!33036 DVPP method adapt and lite whl package bugfix

Merge pull request !33036 from chenping/runtime

include/api/types.h

@@ -140,6 +140,7 @@ class MS_API MSTensor {
 
   MSTensor();
   explicit MSTensor(const std::shared_ptr<Impl> &impl);
+  // if malloc data, user need to free after constructing MSTensor, else memory leak.
   inline MSTensor(const std::string &name, DataType type, const std::vector<int64_t> &shape, const void *data,
                   size_t data_len);
   explicit MSTensor(std::nullptr_t);

mindspore/lite/src/CMakeLists.txt

@@ -480,14 +480,18 @@ if(MSLITE_ENABLE_RUNTIME_CONVERT)
             quantizer_mid fusion_mid proto_mid graph_pass_mid preprocess_mid
             cpu_kernel_mid ccsrc_src_mid converter_src_mid anf_exporter_mid
             config_parser_mid mslite_converter_plugin mindspore_core coder_mid
-            ccsrc_debug_common_mid_ mindir_proto_mid _mindspore_transform_express_ir_obj
             mindir_serializer_mid mindspore::protobuf ${SECUREC_LIBRARY})
     target_link_libraries(mindspore-lite_static
             quantizer_mid fusion_mid proto_mid graph_pass_mid preprocess_mid
             cpu_kernel_mid ccsrc_src_mid converter_src_mid anf_exporter_mid
             config_parser_mid mslite_converter_plugin mindspore_core coder_mid
-            ccsrc_debug_common_mid_ mindir_proto_mid _mindspore_transform_express_ir_obj
             mindir_serializer_mid mindspore::protobuf ${SECUREC_LIBRARY})
+    if(NOT ENABLE_CLOUD_AND_LITE)
+        target_link_libraries(mindspore-lite
+                ccsrc_debug_common_mid_ mindir_proto_mid _mindspore_transform_express_ir_obj)
+        target_link_libraries(mindspore-lite_static
+                ccsrc_debug_common_mid_ mindir_proto_mid _mindspore_transform_express_ir_obj)
+    endif()
     if(MSLITE_ENABLE_ACL)
         target_link_libraries(mindspore-lite lite_acl_mid
                 mindspore_shared_lib)
@@ -552,4 +556,4 @@ endif()
 
 if(ENABLE_CLOUD_AND_LITE)
     set_target_properties(mindspore-lite PROPERTIES INSTALL_RPATH $ORIGIN)
-endif()
+endif()

mindspore/lite/src/common/tensor_util.cc

@@ -315,6 +315,20 @@ int CheckTensorsInvalid(const std::vector<Tensor *> &tensors) {
   return RET_OK;
 }
 
+std::string ShapeToString(const std::vector<int> &shape) {
+  std::string result = "[";
+  int max_size = 40;
+  result.reserve(max_size);
+  for (size_t i = 0; i < shape.size(); ++i) {
+    result += std::to_string(shape[i]);
+    if (i + 1 < shape.size()) {
+      result += ", ";
+    }
+  }
+  result += "]";
+  return result;
+}
+
 int CheckGraphInputShapes(const std::vector<Tensor *> &inputs,
                           const std::unordered_map<Tensor *, std::vector<int>> &input_shape_map) {
   for (const auto input : inputs) {
@@ -324,9 +338,17 @@ int CheckGraphInputShapes(const std::vector<Tensor *> &inputs,
       return RET_ERROR;
     }
     if (!input_shape_map.at(input).empty() && input_shape_map.at(input) != input->shape()) {
+#ifndef ENABLE_LITE_ACL
       MS_LOG(ERROR) << "graph input:" << input->tensor_name()
                     << " shape has been illegally modified, please modify the input shape with method Resize().";
       return RET_ERROR;
+#else
+      MS_LOG(WARNING) << "Please check graph input " << input->tensor_name()
+                      << " shape:" << ShapeToString(input->shape())
+                      << " has been modified by DVPP method to shape:" << ShapeToString(input_shape_map.at(input))
+                      << "."
+                      << "If not, the modification is illegal, please modify the input shape with method Resize().";
+#endif
     }
   }
   return RET_OK;

mindspore/lite/src/cxx_api/model/model_impl.cc

@@ -302,8 +302,15 @@ Status ModelImpl::Predict(const std::vector<MSTensor> &inputs, std::vector<MSTen
       if (user_input.MutableData() != input->data()) {
         if (input->Size() != user_input.DataSize()) {
           ResetTensorData(old_data, input_tensors);
+#ifndef ENABLE_LITE_ACL
           MS_LOG(ERROR) << "Tensor " << user_input.Name() << " has wrong data size.";
           return kLiteInputTensorError;
+#else
+          MS_LOG(WARNING) << "Please check tensor " << user_input.Name()
+                          << " has been modified data size by DVPP method.";
+          std::vector<int> truncate_shape = {static_cast<int>(user_input.DataSize())};
+          input->set_shape(truncate_shape);
+#endif
         }
         input->set_data(user_input.MutableData());
       }

mindspore/lite/src/ms_tensor.cc

@@ -104,7 +104,24 @@ tensor::MSTensor *tensor::MSTensor::CreateTensorByDeepCopy(const std::string &na
     tensor->set_data(const_cast<void *>(new_data));
   }
 
-  tensor->set_shape(shape);
+  size_t shape_size = 1;
+  if (shape.empty()) {
+    shape_size = 0;
+  } else {
+    for (size_t i = 0; i < shape.size(); ++i) {
+      if (shape[i] < 0) {
+        delete tensor;
+        return nullptr;
+      }
+      shape_size *= static_cast<size_t>(shape[i]);
+    }
+  }
+  if (data_len != shape_size * data_type_size) {
+    std::vector<int> truncate_shape = {static_cast<int>(data_len)};
+    tensor->set_shape(truncate_shape);
+  } else {
+    tensor->set_shape(shape);
+  }
   tensor->set_tensor_name(name);
   tensor->set_data_type(type);
   return tensor;

mindspore/lite/src/runtime/kernel/ascend/src/model_process.cc

@@ -15,6 +15,7 @@
  */
 
 #include "src/runtime/kernel/ascend/src/model_process.h"
+#include <sys/time.h>
 #include <utility>
 #include <algorithm>
 #include <map>
@@ -426,9 +427,9 @@ STATUS ModelProcess::CheckTensorByTensorInfo(const std::vector<mindspore::MSTens
   if (!IsDynamicShape()) {
     for (size_t i = 0; i < tensor_info.size(); ++i) {
       if (tensor[i].Shape() != tensor_info[i].dims) {
-        MS_LOG(ERROR) << "Note: input " << i << " shape not match, required " << ShapeToString(tensor_info[i].dims)
+        MS_LOG(WARNING) << "Note: input " << i << " shape not match, required " << ShapeToString(tensor_info[i].dims)
-                      << ", given " << ShapeToString(tensor[i].Shape());
+                        << ", given " << ShapeToString(tensor[i].Shape()) << "."
-        return lite::RET_ERROR;
+                        << "Please check input shape has been modified by DVPP method.";
       }
       if (tensor[i].DataType() != TransToDataType(tensor_info[i].data_type)) {
         MS_LOG(ERROR) << "Note: input " << i << " data type not match, required "
@@ -588,7 +589,24 @@ STATUS ModelProcess::PredictFromHost(const std::vector<mindspore::MSTensor> &inp
     DestroyInputsDataset();
     return ret;  // forward status error
   }
-  aclError acl_ret = aclmdlExecute(model_id_, inputs_, outputs_);
+
+  aclError acl_ret;
+  auto env = std::getenv("GLOG_v");
+  if (env != nullptr && env[0] == '1') {
+    struct timeval start_time;
+    struct timeval end_time;
+    (void)gettimeofday(&start_time, nullptr);
+    acl_ret = aclmdlExecute(model_id_, inputs_, outputs_);
+    (void)gettimeofday(&end_time, nullptr);
+    constexpr uint64_t kUSecondInSecond = 1000000;
+    uint64_t cost =
+      (kUSecondInSecond * static_cast<uint64_t>(end_time.tv_sec) + static_cast<uint64_t>(end_time.tv_usec)) -
+      (kUSecondInSecond * static_cast<uint64_t>(start_time.tv_sec) + static_cast<uint64_t>(start_time.tv_usec));
+    MS_LOG(INFO) << "Model execute in " << cost << " us";
+  } else {
+    acl_ret = aclmdlExecute(model_id_, inputs_, outputs_);
+  }
+
   DestroyInputsDataset();
   if (acl_ret != ACL_ERROR_NONE) {
     MS_LOG(ERROR) << "Execute Model Failed, ret = " << acl_ret;

mindspore/lite/tools/converter/converter.cc

@@ -119,6 +119,15 @@ schema::MetaGraphT *Converter::Convert(const std::unique_ptr<converter::Flags> &
     MS_LOG(ERROR) << "Parser/Import model return nullptr";
     return nullptr;
   }
+  MS_CHECK_TRUE_MSG(funcgraph_transform_ != nullptr, nullptr, "funcgraph_transform init failed.");
+  // funcgraph_transform
+  graph = funcgraph_transform_->Transform(graph, flag.get());
+  MS_CHECK_TRUE_MSG(graph != nullptr, nullptr, "Transform anf graph return nullptr.");
+  // export protobuf
+  auto status = MindIRSerialize(flag, graph);
+  if (status != RET_OK) {
+    MS_LOG(WARNING) << "Export to mindir proto return nullptr.";
+  }
   return TransferFuncGraph(flag, graph);
 }