!1202 Fix tensor print order

Merge pull request !1202 from zjun/fix_tensor_print

mindspore/ccsrc/utils/tensorprint_utils.cc

@@ -50,6 +50,7 @@ bool ParseTensorShape(const std::string &input_shape_str, std::vector<int> *cons
   if (tensor_shape == nullptr) {
     return false;
   }
+  MS_EXCEPTION_IF_NULL(dims);
   std::string shape_str = input_shape_str;
   if (shape_str.size() <= 2) {
     return false;
@@ -71,6 +72,8 @@ bool ParseTensorShape(const std::string &input_shape_str, std::vector<int> *cons
 
 bool PrintTensorToString(const char *str_data_ptr, mindspore::tensor::Tensor *const print_tensor,
                          const size_t &memory_size) {
+  MS_EXCEPTION_IF_NULL(str_data_ptr);
+  MS_EXCEPTION_IF_NULL(print_tensor);
   auto *tensor_data_ptr = static_cast<uint8_t *>(print_tensor->data_c(true));
   MS_EXCEPTION_IF_NULL(tensor_data_ptr);
   auto cp_ret =
@@ -83,55 +86,57 @@ bool PrintTensorToString(const char *str_data_ptr, mindspore::tensor::Tensor *co
 }
 
 template <typename T>
-void PrintScalarToString(const char *str_data_ptr, const string &tensor_type) {
+void PrintScalarToString(const char *str_data_ptr, const string &tensor_type, std::ostringstream *buf) {
+  MS_EXCEPTION_IF_NULL(str_data_ptr);
+  MS_EXCEPTION_IF_NULL(buf);
   const T *data_ptr = reinterpret_cast<const T *>(str_data_ptr);
-  std::ostringstream buf_scalar;
-  buf_scalar << "Tensor shape :1 " << tensor_type;
-  buf_scalar << "\nval:";
-  buf_scalar << *data_ptr;
-  std::cout << buf_scalar.str() << std::endl;
+  *buf << "Tensor shape:[1] " << tensor_type;
+  *buf << "\nval:";
+  *buf << *data_ptr << "\n";
 }
 
-void PrintScalarToBoolString(const char *str_data_ptr, const string &tensor_type) {
+void PrintScalarToBoolString(const char *str_data_ptr, const string &tensor_type, std::ostringstream *buf) {
+  MS_EXCEPTION_IF_NULL(str_data_ptr);
+  MS_EXCEPTION_IF_NULL(buf);
   const bool *data_ptr = reinterpret_cast<const bool *>(str_data_ptr);
-  std::ostringstream buf_scalar;
-  buf_scalar << "Tensor shape :1 " << tensor_type;
-  buf_scalar << "\nval:";
-  if (*data_ptr == true) {
-    buf_scalar << "True";
+  *buf << "Tensor shape:[1] " << tensor_type;
+  *buf << "\nval:";
+  if (*data_ptr) {
+    *buf << "True\n";
   } else {
-    buf_scalar << "False";
+    *buf << "False\n";
   }
-  std::cout << buf_scalar.str() << std::endl;
 }
 
-void convertDataItem2Scalar(const char *str_data_ptr, const string &tensor_type) {
+void convertDataItem2Scalar(const char *str_data_ptr, const string &tensor_type, std::ostringstream *buf) {
+  MS_EXCEPTION_IF_NULL(str_data_ptr);
+  MS_EXCEPTION_IF_NULL(buf);
   auto type_iter = print_type_map.find(tensor_type);
   auto type_id = type_iter->second;
   if (type_id == TypeId::kNumberTypeBool) {
-    PrintScalarToBoolString(str_data_ptr, tensor_type);
+    PrintScalarToBoolString(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeInt8) {
-    PrintScalarToString<int8_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<int8_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeUInt8) {
-    PrintScalarToString<uint8_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<uint8_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeInt16) {
-    PrintScalarToString<int16_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<int16_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeUInt16) {
-    PrintScalarToString<uint16_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<uint16_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeInt32) {
-    PrintScalarToString<int32_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<int32_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeUInt32) {
-    PrintScalarToString<uint32_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<uint32_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeInt64) {
-    PrintScalarToString<int64_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<int64_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeUInt64) {
-    PrintScalarToString<uint64_t>(str_data_ptr, tensor_type);
+    PrintScalarToString<uint64_t>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeFloat16) {
-    PrintScalarToString<float16>(str_data_ptr, tensor_type);
+    PrintScalarToString<float16>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeFloat32) {
-    PrintScalarToString<float>(str_data_ptr, tensor_type);
+    PrintScalarToString<float>(str_data_ptr, tensor_type, buf);
   } else if (type_id == TypeId::kNumberTypeFloat64) {
-    PrintScalarToString<double>(str_data_ptr, tensor_type);
+    PrintScalarToString<double>(str_data_ptr, tensor_type, buf);
   } else {
     MS_LOG(EXCEPTION) << "Cannot print scalar because of unsupport data type: " << tensor_type << ".";
   }
@@ -142,11 +147,7 @@ bool judgeLengthValid(const size_t str_len, const string &tensor_type) {
   if (type_iter == type_size_map.end()) {
     MS_LOG(EXCEPTION) << "type of scalar to print is not support.";
   }
-
-  if (str_len != type_iter->second) {
-    return false;
-  }
-  return true;
+  return str_len == type_iter->second;
 }
 
 #ifndef NO_DLIB
@@ -166,7 +167,7 @@ bool ConvertDataItem2Tensor(const std::vector<tdt::DataItem> &items) {
       if (!judgeLengthValid(str_data_ptr->size(), item.tensorType_)) {
         MS_LOG(EXCEPTION) << "Print op receive data length is  invalid.";
       }
-      convertDataItem2Scalar(str_data_ptr->data(), item.tensorType_);
+      convertDataItem2Scalar(str_data_ptr->data(), item.tensorType_, &buf);
       continue;
     }