/*
* 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.
*/
#include "NeuralNetworks.h"
#include "NeuralNetworksOEM.h"
#include <android/sharedmem.h>
#include <gtest/gtest.h>
#include <string>
#include <sys/mman.h>
// This file tests all the validations done by the Neural Networks API.
namespace {
class ValidationTest : public ::testing::Test {
protected:
virtual void SetUp() {}
};
class ValidationTestModel : public ValidationTest {
protected:
virtual void SetUp() {
ValidationTest::SetUp();
ASSERT_EQ(ANeuralNetworksModel_create(&mModel), ANEURALNETWORKS_NO_ERROR);
}
virtual void TearDown() {
ANeuralNetworksModel_free(mModel);
ValidationTest::TearDown();
}
ANeuralNetworksModel* mModel = nullptr;
};
class ValidationTestIdentify : public ValidationTestModel {
virtual void SetUp() {
ValidationTestModel::SetUp();
uint32_t dimensions[]{1};
ANeuralNetworksOperandType tensorType{.type = ANEURALNETWORKS_TENSOR_FLOAT32,
.dimensionCount = 1,
.dimensions = dimensions};
ANeuralNetworksOperandType scalarType{.type = ANEURALNETWORKS_INT32,
.dimensionCount = 0,
.dimensions = nullptr};
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &tensorType), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &tensorType), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &scalarType), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &tensorType), ANEURALNETWORKS_NO_ERROR);
uint32_t inList[3]{0, 1, 2};
uint32_t outList[1]{3};
ASSERT_EQ(ANeuralNetworksModel_addOperation(mModel, ANEURALNETWORKS_ADD, 3, inList, 1,
outList),
ANEURALNETWORKS_NO_ERROR);
}
virtual void TearDown() {
ValidationTestModel::TearDown();
}
};
class ValidationTestCompilation : public ValidationTestModel {
protected:
virtual void SetUp() {
ValidationTestModel::SetUp();
uint32_t dimensions[]{1};
ANeuralNetworksOperandType tensorType{.type = ANEURALNETWORKS_TENSOR_FLOAT32,
.dimensionCount = 1,
.dimensions = dimensions};
ANeuralNetworksOperandType scalarType{.type = ANEURALNETWORKS_INT32,
.dimensionCount = 0,
.dimensions = nullptr};
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &tensorType), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &tensorType), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &scalarType), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_addOperand(mModel, &tensorType), ANEURALNETWORKS_NO_ERROR);
uint32_t inList[3]{0, 1, 2};
uint32_t outList[1]{3};
ASSERT_EQ(ANeuralNetworksModel_addOperation(mModel, ANEURALNETWORKS_ADD, 3, inList, 1,
outList),
ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 3, inList, 1, outList),
ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_finish(mModel), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksCompilation_create(mModel, &mCompilation),
ANEURALNETWORKS_NO_ERROR);
}
virtual void TearDown() {
ANeuralNetworksCompilation_free(mCompilation);
ValidationTestModel::TearDown();
}
ANeuralNetworksCompilation* mCompilation = nullptr;
};
class ValidationTestExecution : public ValidationTestCompilation {
protected:
virtual void SetUp() {
ValidationTestCompilation::SetUp();
ASSERT_EQ(ANeuralNetworksCompilation_finish(mCompilation), ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksExecution_create(mCompilation, &mExecution),
ANEURALNETWORKS_NO_ERROR);
}
virtual void TearDown() {
ANeuralNetworksExecution_free(mExecution);
ValidationTestCompilation::TearDown();
}
ANeuralNetworksExecution* mExecution = nullptr;
};
TEST_F(ValidationTest, CreateModel) {
EXPECT_EQ(ANeuralNetworksModel_create(nullptr), ANEURALNETWORKS_UNEXPECTED_NULL);
}
TEST_F(ValidationTestModel, AddOperand) {
ANeuralNetworksOperandType floatType{
.type = ANEURALNETWORKS_FLOAT32, .dimensionCount = 0, .dimensions = nullptr};
EXPECT_EQ(ANeuralNetworksModel_addOperand(nullptr, &floatType),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, nullptr), ANEURALNETWORKS_UNEXPECTED_NULL);
ANeuralNetworksOperandType quant8TypeInvalidScale{
.type = ANEURALNETWORKS_TENSOR_QUANT8_ASYMM,
.dimensionCount = 0,
.dimensions = nullptr,
// Scale has to be non-negative
.scale = -1.0f,
.zeroPoint = 0,
};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &quant8TypeInvalidScale),
ANEURALNETWORKS_BAD_DATA);
ANeuralNetworksOperandType quant8TypeInvalidZeroPoint{
.type = ANEURALNETWORKS_TENSOR_QUANT8_ASYMM,
.dimensionCount = 0,
.dimensions = nullptr,
.scale = 1.0f,
// zeroPoint has to be in [0, 255]
.zeroPoint = -1,
};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &quant8TypeInvalidZeroPoint),
ANEURALNETWORKS_BAD_DATA);
uint32_t dim = 2;
ANeuralNetworksOperandType invalidScalarType{
.type = ANEURALNETWORKS_INT32,
// scalar types can only 0 dimensions.
.dimensionCount = 1,
.dimensions = &dim,
};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &invalidScalarType),
ANEURALNETWORKS_BAD_DATA);
ANeuralNetworksModel_finish(mModel);
// This should fail, as the model is already finished.
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &floatType),
ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, SetOptionalOperand) {
ANeuralNetworksOperandType floatType{
.type = ANEURALNETWORKS_FLOAT32, .dimensionCount = 0, .dimensions = nullptr};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &floatType), ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 0, nullptr, 0),
ANEURALNETWORKS_NO_ERROR);
}
TEST_F(ValidationTestModel, SetOperandValue) {
ANeuralNetworksOperandType floatType{
.type = ANEURALNETWORKS_FLOAT32, .dimensionCount = 0, .dimensions = nullptr};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &floatType), ANEURALNETWORKS_NO_ERROR);
char buffer[20];
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(nullptr, 0, buffer, sizeof(buffer)),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 0, nullptr, sizeof(buffer)),
ANEURALNETWORKS_UNEXPECTED_NULL);
// This should fail, since buffer is not the size of a float32.
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 0, buffer, sizeof(buffer)),
ANEURALNETWORKS_BAD_DATA);
// This should succeed.
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 0, buffer, sizeof(float)),
ANEURALNETWORKS_NO_ERROR);
// This should fail, as this operand does not exist.
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 1, buffer, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
ANeuralNetworksModel_finish(mModel);
// This should fail, as the model is already finished.
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 0, buffer, sizeof(float)),
ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, SetOperandValueFromMemory) {
uint32_t dimensions[]{1};
ANeuralNetworksOperandType floatType{
.type = ANEURALNETWORKS_TENSOR_FLOAT32,
.dimensionCount = 1,
.dimensions = dimensions};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &floatType), ANEURALNETWORKS_NO_ERROR);
const size_t memorySize = 20;
int memoryFd = ASharedMemory_create("nnMemory", memorySize);
ASSERT_GT(memoryFd, 0);
ANeuralNetworksMemory* memory;
EXPECT_EQ(ANeuralNetworksMemory_createFromFd(memorySize, PROT_READ | PROT_WRITE,
memoryFd, 0, &memory),
ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(nullptr, 0,
memory, 0, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(mModel, 0,
nullptr, 0, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
// This should fail, since the operand does not exist.
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(mModel, -1,
memory, 0, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since memory is not the size of a float32.
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(mModel, 0,
memory, 0, memorySize),
ANEURALNETWORKS_BAD_DATA);
// This should fail, as this operand does not exist.
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(mModel, 1,
memory, 0, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since offset is larger than memorySize.
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(mModel, 0,
memory, memorySize + 1,
sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since requested size is larger than the memory.
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(mModel, 0,
memory, memorySize - 3,
sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
ANeuralNetworksModel_finish(mModel);
// This should fail, as the model is already finished.
EXPECT_EQ(ANeuralNetworksModel_setOperandValueFromMemory(mModel, 0,
memory, 0,
sizeof(float)),
ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, AddOEMOperand) {
ANeuralNetworksOperandType OEMScalarType{
.type = ANEURALNETWORKS_OEM_SCALAR, .dimensionCount = 0, .dimensions = nullptr};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &OEMScalarType), ANEURALNETWORKS_NO_ERROR);
char buffer[20];
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 0, buffer, sizeof(buffer)),
ANEURALNETWORKS_NO_ERROR);
const size_t kByteSizeOfOEMTensor = 4;
uint32_t dimensions[]{kByteSizeOfOEMTensor};
ANeuralNetworksOperandType OEMTensorType{
.type = ANEURALNETWORKS_TENSOR_OEM_BYTE,
.dimensionCount = 1,
.dimensions = dimensions};
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &OEMTensorType), ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksModel_setOperandValue(mModel, 1, buffer, kByteSizeOfOEMTensor),
ANEURALNETWORKS_NO_ERROR);
ANeuralNetworksModel_finish(mModel);
// This should fail, as the model is already finished.
EXPECT_EQ(ANeuralNetworksModel_addOperand(mModel, &OEMTensorType), ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, AddOperation) {
uint32_t input = 0;
uint32_t output = 0;
EXPECT_EQ(ANeuralNetworksModel_addOperation(nullptr, ANEURALNETWORKS_AVERAGE_POOL_2D, 1, &input,
1, &output),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_addOperation(mModel, ANEURALNETWORKS_AVERAGE_POOL_2D, 0, nullptr,
1, &output),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_addOperation(mModel, ANEURALNETWORKS_AVERAGE_POOL_2D, 1, &input,
0, nullptr),
ANEURALNETWORKS_UNEXPECTED_NULL);
ANeuralNetworksOperationType invalidOp = -1;
EXPECT_EQ(ANeuralNetworksModel_addOperation(mModel, invalidOp, 1, &input,
1, &output),
ANEURALNETWORKS_BAD_DATA);
ANeuralNetworksModel_finish(mModel);
// This should fail, as the model is already finished.
EXPECT_EQ(ANeuralNetworksModel_addOperation(mModel, ANEURALNETWORKS_AVERAGE_POOL_2D, 1, &input,
1, &output),
ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, IdentifyInputsAndOutputs) {
uint32_t input = 0;
uint32_t output = 0;
EXPECT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(nullptr, 1, &input, 1, &output),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 0, nullptr, 1, &output),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 1, &input, 0, nullptr),
ANEURALNETWORKS_UNEXPECTED_NULL);
ANeuralNetworksModel_finish(mModel);
// This should fail, as the model is already finished.
EXPECT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 1, &input, 1, &output),
ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, RelaxComputationFloat32toFloat16) {
EXPECT_EQ(ANeuralNetworksModel_relaxComputationFloat32toFloat16(nullptr, true),
ANEURALNETWORKS_UNEXPECTED_NULL);
ANeuralNetworksModel_finish(mModel);
// This should fail, as the model is already finished.
EXPECT_EQ(ANeuralNetworksModel_relaxComputationFloat32toFloat16(mModel, true),
ANEURALNETWORKS_BAD_STATE);
EXPECT_EQ(ANeuralNetworksModel_relaxComputationFloat32toFloat16(mModel, false),
ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, Finish) {
EXPECT_EQ(ANeuralNetworksModel_finish(nullptr), ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksModel_finish(mModel), ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksModel_finish(mModel), ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestModel, CreateCompilation) {
ANeuralNetworksCompilation* compilation = nullptr;
EXPECT_EQ(ANeuralNetworksCompilation_create(nullptr, &compilation),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksCompilation_create(mModel, nullptr), ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksCompilation_create(mModel, &compilation), ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestIdentify, Ok) {
uint32_t inList[3]{0, 1, 2};
uint32_t outList[1]{3};
ASSERT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 3, inList, 1, outList),
ANEURALNETWORKS_NO_ERROR);
ASSERT_EQ(ANeuralNetworksModel_finish(mModel), ANEURALNETWORKS_NO_ERROR);
}
TEST_F(ValidationTestIdentify, InputIsOutput) {
uint32_t inList[3]{0, 1, 2};
uint32_t outList[2]{3, 0};
ASSERT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 3, inList, 2, outList),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestIdentify, OutputIsInput) {
uint32_t inList[4]{0, 1, 2, 3};
uint32_t outList[1]{3};
ASSERT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 4, inList, 1, outList),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestIdentify, DuplicateInputs) {
uint32_t inList[4]{0, 1, 2, 0};
uint32_t outList[1]{3};
ASSERT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 4, inList, 1, outList),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestIdentify, DuplicateOutputs) {
uint32_t inList[3]{0, 1, 2};
uint32_t outList[2]{3, 3};
ASSERT_EQ(ANeuralNetworksModel_identifyInputsAndOutputs(mModel, 3, inList, 2, outList),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestCompilation, SetPreference) {
EXPECT_EQ(ANeuralNetworksCompilation_setPreference(nullptr, ANEURALNETWORKS_PREFER_LOW_POWER),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksCompilation_setPreference(mCompilation, 40), ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestCompilation, CreateExecution) {
ANeuralNetworksExecution* execution = nullptr;
EXPECT_EQ(ANeuralNetworksExecution_create(nullptr, &execution),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksExecution_create(mCompilation, nullptr),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksExecution_create(mCompilation, &execution),
ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestCompilation, Finish) {
EXPECT_EQ(ANeuralNetworksCompilation_finish(nullptr), ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksCompilation_finish(mCompilation), ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksCompilation_setPreference(mCompilation,
ANEURALNETWORKS_PREFER_FAST_SINGLE_ANSWER),
ANEURALNETWORKS_BAD_STATE);
EXPECT_EQ(ANeuralNetworksCompilation_finish(mCompilation), ANEURALNETWORKS_BAD_STATE);
}
TEST_F(ValidationTestExecution, SetInput) {
ANeuralNetworksExecution* execution;
EXPECT_EQ(ANeuralNetworksExecution_create(mCompilation, &execution), ANEURALNETWORKS_NO_ERROR);
char buffer[20];
EXPECT_EQ(ANeuralNetworksExecution_setInput(nullptr, 0, nullptr, buffer, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksExecution_setInput(execution, 0, nullptr, nullptr, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
// This should fail, since memory is not the size of a float32.
EXPECT_EQ(ANeuralNetworksExecution_setInput(execution, 0, nullptr, buffer, 20),
ANEURALNETWORKS_BAD_DATA);
// This should fail, as this operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setInput(execution, 999, nullptr, buffer, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, as this operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setInput(execution, -1, nullptr, buffer, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestExecution, SetOutput) {
ANeuralNetworksExecution* execution;
EXPECT_EQ(ANeuralNetworksExecution_create(mCompilation, &execution), ANEURALNETWORKS_NO_ERROR);
char buffer[20];
EXPECT_EQ(ANeuralNetworksExecution_setOutput(nullptr, 0, nullptr, buffer, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksExecution_setOutput(execution, 0, nullptr, nullptr, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
// This should fail, since memory is not the size of a float32.
EXPECT_EQ(ANeuralNetworksExecution_setOutput(execution, 0, nullptr, buffer, 20),
ANEURALNETWORKS_BAD_DATA);
// This should fail, as this operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setOutput(execution, 999, nullptr, buffer, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, as this operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setOutput(execution, -1, nullptr, buffer, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestExecution, SetInputFromMemory) {
ANeuralNetworksExecution* execution;
EXPECT_EQ(ANeuralNetworksExecution_create(mCompilation, &execution), ANEURALNETWORKS_NO_ERROR);
const size_t memorySize = 20;
int memoryFd = ASharedMemory_create("nnMemory", memorySize);
ASSERT_GT(memoryFd, 0);
ANeuralNetworksMemory* memory;
EXPECT_EQ(ANeuralNetworksMemory_createFromFd(memorySize, PROT_READ | PROT_WRITE,
memoryFd, 0, &memory),
ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksExecution_setInputFromMemory(nullptr, 0, nullptr,
memory, 0, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksExecution_setInputFromMemory(execution, 0, nullptr,
nullptr, 0, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
// This should fail, since the operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setInputFromMemory(execution, 999, nullptr,
memory, 0, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since the operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setInputFromMemory(execution, -1, nullptr,
memory, 0, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since memory is not the size of a float32.
EXPECT_EQ(ANeuralNetworksExecution_setInputFromMemory(execution, 0, nullptr,
memory, 0, memorySize),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since offset is larger than memorySize.
EXPECT_EQ(ANeuralNetworksExecution_setInputFromMemory(execution, 0, nullptr,
memory, memorySize + 1, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since requested size is larger than the memory.
EXPECT_EQ(ANeuralNetworksExecution_setInputFromMemory(execution, 0, nullptr,
memory, memorySize - 3, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestExecution, SetOutputFromMemory) {
ANeuralNetworksExecution* execution;
EXPECT_EQ(ANeuralNetworksExecution_create(mCompilation, &execution), ANEURALNETWORKS_NO_ERROR);
const size_t memorySize = 20;
int memoryFd = ASharedMemory_create("nnMemory", memorySize);
ASSERT_GT(memoryFd, 0);
ANeuralNetworksMemory* memory;
EXPECT_EQ(ANeuralNetworksMemory_createFromFd(memorySize, PROT_READ | PROT_WRITE,
memoryFd, 0, &memory),
ANEURALNETWORKS_NO_ERROR);
EXPECT_EQ(ANeuralNetworksExecution_setOutputFromMemory(nullptr, 0, nullptr,
memory, 0, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksExecution_setOutputFromMemory(execution, 0, nullptr,
nullptr, 0, sizeof(float)),
ANEURALNETWORKS_UNEXPECTED_NULL);
// This should fail, since the operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setOutputFromMemory(execution, 999, nullptr,
memory, 0, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since the operand does not exist.
EXPECT_EQ(ANeuralNetworksExecution_setOutputFromMemory(execution, -1, nullptr,
memory, 0, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since memory is not the size of a float32.
EXPECT_EQ(ANeuralNetworksExecution_setOutputFromMemory(execution, 0, nullptr,
memory, 0, memorySize),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since offset is larger than memorySize.
EXPECT_EQ(ANeuralNetworksExecution_setOutputFromMemory(execution, 0, nullptr,
memory, memorySize + 1, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
// This should fail, since requested size is larger than the memory.
EXPECT_EQ(ANeuralNetworksExecution_setOutputFromMemory(execution, 0, nullptr,
memory, memorySize - 3, sizeof(float)),
ANEURALNETWORKS_BAD_DATA);
}
TEST_F(ValidationTestExecution, StartCompute) {
ANeuralNetworksExecution* execution;
EXPECT_EQ(ANeuralNetworksExecution_create(mCompilation, &execution), ANEURALNETWORKS_NO_ERROR);
ANeuralNetworksEvent* event;
EXPECT_EQ(ANeuralNetworksExecution_startCompute(nullptr, &event),
ANEURALNETWORKS_UNEXPECTED_NULL);
EXPECT_EQ(ANeuralNetworksExecution_startCompute(execution, nullptr),
ANEURALNETWORKS_UNEXPECTED_NULL);
}
TEST_F(ValidationTestExecution, EventWait) {
EXPECT_EQ(ANeuralNetworksEvent_wait(nullptr), ANEURALNETWORKS_UNEXPECTED_NULL);
}
} // namespace