--- /dev/null
+/*
+ * Copyright (C) 2017 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_ML_NN_COMMON_UTILS_H
+#define ANDROID_ML_NN_COMMON_UTILS_H
+
+#if 0 // REF-ANN
+#include "HalInterfaces.h"
+#endif
+#include "NeuralNetworks.h"
+
+#if 0 // REF-ANN
+#include <android-base/logging.h>
+#endif
+#include <vector>
+
+namespace android {
+namespace nn {
+
+// The number of data types (OperandCode) defined in NeuralNetworks.h.
+const int kNumberOfDataTypes = 6;
+
+// The number of operation types (OperationCode) defined in NeuralNetworks.h.
+const int kNumberOfOperationTypes = 30;
+
+// The number of execution preferences defined in NeuralNetworks.h.
+const int kNumberOfPreferences = 3;
+
+// The number of data types (OperandCode) defined in NeuralNetworksOEM.h.
+const int kNumberOfDataTypesOEM = 2;
+
+// The number of operation types (OperationCode) defined in NeuralNetworksOEM.h.
+const int kNumberOfOperationTypesOEM = 1;
+
+// The lowest number assigned to any OEM Code in NeuralNetworksOEM.h.
+const int kOEMCodeBase = 10000;
+
+#if 0 // REF-ANN
+/* IMPORTANT: if you change the following list, don't
+ * forget to update the corresponding 'tags' table in
+ * the initVlogMask() function implemented in Utils.cpp.
+ */
+enum VLogFlags {
+ MODEL = 0,
+ COMPILATION,
+ EXECUTION,
+ CPUEXE,
+ MANAGER,
+ DRIVER
+};
+
+#define VLOG_IS_ON(TAG) \
+ ((vLogMask & (1 << (TAG))) != 0)
+
+#define VLOG(TAG) \
+ if (LIKELY(!VLOG_IS_ON(TAG))) \
+ ; \
+ else \
+ LOG(INFO)
+
+extern int vLogMask;
+void initVLogMask();
+
+// Assert macro, as Android does not generally support assert.
+#define nnAssert(v) \
+ do { \
+ if (!(v)) { \
+ LOG(ERROR) << "nnAssert failed at " << __FILE__ << ":" << __LINE__ << " - '" << #v \
+ << "'\n"; \
+ abort(); \
+ } \
+ } while (0)
+
+// Returns the amount of space needed to store a value of the specified
+// dimensions and type.
+uint32_t sizeOfData(OperandType type, const std::vector<uint32_t>& dimensions);
+
+// Returns the amount of space needed to store a value of the dimensions and
+// type of this operand.
+inline uint32_t sizeOfData(const Operand& operand) {
+ return sizeOfData(operand.type, operand.dimensions);
+}
+
+// Returns the name of the operation in ASCII.
+const char* getOperationName(OperationType opCode);
+
+// Memory is unmapped.
+// Memory is reference counted by hidl_memory instances, and is deallocated
+// once there are no more references.
+hidl_memory allocateSharedMemory(int64_t size);
+
+// Returns the number of padding bytes needed to align data of the
+// specified length. It aligns object of length:
+// 2, 3 on a 2 byte boundary,
+// 4+ on a 4 byte boundary.
+// We may want to have different alignments for tensors.
+// TODO: This is arbitrary, more a proof of concept. We need
+// to determine what this should be.
+uint32_t alignBytesNeeded(uint32_t index, size_t length);
+
+// Does a detailed LOG(INFO) of the model
+void logModelToInfo(const Model& model);
+
+inline void setFromIntList(hidl_vec<uint32_t>* vec, uint32_t count, const uint32_t* data) {
+ vec->resize(count);
+ for (uint32_t i = 0; i < count; i++) {
+ (*vec)[i] = data[i];
+ }
+}
+
+inline void setFromIntList(std::vector<uint32_t>* vec, uint32_t count, const uint32_t* data) {
+ vec->resize(count);
+ for (uint32_t i = 0; i < count; i++) {
+ (*vec)[i] = data[i];
+ }
+}
+
+inline std::string toString(uint32_t obj) {
+ return std::to_string(obj);
+}
+
+template <typename Type>
+std::string toString(const std::vector<Type>& range) {
+ std::string os = "[";
+ for (size_t i = 0; i < range.size(); ++i) {
+ os += (i == 0 ? "" : ", ") + toString(range[i]);
+ }
+ return os += "]";
+}
+
+inline bool validCode(uint32_t codeCount, uint32_t codeCountOEM, uint32_t code) {
+ return (code < codeCount) || (code >= kOEMCodeBase && (code - kOEMCodeBase) < codeCountOEM);
+}
+
+int validateOperandType(const ANeuralNetworksOperandType& type, const char* tag, bool allowPartial);
+int validateOperandList(uint32_t count, const uint32_t* list, uint32_t operandCount,
+ const char* tag);
+bool validateModel(const Model& model);
+bool validateRequest(const Request& request, const Model& model);
+
+inline size_t getSizeFromInts(int lower, int higher) {
+ return (uint32_t)(lower) + ((uint64_t)(uint32_t)(higher) << 32);
+}
+
+#ifdef NN_DEBUGGABLE
+uint32_t getProp(const char* str, uint32_t defaultValue = 0);
+#endif // NN_DEBUGGABLE
+
+#endif // REF-ANN
+
+} // namespace nn
+} // namespace android
+
+#endif // ANDROID_ML_NN_COMMON_UTILS_H