@ -365,40 +367,40 @@
LOG(ERROR) << "ANeuralNetworksModel_addOperation invalid operations type " << type;
return ANEURALNETWORKS_BAD_DATA;
}
- int n = ValidateOperandList(*inputs, m->operandCount(),
+ int n = ValidateOperandList(inputCount, inputs, m->operandCount(),
"ANeuralNetworksModel_addOperation inputs");
if (n != ANEURALNETWORKS_NO_ERROR) {
return n;
}
- n = ValidateOperandList(*outputs, m->operandCount(),
+ n = ValidateOperandList(outputCount, outputs, m->operandCount(),
"ANeuralNetworksModel_addOperation outputs");
if (n != ANEURALNETWORKS_NO_ERROR) {
return n;
}
- return m->addOperation(type, inputs, outputs);
+ return m->addOperation(type, inputCount, inputs, outputCount, outputs);
}
-int ANeuralNetworksModel_setInputsAndOutputs(ANeuralNetworksModel* model,
- ANeuralNetworksIntList* inputs,
- ANeuralNetworksIntList* outputs) {
+int ANeuralNetworksModel_setInputsAndOutputs(ANeuralNetworksModel* model, uint32_t inputCount,
+ const uint32_t* inputs, uint32_t outputCount,
+ const uint32_t* outputs) {
if (!model || !inputs || !outputs) {
LOG(ERROR) << ("ANeuralNetworksModel_setInputsAndOutputs passed a nullptr");
return ANEURALNETWORKS_UNEXPECTED_NULL;
}
ModelBuilder* m = reinterpret_cast<ModelBuilder*>(model);
- int n = ValidateOperandList(*inputs, m->operandCount(),
+ int n = ValidateOperandList(inputCount, inputs, m->operandCount(),
"ANeuralNetworksModel_setInputsAndOutputs inputs");
if (n != ANEURALNETWORKS_NO_ERROR) {
return n;
}
- n = ValidateOperandList(*outputs, m->operandCount(),
+ n = ValidateOperandList(outputCount, outputs, m->operandCount(),
"ANeuralNetworksModel_setInputsAndOutputs outputs");
if (n != ANEURALNETWORKS_NO_ERROR) {
return n;
}
- return m->setInputsAndOutputs(inputs, outputs);
+ return m->setInputsAndOutputs(inputCount, inputs, outputCount, outputs);
}
int ANeuralNetworksCompilation_create(ANeuralNetworksModel* model,
