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!14358 [MS][LITE][Develop]fix input tensor check 

From: @lx0095
Reviewed-by: @hangangqiang,@zhang_xue_tong,@zhanghaibo5
Signed-off-by: @zhang_xue_tong
This commit is contained in:
mindspore-ci-bot 2021-04-01 11:35:08 +08:00 committed by Gitee
parent 1ad05f52cb a949a11af5
commit be6cd743bf
13 changed files with 43 additions and 27 deletions
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2
mindspore/lite/nnacl/fp32/prelu_fp32.c
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@ -16,7 +16,7 @@
#include "nnacl/fp32/prelu_fp32.h"
#ifdef ENABLE_ARM64
inline void PRelu4x16(const float *in, float *out, float *cur_slope, size_t step) {
static inline void PRelu4x16(const float *in, float *out, float *cur_slope, size_t step) {
asm volatile(
"mov x10, %[in]\n"
"mov x11, %[out]\n"

3
mindspore/lite/src/cxx_api/cell.cc
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@ -13,11 +13,11 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "include/api/cell.h"
#include "src/common/log_adapter.h"
namespace mindspore {
class GraphImpl {};
std::vector<Output> CellBase::operator()(const std::vector<Input> &inputs) const {
@ -90,5 +90,4 @@ InputAndOutput::InputAndOutput(const std::shared_ptr<CellBase> &cell, const std:
int32_t index) {
MS_LOG(ERROR) << "Unsupported feature.";
}
} // namespace mindspore

2
mindspore/lite/src/cxx_api/context.cc
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@ -13,6 +13,7 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "include/api/context.h"
#include <string>
#include <memory>
@ -262,5 +263,4 @@ enum DataType Ascend310DeviceInfo::GetOutputType() const {
MS_LOG(ERROR) << "Unsupported Feature.";
return DataType::kTypeUnknown;
}
} // namespace mindspore

1
mindspore/lite/src/cxx_api/graph/graph.cc
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@ -19,7 +19,6 @@
#include "src/cxx_api/graph/graph_data.h"
namespace mindspore {
Graph::Graph() : graph_data_(nullptr) {}
Graph::Graph(const std::shared_ptr<GraphData> &graph_data) : graph_data_(graph_data) {}

2
mindspore/lite/src/cxx_api/graph/graph_data.h
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@ -13,6 +13,7 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_SRC_CXX_API_GRAPH_GRAPH_DATA_H
#define MINDSPORE_LITE_SRC_CXX_API_GRAPH_GRAPH_DATA_H
@ -39,4 +40,5 @@ class Graph::GraphData {
std::shared_ptr<lite::Model> lite_model_;
};
} // namespace mindspore
#endif // MINDSPORE_LITE_SRC_CXX_API_GRAPH_GRAPH_DATA_H

2
mindspore/lite/src/cxx_api/model/model.cc
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@ -13,6 +13,7 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "include/api/model.h"
#include "include/api/types.h"
#include "include/api/context.h"
@ -21,7 +22,6 @@
#include "src/common/log_adapter.h"
namespace mindspore {
Status Model::Build(GraphCell graph, const std::shared_ptr<Context> &model_context) {
if (impl_ != nullptr) {
MS_LOG(DEBUG) << "Model has been already built.";

6
mindspore/lite/src/cxx_api/model/model_impl.cc
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@ -150,6 +150,11 @@ Status ModelImpl::Predict(const std::vector<MSTensor> &inputs, std::vector<MSTen
<< ".";
return kLiteInputTensorError;
}
if (user_input.Data() == nullptr) {
ResetTensorData(old_data, input_tensors);
MS_LOG(ERROR) << "Tensor " << user_input.Name() << " has no data.";
return kLiteInputTensorError;
}
if (user_input.Name() != input->tensor_name()) {
MS_LOG(WARNING) << "Tensor " << user_input.Name() << " has a different name from input" << input->tensor_name()
<< ".";
@ -384,5 +389,4 @@ Status ModelImpl::Resize(const std::vector<MSTensor> &inputs, const std::vector<
auto ret = session_->Resize(inner_input, truncated_shape);
return static_cast<StatusCode>(ret);
}
} // namespace mindspore

2
mindspore/lite/src/cxx_api/model/model_impl.h
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@ -13,8 +13,10 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_SRC_CXX_API_MODEL_MODEL_IMPL_H
#define MINDSPORE_LITE_SRC_CXX_API_MODEL_MODEL_IMPL_H
#include <functional>
#include <map>
#include <string>

1
mindspore/lite/src/cxx_api/serialization.cc
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@ -27,7 +27,6 @@
#include "src/common/log_adapter.h"
namespace mindspore {
Status Serialization::Load(const void *model_data, size_t data_size, ModelType model_type, Graph *graph) {
if (model_type != kMindIR) {
MS_LOG(ERROR) << "Unsupported IR.";

14
mindspore/lite/src/cxx_api/tensor/tensor_impl.cc
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@ -13,6 +13,7 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <cstddef>
#include <numeric>
#include <memory>
@ -33,8 +34,9 @@
namespace mindspore {
using mindspore::lite::RET_OK;
MSTensor::Impl *MSTensor::Impl::CreateTensorImpl(const std::string &name, enum DataType type,
const std::vector<int64_t> &shape, const void *data, size_t data_len) {
std::shared_ptr<MSTensor::Impl> MSTensor::Impl::CreateTensorImpl(const std::string &name, enum DataType type,
const std::vector<int64_t> &shape, const void *data,
size_t data_len) {
std::vector<int32_t> truncated_shape = TruncateShape(shape, static_cast<enum TypeId>(type), data_len, true);
if (truncated_shape.empty() && !(shape.empty())) {
MS_LOG(ERROR) << "Invalid shape for creating tensor.";
@ -45,7 +47,7 @@ MSTensor::Impl *MSTensor::Impl::CreateTensorImpl(const std::string &name, enum D
MS_LOG(ERROR) << "Failed to allocate lite tensor.";
return nullptr;
}
auto impl = new (std::nothrow) Impl(lite_tensor);
auto impl = std::shared_ptr<MSTensor::Impl>(new (std::nothrow) Impl(lite_tensor));
if (impl == nullptr) {
MS_LOG(ERROR) << "Failed to allocate tensor impl.";
return nullptr;
@ -54,7 +56,8 @@ MSTensor::Impl *MSTensor::Impl::CreateTensorImpl(const std::string &name, enum D
return impl;
}
MSTensor::Impl *MSTensor::Impl::StringsToTensorImpl(const std::string &name, const std::vector<std::string> &str) {
std::shared_ptr<MSTensor::Impl> MSTensor::Impl::StringsToTensorImpl(const std::string &name,
const std::vector<std::string> &str) {
auto lite_tensor = new (std::nothrow) lite::Tensor();
if (lite_tensor == nullptr) {
MS_LOG(ERROR) << "Failed to allocate lite tensor.";
@ -67,7 +70,7 @@ MSTensor::Impl *MSTensor::Impl::StringsToTensorImpl(const std::string &name, con
delete lite_tensor;
return nullptr;
}
auto impl = new (std::nothrow) Impl(lite_tensor);
auto impl = std::shared_ptr<MSTensor::Impl>(new (std::nothrow) Impl(lite_tensor));
if (impl == nullptr) {
delete lite_tensor;
MS_LOG(ERROR) << "Failed to allocate tensor impl.";
@ -77,5 +80,4 @@ MSTensor::Impl *MSTensor::Impl::StringsToTensorImpl(const std::string &name, con
impl->set_from_session(false);
return impl;
}
} // namespace mindspore

15
mindspore/lite/src/cxx_api/tensor/tensor_impl.h
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@ -13,6 +13,10 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H
#define MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H
#include <cstddef>
#include <numeric>
#include <memory>
@ -53,10 +57,10 @@ class MSTensor::Impl {
}
}
static Impl *CreateTensorImpl(const std::string &name, enum DataType type, const std::vector<int64_t> &shape,
const void *data, size_t data_len);
static std::shared_ptr<Impl> CreateTensorImpl(const std::string &name, enum DataType type,
const std::vector<int64_t> &shape, const void *data, size_t data_len);
static Impl *StringsToTensorImpl(const std::string &name, const std::vector<std::string> &str);
static std::shared_ptr<Impl> StringsToTensorImpl(const std::string &name, const std::vector<std::string> &str);
static std::vector<std::string> TensorImplToStrings(const std::shared_ptr<Impl> &impl) {
std::vector<std::string> empty;
@ -116,7 +120,7 @@ class MSTensor::Impl {
return nullptr;
}
return std::shared_ptr<const void>(lite_tensor_->MutableData(), [](const void *) {});
return std::shared_ptr<const void>(lite_tensor_->data(), [](const void *) {});
}
virtual void *MutableData() {
@ -158,5 +162,6 @@ class MSTensor::Impl {
bool own_data_ = false;
bool from_session_ = false;
};
} // namespace mindspore
#endif // MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H

7
mindspore/lite/src/cxx_api/tensor_utils.h
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@ -13,6 +13,10 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_SRC_CXX_API_TENSOR_UTILS_H
#define MINDSPORE_LITE_SRC_CXX_API_TENSOR_UTILS_H
#include <limits.h>
#include <vector>
#include "ir/dtype/type_id.h"
@ -45,5 +49,6 @@ static std::vector<int32_t> TruncateShape(const std::vector<int64_t> &shape, enu
}
return truncated_shape;
}
} // namespace mindspore
#endif // MINDSPORE_LITE_SRC_CXX_API_TENSOR_UTILS_H

13
mindspore/lite/src/cxx_api/types.cc
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@ -13,6 +13,7 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "include/api/types.h"
#include <string.h>
#include <limits.h>
@ -25,7 +26,6 @@
#include "src/common/log_adapter.h"
namespace mindspore {
class Buffer::Impl {
public:
Impl() : data_() { MS_LOG(ERROR) << "Unsupported feature."; }
@ -64,7 +64,7 @@ MSTensor::MSTensor(std::nullptr_t) : impl_(nullptr) {}
MSTensor::MSTensor(const std::shared_ptr<Impl> &impl) : impl_(impl) {}
MSTensor::MSTensor(const std::vector<char> &name, enum DataType type, const std::vector<int64_t> &shape,
const void *data, size_t data_len)
: impl_(std::shared_ptr<Impl>(Impl::CreateTensorImpl(CharToString(name), type, shape, data, data_len))) {}
: impl_(Impl::CreateTensorImpl(CharToString(name), type, shape, data, data_len)) {}
MSTensor::~MSTensor() = default;
bool MSTensor::operator==(std::nullptr_t) const { return impl_ == nullptr; }
@ -79,7 +79,7 @@ MSTensor *MSTensor::CreateTensor(const std::vector<char> &name, enum DataType ty
return nullptr;
}
::memcpy(new_data, data, data_len);
auto impl = std::shared_ptr<Impl>(Impl::CreateTensorImpl(CharToString(name), type, shape, new_data, data_len));
auto impl = Impl::CreateTensorImpl(CharToString(name), type, shape, new_data, data_len);
if (impl == nullptr) {
MS_LOG(ERROR) << "Allocate tensor impl failed.";
free(new_data);
@ -97,7 +97,7 @@ MSTensor *MSTensor::CreateTensor(const std::vector<char> &name, enum DataType ty
MSTensor *MSTensor::CreateRefTensor(const std::vector<char> &name, enum DataType type,
const std::vector<int64_t> &shape, const void *data, size_t data_len) noexcept {
auto impl = std::shared_ptr<Impl>(Impl::CreateTensorImpl(CharToString(name), type, shape, data, data_len));
auto impl = Impl::CreateTensorImpl(CharToString(name), type, shape, data, data_len);
if (impl == nullptr) {
MS_LOG(ERROR) << "Allocate tensor impl failed.";
return nullptr;
@ -111,7 +111,7 @@ MSTensor *MSTensor::CreateRefTensor(const std::vector<char> &name, enum DataType
}
MSTensor *MSTensor::CharStringsToTensor(const std::vector<char> &name, const std::vector<std::vector<char>> &inputs) {
auto impl = std::shared_ptr<Impl>(Impl::StringsToTensorImpl(CharToString(name), VectorCharToString(inputs)));
auto impl = Impl::StringsToTensorImpl(CharToString(name), VectorCharToString(inputs));
if (impl == nullptr) {
MS_LOG(ERROR) << "Allocate tensor impl failed.";
return nullptr;
@ -148,8 +148,7 @@ MSTensor *MSTensor::Clone() const {
MS_LOG(ERROR) << "Allocate data failed.";
return nullptr;
}
auto impl =
std::shared_ptr<Impl>(Impl::CreateTensorImpl(this->Name(), this->DataType(), this->Shape(), new_data, data_len));
auto impl = Impl::CreateTensorImpl(this->Name(), this->DataType(), this->Shape(), new_data, data_len);
if (impl == nullptr) {
MS_LOG(ERROR) << "Allocate tensor impl failed.";
free(new_data);