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310 control getoutput

This commit is contained in:
ttudu 2021-09-16 16:05:54 +08:00
parent a59b3a40a9
commit eddf612413
3 changed files with 130 additions and 0 deletions
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57
mindspore/ccsrc/cxx_api/model/acl/acl_model_multi.cc
View File

@ -20,6 +20,8 @@
#include <map>
#include <string>
#include <algorithm>
#include <numeric>
#include <functional>
#include "backend/session/session_basic.h"
#include "backend/session/session_factory.h"
#include "cxx_api/factory.h"
@ -33,6 +35,14 @@ namespace mindspore {
API_FACTORY_REG(ModelImpl, Ascend310, AclModelMulti);
namespace {
std::map<DataType, size_t> kDtypeMap = {
{DataType::kNumberTypeBool, sizeof(bool)}, {DataType::kNumberTypeInt8, sizeof(int8_t)},
{DataType::kNumberTypeInt16, sizeof(int16_t)}, {DataType::kNumberTypeInt32, sizeof(int32_t)},
{DataType::kNumberTypeInt64, sizeof(int64_t)}, {DataType::kNumberTypeFloat16, sizeof(float16)},
{DataType::kNumberTypeFloat32, sizeof(float)}, {DataType::kNumberTypeFloat64, sizeof(double)},
{DataType::kNumberTypeUInt8, sizeof(uint8_t)}, {DataType::kNumberTypeUInt16, sizeof(uint16_t)},
{DataType::kNumberTypeUInt32, sizeof(uint32_t)}, {DataType::kNumberTypeUInt64, sizeof(uint64_t)}};
class MSTensorRef : public BaseRef {
public:
static VectorRef Convert(const std::vector<MSTensor> &tensors) {
@ -369,6 +379,8 @@ Status AclModelMulti::Build() {
return abstract;
});
(void)InferMindir(ModelImpl::GetFuncGraph(), broaded_args);
// set output
SetOutput();
// create vm
auto backend = CreateBackend(std::make_shared<AclModelOptions>(model_context_));
auto context_ptr = MsContext::GetInstance();
@ -449,6 +461,51 @@ void AclModelMulti::SetInputs() {
}
}
void AclModelMulti::SetOutput() {
if (outputs_.empty()) {
auto fg = ModelImpl::GetFuncGraph();
MS_EXCEPTION_IF_NULL(fg);
const auto output = fg->output();
MS_EXCEPTION_IF_NULL(output);
auto abs = output->abstract();
MS_EXCEPTION_IF_NULL(abs);
// DataType
DataType type_id;
if (abs->isa<abstract::AbstractTensor>()) {
auto abs_tensor = abs->cast<abstract::AbstractTensorPtr>();
auto ele = abs_tensor->element();
MS_EXCEPTION_IF_NULL(ele);
MS_EXCEPTION_IF_NULL(ele->GetTypeTrack());
type_id = static_cast<DataType>(ele->GetTypeTrack()->type_id());
} else {
MS_EXCEPTION_IF_NULL(abs->GetTypeTrack());
type_id = static_cast<DataType>(abs->GetTypeTrack()->type_id());
}
// Shape
auto shape_track = abs->GetShapeTrack();
MS_EXCEPTION_IF_NULL(shape_track);
std::vector<int64_t> shape = {};
if (shape_track->isa<abstract::Shape>()) {
auto shapeptr = shape_track->cast<abstract::ShapePtr>();
shape = static_cast<std::vector<int64_t>>(shapeptr->shape());
}
// Size
size_t ato_size = 0;
if (kDtypeMap.find(type_id) != kDtypeMap.end()) {
ato_size = kDtypeMap[type_id];
}
int64_t ele_num = std::accumulate(shape.begin(), shape.end(), 1, std::multiplies<int64_t>());
size_t size = ato_size * ele_num;
// create tensor
auto output_tensor = MSTensor::CreateTensor("", type_id, shape, nullptr, size);
outputs_.emplace_back(*output_tensor);
MSTensor::DestroyTensorPtr(output_tensor);
} else {
MS_LOG(DEBUG) << "outputs_ has been set.";
}
}
std::vector<MSTensor> AclModelMulti::GetInputs() {
if (!is_multi_graph_.has_value()) {
is_multi_graph_ = ModelImpl::GetFuncGraph() == nullptr ? false : HasMultiGraph(ModelImpl::GetFuncGraph());

2
mindspore/ccsrc/cxx_api/model/acl/acl_model_multi.h
View File

@ -21,6 +21,7 @@
#include <optional>
#include <vector>
#include <string>
#include <map>
namespace mindspore {
namespace compile {
@ -41,6 +42,7 @@ class AclModelMulti : public AclModel {
private:
void SetInputs();
void SetOutput();
std::optional<bool> is_multi_graph_;
std::shared_ptr<compile::MsBackend> backend_;

71
tests/st/cpp/model/test_control.cc
View File

@ -72,6 +72,17 @@ TEST_F(TestControl, InferIfbyIf) {
EXPECT_EQ(inputs_before[4].Shape()[2], 4);
EXPECT_EQ(inputs_before[4].Shape()[3], 5);
// assert outputs
std::vector<MSTensor> outputs_before = control_model.GetOutputs();
ASSERT_EQ(1, outputs_before.size());
EXPECT_EQ(outputs_before[0].DataType(), DataType::kNumberTypeFloat32);
ASSERT_TRUE(outputs_before[0].DataSize() == sizeof(float) * input_data.size());
ASSERT_EQ(outputs_before[0].Shape().size(), 4);
EXPECT_EQ(outputs_before[0].Shape()[0], 2);
EXPECT_EQ(outputs_before[0].Shape()[1], 3);
EXPECT_EQ(outputs_before[0].Shape()[2], 4);
EXPECT_EQ(outputs_before[0].Shape()[3], 5);
// prepare input
std::vector<MSTensor> outputs;
std::vector<MSTensor> inputs;
@ -130,6 +141,17 @@ TEST_F(TestControl, InferSimpleWhile) {
EXPECT_EQ(inputs_before[2].Shape()[2], 4);
EXPECT_EQ(inputs_before[2].Shape()[3], 5);
// assert outputs
std::vector<MSTensor> outputs_before = control_model.GetOutputs();
ASSERT_EQ(1, outputs_before.size());
EXPECT_EQ(outputs_before[0].DataType(), DataType::kNumberTypeFloat32);
ASSERT_TRUE(outputs_before[0].DataSize() == sizeof(float) * input_data.size());
ASSERT_EQ(outputs_before[0].Shape().size(), 4);
EXPECT_EQ(outputs_before[0].Shape()[0], 2);
EXPECT_EQ(outputs_before[0].Shape()[1], 3);
EXPECT_EQ(outputs_before[0].Shape()[2], 4);
EXPECT_EQ(outputs_before[0].Shape()[3], 5);
// prepare input
std::vector<MSTensor> outputs;
std::vector<MSTensor> inputs;
@ -173,6 +195,15 @@ TEST_F(TestControl, InferRecursive) {
ASSERT_EQ(inputs_before[0].Shape().size(), 1);
EXPECT_EQ(inputs_before[0].Shape()[0], 1);
// assert outputs
std::vector<MSTensor> outputs_before = control_model.GetOutputs();
ASSERT_EQ(1, outputs_before.size());
EXPECT_EQ(outputs_before[0].DataType(), DataType::kNumberTypeInt32);
ASSERT_TRUE(outputs_before[0].DataSize() == sizeof(int32_t));
ASSERT_EQ(outputs_before[0].Shape().size(), 1);
EXPECT_EQ(outputs_before[0].Shape()[0], 1);
// prepare input
std::vector<MSTensor> outputs;
std::vector<MSTensor> inputs;
@ -226,6 +257,14 @@ TEST_F(TestControl, InferMixedWhileIf) {
ASSERT_EQ(inputs_before[4].Shape().size(), 1);
EXPECT_EQ(inputs_before[4].Shape()[0], 1);
// assert outputs
std::vector<MSTensor> outputs_before = control_model.GetOutputs();
ASSERT_EQ(1, outputs_before.size());
EXPECT_EQ(outputs_before[0].DataType(), DataType::kNumberTypeInt32);
ASSERT_TRUE(outputs_before[0].DataSize() == sizeof(int32_t));
ASSERT_EQ(outputs_before[0].Shape().size(), 1);
EXPECT_EQ(outputs_before[0].Shape()[0], 1);
// prepare input
std::vector<MSTensor> outputs;
std::vector<MSTensor> inputs;
@ -279,6 +318,14 @@ TEST_F(TestControl, InferSingleFor) {
ASSERT_EQ(inputs_before[2].Shape().size(), 1);
EXPECT_EQ(inputs_before[2].Shape()[0], 1);
// assert outputs
std::vector<MSTensor> outputs_before = control_model.GetOutputs();
ASSERT_EQ(1, outputs_before.size());
EXPECT_EQ(outputs_before[0].DataType(), DataType::kNumberTypeInt32);
ASSERT_TRUE(outputs_before[0].DataSize() == sizeof(int32_t));
ASSERT_EQ(outputs_before[0].Shape().size(), 1);
EXPECT_EQ(outputs_before[0].Shape()[0], 1);
// prepare input
std::vector<MSTensor> outputs;
std::vector<MSTensor> inputs;
@ -324,6 +371,12 @@ TEST_F(TestControl, InferSingleOr) {
ASSERT_EQ(inputs_before[1].Shape().size(), 1);
EXPECT_EQ(inputs_before[1].Shape()[0], 2);
// assert outputs
std::vector<MSTensor> outputs_before = control_model.GetOutputs();
ASSERT_EQ(1, outputs_before.size());
EXPECT_EQ(outputs_before[0].DataType(), DataType::kNumberTypeFloat32);
ASSERT_TRUE(outputs_before[0].DataSize() == sizeof(float));
// prepare input
std::vector<MSTensor> outputs;
std::vector<MSTensor> inputs;
@ -339,6 +392,13 @@ TEST_F(TestControl, InferSingleOr) {
// infer
ASSERT_TRUE(control_model.Predict(inputs, &outputs) == kSuccess);
// assert outputs
std::vector<MSTensor> outputs_after = control_model.GetOutputs();
ASSERT_EQ(1, outputs_after.size());
EXPECT_EQ(outputs_after[0].DataType(), DataType::kNumberTypeFloat32);
ASSERT_TRUE(outputs_after[0].DataSize() == sizeof(float));
EXPECT_EQ(outputs_after[0].Shape().size(), outputs_before[0].Shape().size());
// assert output
ASSERT_TRUE(outputs.size() == 1);
auto out = outputs[0];
@ -375,6 +435,17 @@ TEST_F(TestControl, InferSingleSwitch) {
ASSERT_EQ(inputs_before[2].Shape().size(), 1);
EXPECT_EQ(inputs_before[2].Shape()[0], 1);
// assert outputs
std::vector<MSTensor> outputs_before = control_model.GetOutputs();
ASSERT_EQ(1, outputs_before.size());
EXPECT_EQ(outputs_before[0].DataType(), DataType::kNumberTypeFloat32);
ASSERT_TRUE(outputs_before[0].DataSize() == sizeof(float) * 224 * 224);
ASSERT_EQ(outputs_before[0].Shape().size(), 4);
EXPECT_EQ(outputs_before[0].Shape()[0], 1);
EXPECT_EQ(outputs_before[0].Shape()[1], 1);
EXPECT_EQ(outputs_before[0].Shape()[2], 224);
EXPECT_EQ(outputs_before[0].Shape()[3], 224);
// prepare input
std::vector<MSTensor> outputs;
std::vector<MSTensor> inputs;