!20220 [MS][LITE][TOD] Activated UT of CxxApiLite and ported fixes from R1.3

Merge pull request !20220 from ehaleva/API2

mindspore/ccsrc/minddata/dataset/core/de_tensor.h

@@ -21,7 +21,11 @@
 #include <memory>
 #include "include/api/status.h"
 #include "include/api/types.h"
+#ifdef ENABLE_ANDROID
+#include "mindspore/lite/src/cxx_api/tensor/tensor_impl.h"
+#else
 #include "mindspore/core/ir/api_tensor_impl.h"
+#endif
 #include "minddata/dataset/core/tensor.h"
 
 namespace mindspore {
@@ -29,7 +33,7 @@ namespace dataset {
 class DETensor : public mindspore::MSTensor::Impl {
  public:
   DETensor() = default;
-  ~DETensor() override = default;
+  ~DETensor() = default;
   explicit DETensor(std::shared_ptr<dataset::Tensor> tensor_impl);
 #ifndef ENABLE_ANDROID
   explicit DETensor(std::shared_ptr<dataset::DeviceTensor> device_tensor_impl, bool is_device);

mindspore/lite/examples/train_lenet_java/prepare_and_run.sh

@@ -29,7 +29,7 @@ checkopts()
   do
     case "${opt}" in
       D)
-        MNIST_DATA_PATH=$OPTARG
+        MNIST_DATA_PATH=$(realpath $OPTARG)
         ;;
       d)
         DOCKER=$OPTARG
@@ -46,8 +46,8 @@ checkopts()
 }
 
 checkopts "$@"
-if [ "$MNIST_DATA_PATH" == "" ]; then
-  echo "MNIST Dataset directory path was not provided"
+if [ "$MNIST_DATA_PATH" == "" ] || [ ! -d "$MNIST_DATA_PATH" ]; then
+  echo "MNIST Dataset directory path was not provided or wrong path " $MNIST_DATA_PATH
   display_usage
   exit 1
 fi

mindspore/lite/examples/unified_api/src/inference.cc

@@ -68,21 +68,60 @@ int main(int argc, char **argv) {
   auto inputs = model.GetInputs();
   MS_ASSERT(inputs.size() >= 1);
 
-  auto *input_data = reinterpret_cast<float *>(inputs.at(0).MutableData());
+  int index = 0;
+  std::cout << "There are " << inputs.size() << " input tensors with sizes: " << std::endl;
+  for (auto tensor : inputs) {
+    std::cout << "tensor " << index++ << ": shape is [";
+    for (auto dim : tensor.Shape()) {
+      std::cout << dim << " ";
+    }
+    std::cout << "]" << std::endl;
+  }
+
+  mindspore::MSTensor *input_tensor = inputs.at(0).Clone();
+  auto *input_data = reinterpret_cast<float *>(input_tensor->MutableData());
   std::ifstream in;
   in.open("dataset/batch_of32.dat", std::ios::in | std::ios::binary);
-  in.read(reinterpret_cast<char *>(&input_data), inputs.at(0).ElementNum() * sizeof(float));
+  if (in.fail()) {
+    std::cout << "error loading dataset/batch_of32.dat file reading" << std::endl;
+    MS_ASSERT(!in.fail());
+  }
+  in.read(reinterpret_cast<char *>(input_data), inputs.at(0).ElementNum() * sizeof(float));
   in.close();
 
   std::vector<mindspore::MSTensor> outputs;
-  status = model.Predict(inputs, &outputs);
+  status = model.Predict({*input_tensor}, &outputs);
   if (status != mindspore::kSuccess) {
     std::cout << "Error " << status << " during running predict of model " << infer_model_fn;
     MS_ASSERT(status != mindspore::kSuccess);
   }
-  std::cout << "Got Vector of size: " << outputs.size() << std::endl;
+
+  index = 0;
+  std::cout << "There are " << outputs.size() << " output tensors with sizes: " << std::endl;
   for (auto tensor : outputs) {
-    std::cout << "[ " << tensor.Shape().at(0) << ", " << tensor.Shape().at(1) << "]\n";
+    std::cout << "tensor " << index++ << ": shape is [";
+    for (auto dim : tensor.Shape()) {
+      std::cout << dim << " ";
+    }
+    std::cout << "]" << std::endl;
+  }
+
+  if (outputs.size() > 0) {
+    std::cout << "The predicted classes are:" << std::endl;
+    auto predictions = reinterpret_cast<float *>(outputs.at(0).MutableData());
+    int i = 0;
+    for (int b = 0; b < outputs.at(0).Shape().at(0); b++) {
+      int max_c = 0;
+      float max_p = predictions[i];
+      for (int c = 0; c < outputs.at(0).Shape().at(1); c++, i++) {
+        if (predictions[i] > max_p) {
+          max_c = c;
+          max_p = predictions[i];
+        }
+      }
+      std::cout << max_c << ", ";
+    }
+    std::cout << std::endl;
   }
   return 0;
 }

mindspore/lite/minddata/CMakeLists.txt

@@ -12,7 +12,7 @@ set(CMAKE_CXX_STANDARD 17)
 set(CMAKE_CXX_FLAGS_DEBUG "$ENV{CXXFLAGS} -O0 -g2 -ggdb -fno-inline-functions -fno-omit-frame-pointer \
   -D_LIBCPP_INLINE_VISIBILITY='' -D_LIBCPP_DISABLE_EXTERN_TEMPLATE=1 -DHALF_ENABLE_CPP11_USER_LITERALS=0 \
   -D_FORTIFY_SOURCE=2 -Wno-cpp")
-set(CMAKE_CXX_FLAGS_DEBUG "$ENV{CXXFLAGS} -Werror -Wno-return-std-move -Wno-unused-private-field \
+set(CMAKE_CXX_FLAGS_DEBUG "${CMAKE_CXX_FLAGS_DEBUG} -Werror -Wno-return-std-move -Wno-unused-private-field \
   -Wno-unused-lambda-capture -Wno-sign-compare -Wno-overloaded-virtual -Wno-unneeded-internal-declaration \
   -Wno-unused-variable -Wno-pessimizing-move -Wno-inconsistent-missing-override")
 

mindspore/lite/src/cxx_api/tensor/tensor_impl.h

@@ -14,8 +14,8 @@
  * limitations under the License.
  */
 
-#ifndef MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H
-#define MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H
+#ifndef MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H_
+#define MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H_
 
 #include <cstddef>
 #include <numeric>
@@ -38,7 +38,7 @@ class MSTensor::Impl {
  public:
   Impl() {}
 
-  ~Impl() {
+  virtual ~Impl() {
     if (lite_tensor_ == nullptr) {
       return;
     }
@@ -65,7 +65,7 @@ class MSTensor::Impl {
 
   static std::vector<std::string> MS_API TensorImplToStrings(const std::shared_ptr<Impl> &impl);
 
-  const std::string &Name() const {
+  virtual const std::string &Name() const {
     static std::string empty = "";
     if (lite_tensor_ == nullptr) {
       MS_LOG(ERROR) << "Invalid tensor.";
@@ -82,7 +82,7 @@ class MSTensor::Impl {
     lite_tensor_->set_tensor_name(name);
   }
 
-  enum DataType DataType() const {
+  virtual enum DataType DataType() const {
     if (lite_tensor_ == nullptr) {
       MS_LOG(ERROR) << "Invalid tensor.";
       return DataType::kTypeUnknown;
@@ -106,18 +106,20 @@ class MSTensor::Impl {
     return static_cast<int64_t>(lite_tensor_->ElementsNum());
   }
 
-  const std::vector<int64_t> &Shape() {
+  virtual const std::vector<int64_t> &Shape() const {
     static std::vector<int64_t> empty;
     if (lite_tensor_ == nullptr) {
       MS_LOG(ERROR) << "Invalid tensor.";
       return empty;
     }
     auto shape = lite_tensor_->shape();
-    shape_.resize(shape.size());
-    std::transform(shape.begin(), shape.end(), shape_.begin(), [](int c) { return static_cast<int64_t>(c); });
-    return shape_;
+    lite_shape.resize(shape.size());
+    std::transform(shape.begin(), shape.end(), lite_shape.begin(), [](int c) { return static_cast<int64_t>(c); });
+    return lite_shape;
   }
 
+  virtual std::shared_ptr<Impl> Clone() const { return nullptr; }
+
   void SetShape(const std::vector<int64_t> &shape) {
     if (lite_tensor_ == nullptr) {
       MS_LOG(ERROR) << "Invalid tensor.";
@@ -161,7 +163,7 @@ class MSTensor::Impl {
     lite_tensor_->set_format(format);
   }
 
-  std::shared_ptr<const void> Data() const {
+  virtual std::shared_ptr<const void> Data() const {
     if (lite_tensor_ == nullptr) {
       MS_LOG(ERROR) << "Invalid tensor.";
       return nullptr;
@@ -175,7 +177,7 @@ class MSTensor::Impl {
     return std::shared_ptr<const void>(lite_tensor_->data(), [](const void *) {});
   }
 
-  void *MutableData() {
+  virtual void *MutableData() {
     if (lite_tensor_ == nullptr) {
       MS_LOG(ERROR) << "Invalid tensor.";
       return nullptr;
@@ -183,7 +185,7 @@ class MSTensor::Impl {
     return lite_tensor_->MutableData();
   }
 
-  size_t DataSize() const {
+  virtual size_t DataSize() const {
     if (lite_tensor_ == nullptr) {
       MS_LOG(ERROR) << "Invalid tensor.";
       return 0;
@@ -199,7 +201,7 @@ class MSTensor::Impl {
     lite_tensor_->set_data(data);
   }
 
-  bool IsDevice() const { return false; }
+  virtual bool IsDevice() const { return false; }
 
   tensor::MSTensor *lite_tensor() const { return lite_tensor_; }
 
@@ -219,10 +221,10 @@ class MSTensor::Impl {
  private:
   tensor::MSTensor *lite_tensor_ = nullptr;
   std::string tensor_name_ = "";
-  std::vector<int64_t> shape_ = {};
+  mutable std::vector<int64_t> lite_shape;
   bool own_data_ = false;
   bool from_session_ = false;
 };
 }  // namespace mindspore
 
-#endif  // MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H
+#endif  // MINDSPORE_LITE_SRC_CXX_API_TENSOR_TENSOR_IMPL_H_