!12484 MD C++ api decouple ABI compile macro

From: @luoyang42
Reviewed-by: 
Signed-off-by:

include/api/dual_abi_helper.h

@@ -16,11 +16,147 @@
 #ifndef MINDSPORE_INCLUDE_API_DUAL_ABI_HELPER_H_
 #define MINDSPORE_INCLUDE_API_DUAL_ABI_HELPER_H_
 
+#include <algorithm>
+#include <map>
+#include <memory>
+#include <optional>
 #include <string>
+#include <set>
+#include <unordered_map>
+#include <utility>
 #include <vector>
 
 namespace mindspore {
 inline std::vector<char> StringToChar(const std::string &s) { return std::vector<char>(s.begin(), s.end()); }
+
 inline std::string CharToString(const std::vector<char> &c) { return std::string(c.begin(), c.end()); }
+
+inline std::optional<std::vector<char>> OptionalStringToChar(const std::optional<std::string> &s) {
+  std::optional<std::vector<char>> ret = std::vector<char>(s->begin(), s->end());
+  return (s == std::nullopt) ? std::nullopt : ret;
+}
+
+inline std::optional<std::string> OptionalCharToString(const std::optional<std::vector<char>> &c) {
+  std::optional<std::string> ret = std::string(c->begin(), c->end());
+  return (c == std::nullopt) ? std::nullopt : ret;
+}
+
+inline std::pair<std::vector<char>, int32_t> PairStringToChar(const std::pair<std::string, int32_t> &s) {
+  return std::pair<std::vector<char>, int32_t>(std::vector<char>(s.first.begin(), s.first.end()), s.second);
+}
+
+inline std::pair<std::string, int32_t> PairCharToString(const std::pair<std::vector<char>, int32_t> &c) {
+  return std::pair<std::string, int32_t>(std::string(c.first.begin(), c.first.end()), c.second);
+}
+
+inline std::vector<std::vector<char>> VectorStringToChar(const std::vector<std::string> &s) {
+  std::vector<std::vector<char>> ret;
+  std::transform(s.begin(), s.end(), std::back_inserter(ret),
+                 [](auto str) { return std::vector<char>(str.begin(), str.end()); });
+  return ret;
+}
+
+inline std::vector<std::string> VectorCharToString(const std::vector<std::vector<char>> &c) {
+  std::vector<std::string> ret;
+  std::transform(c.begin(), c.end(), std::back_inserter(ret),
+                 [](auto ch) { return std::string(ch.begin(), ch.end()); });
+  return ret;
+}
+
+inline std::set<std::vector<char>> SetStringToChar(const std::set<std::string> &s) {
+  std::set<std::vector<char>> ret;
+  std::transform(s.begin(), s.end(), std::inserter(ret, ret.begin()),
+                 [](auto str) { return std::vector<char>(str.begin(), str.end()); });
+  return ret;
+}
+
+inline std::set<std::string> SetCharToString(const std::set<std::vector<char>> &c) {
+  std::set<std::string> ret;
+  std::transform(c.begin(), c.end(), std::inserter(ret, ret.begin()),
+                 [](auto ch) { return std::string(ch.begin(), ch.end()); });
+  return ret;
+}
+
+inline std::map<std::vector<char>, int32_t> MapStringToChar(const std::map<std::string, int32_t> &s) {
+  std::map<std::vector<char>, int32_t> ret;
+  std::transform(s.begin(), s.end(), std::inserter(ret, ret.begin()), [](auto str) {
+    return std::pair<std::vector<char>, int32_t>(std::vector<char>(str.first.begin(), str.first.end()), str.second);
+  });
+  return ret;
+}
+
+inline std::map<std::string, int32_t> MapCharToString(const std::map<std::vector<char>, int32_t> &c) {
+  std::map<std::string, int32_t> ret;
+  std::transform(c.begin(), c.end(), std::inserter(ret, ret.begin()), [](auto ch) {
+    return std::pair<std::string, int32_t>(std::string(ch.first.begin(), ch.first.end()), ch.second);
+  });
+  return ret;
+}
+
+inline std::map<std::vector<char>, std::vector<char>> UnorderedMapStringToChar(
+  const std::unordered_map<std::string, std::string> &s) {
+  std::map<std::vector<char>, std::vector<char>> ret;
+  std::transform(s.begin(), s.end(), std::inserter(ret, ret.begin()), [](auto str) {
+    return std::pair<std::vector<char>, std::vector<char>>(std::vector<char>(str.first.begin(), str.first.end()),
+                                                           std::vector<char>(str.second.begin(), str.second.end()));
+  });
+  return ret;
+}
+
+inline std::unordered_map<std::string, std::string> UnorderedMapCharToString(
+  const std::map<std::vector<char>, std::vector<char>> &c) {
+  std::unordered_map<std::string, std::string> ret;
+  std::transform(c.begin(), c.end(), std::inserter(ret, ret.begin()), [](auto ch) {
+    return std::pair<std::string, std::string>(std::string(ch.first.begin(), ch.first.end()),
+                                               std::string(ch.second.begin(), ch.second.end()));
+  });
+  return ret;
+}
+
+inline std::vector<std::pair<std::vector<char>, std::vector<int32_t>>> ClassIndexStringToChar(
+  const std::vector<std::pair<std::string, std::vector<int32_t>>> &s) {
+  std::vector<std::pair<std::vector<char>, std::vector<int32_t>>> ret;
+  std::transform(s.begin(), s.end(), std::back_inserter(ret), [](auto str) {
+    return std::pair<std::vector<char>, std::vector<int32_t>>(std::vector<char>(str.first.begin(), str.first.end()),
+                                                              str.second);
+  });
+  return ret;
+}
+
+inline std::vector<std::pair<std::string, std::vector<int32_t>>> ClassIndexCharToString(
+  const std::vector<std::pair<std::vector<char>, std::vector<int32_t>>> &c) {
+  std::vector<std::pair<std::string, std::vector<int32_t>>> ret;
+  std::transform(c.begin(), c.end(), std::back_inserter(ret), [](auto ch) {
+    return std::pair<std::string, std::vector<int32_t>>(std::string(ch.first.begin(), ch.first.end()), ch.second);
+  });
+  return ret;
+}
+
+template <class T>
+inline std::map<std::vector<char>, T> PadInfoStringToChar(const std::map<std::string, T> &s_pad_info) {
+  std::map<std::vector<char>, T> ret;
+  std::transform(s_pad_info.begin(), s_pad_info.end(), std::inserter(ret, ret.begin()), [](auto str) {
+    return std::pair<std::vector<char>, T>(std::vector<char>(str.first.begin(), str.first.end()), str.second);
+  });
+  return ret;
+}
+
+template <class T>
+inline std::map<std::string, T> PadInfoCharToString(const std::map<std::vector<char>, T> &c_pad_info) {
+  std::map<std::string, T> ret;
+  std::transform(c_pad_info.begin(), c_pad_info.end(), std::inserter(ret, ret.begin()), [](auto ch) {
+    return std::pair<std::string, T>(std::string(ch.first.begin(), ch.first.end()), ch.second);
+  });
+  return ret;
+}
+
+template <class T>
+inline void TensorMapCharToString(const std::map<std::vector<char>, T> *c, std::unordered_map<std::string, T> *s) {
+  for (auto ch : *c) {
+    auto key = std::string(ch.first.begin(), ch.first.end());
+    auto val = ch.second;
+    s->insert(std::pair<std::string, T>(key, val));
+  }
+}
 }  // namespace mindspore
 #endif  // MINDSPORE_INCLUDE_API_DUAL_ABI_HELPER_H_

mindspore/ccsrc/minddata/dataset/api/config.cc

@@ -94,8 +94,8 @@ bool set_callback_timeback(int32_t timeout) {
 int32_t get_callback_timeout() { return _config->callback_timeout(); }
 
 // Function to load configurations from a file
-bool load(std::string file) {
-  Status rc = _config->LoadFile(file);
+bool load(const std::vector<char> &file) {
+  Status rc = _config->LoadFile(CharToString(file));
   if (rc.IsError()) {
     MS_LOG(ERROR) << rc << file;
     return false;

mindspore/ccsrc/minddata/dataset/api/iterator.cc

@@ -26,7 +26,7 @@ Iterator::Iterator() : consumer_(nullptr) {}
 Iterator::~Iterator() { Stop(); }
 
 // Get the next row from the data pipeline.
-Status Iterator::GetNextRow(MSTensorMap *row) {
+Status Iterator::GetNextRowCharIF(MSTensorMapChar *row) {
   // Clean data buffer
   row->clear();
   std::unordered_map<std::string, std::shared_ptr<dataset::Tensor>> md_map;
@@ -38,7 +38,8 @@ Status Iterator::GetNextRow(MSTensorMap *row) {
   }
   for (auto de_tensor : md_map) {
     CHECK_FAIL_RETURN_UNEXPECTED(de_tensor.second->HasData(), "Apply transform failed, output tensor has no data");
-    row->insert(std::make_pair(de_tensor.first, mindspore::MSTensor(std::make_shared<DETensor>(de_tensor.second))));
+    std::vector<char> col_name(de_tensor.first.begin(), de_tensor.first.end());
+    row->insert(std::make_pair(col_name, mindspore::MSTensor(std::make_shared<DETensor>(de_tensor.second))));
   }
 
   return Status::OK();

mindspore/ccsrc/minddata/dataset/api/transforms.cc

@@ -30,25 +30,30 @@ namespace transforms {
 // (In alphabetical order)
 
 // Constructor to Compose.
-Compose::Compose(const std::vector<TensorTransform *> &transforms) {
+struct Compose::Data {
+  std::vector<std::shared_ptr<TensorOperation>> transforms_;
+};
+
+Compose::Compose(const std::vector<TensorTransform *> &transforms) : data_(std::make_shared<Data>()) {
   (void)std::transform(
-    transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+    transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
     [](TensorTransform *op) -> std::shared_ptr<TensorOperation> { return op != nullptr ? op->Parse() : nullptr; });
 }
 
-Compose::Compose(const std::vector<std::shared_ptr<TensorTransform>> &transforms) {
-  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+Compose::Compose(const std::vector<std::shared_ptr<TensorTransform>> &transforms) : data_(std::make_shared<Data>()) {
+  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
                        [](std::shared_ptr<TensorTransform> op) -> std::shared_ptr<TensorOperation> {
                          return op != nullptr ? op->Parse() : nullptr;
                        });
 }
 
-Compose::Compose(const std::vector<std::reference_wrapper<TensorTransform>> &transforms) {
-  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+Compose::Compose(const std::vector<std::reference_wrapper<TensorTransform>> &transforms)
+    : data_(std::make_shared<Data>()) {
+  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
                        [](TensorTransform &op) -> std::shared_ptr<TensorOperation> { return op.Parse(); });
 }
 
-std::shared_ptr<TensorOperation> Compose::Parse() { return std::make_shared<ComposeOperation>(transforms_); }
+std::shared_ptr<TensorOperation> Compose::Parse() { return std::make_shared<ComposeOperation>(data_->transforms_); }
 
 // Constructor to Duplicate
 Duplicate::Duplicate() {}
@@ -56,59 +61,87 @@ Duplicate::Duplicate() {}
 std::shared_ptr<TensorOperation> Duplicate::Parse() { return std::make_shared<DuplicateOperation>(); }
 
 // Constructor to OneHot
-OneHot::OneHot(int32_t num_classes) : num_classes_(num_classes) {}
+struct OneHot::Data {
+  explicit Data(int32_t num_classes) : num_classes_(num_classes) {}
+  float num_classes_;
+};
+
+OneHot::OneHot(int32_t num_classes) : data_(std::make_shared<Data>(num_classes)) {}
 
-std::shared_ptr<TensorOperation> OneHot::Parse() { return std::make_shared<OneHotOperation>(num_classes_); }
+std::shared_ptr<TensorOperation> OneHot::Parse() { return std::make_shared<OneHotOperation>(data_->num_classes_); }
 
 // Constructor to RandomApply.
-RandomApply::RandomApply(const std::vector<TensorTransform *> &transforms, double prob) : prob_(prob) {
+struct RandomApply::Data {
+  std::vector<std::shared_ptr<TensorOperation>> transforms_;
+  double prob_;
+};
+
+RandomApply::RandomApply(const std::vector<TensorTransform *> &transforms, double prob)
+    : data_(std::make_shared<Data>()) {
   (void)std::transform(
-    transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+    transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
     [](TensorTransform *op) -> std::shared_ptr<TensorOperation> { return op != nullptr ? op->Parse() : nullptr; });
+  data_->prob_ = prob;
 }
 
-RandomApply::RandomApply(const std::vector<std::shared_ptr<TensorTransform>> &transforms, double prob) : prob_(prob) {
-  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+RandomApply::RandomApply(const std::vector<std::shared_ptr<TensorTransform>> &transforms, double prob)
+    : data_(std::make_shared<Data>()) {
+  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
                        [](std::shared_ptr<TensorTransform> op) -> std::shared_ptr<TensorOperation> {
                          return op != nullptr ? op->Parse() : nullptr;
                        });
+  data_->prob_ = prob;
 }
 
 RandomApply::RandomApply(const std::vector<std::reference_wrapper<TensorTransform>> &transforms, double prob)
-    : prob_(prob) {
-  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+    : data_(std::make_shared<Data>()) {
+  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
                        [](TensorTransform &op) -> std::shared_ptr<TensorOperation> { return op.Parse(); });
+  data_->prob_ = prob;
 }
 
 std::shared_ptr<TensorOperation> RandomApply::Parse() {
-  return std::make_shared<RandomApplyOperation>(transforms_, prob_);
+  return std::make_shared<RandomApplyOperation>(data_->transforms_, data_->prob_);
 }
 
 // Constructor to RandomChoice.
-RandomChoice::RandomChoice(const std::vector<TensorTransform *> &transforms) {
+struct RandomChoice::Data {
+  std::vector<std::shared_ptr<TensorOperation>> transforms_;
+};
+
+RandomChoice::RandomChoice(const std::vector<TensorTransform *> &transforms) : data_(std::make_shared<Data>()) {
   (void)std::transform(
-    transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+    transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
     [](TensorTransform *op) -> std::shared_ptr<TensorOperation> { return op != nullptr ? op->Parse() : nullptr; });
 }
 
-RandomChoice::RandomChoice(const std::vector<std::shared_ptr<TensorTransform>> &transforms) {
-  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+RandomChoice::RandomChoice(const std::vector<std::shared_ptr<TensorTransform>> &transforms)
+    : data_(std::make_shared<Data>()) {
+  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
                        [](std::shared_ptr<TensorTransform> op) -> std::shared_ptr<TensorOperation> {
                          return op != nullptr ? op->Parse() : nullptr;
                        });
 }
 
-RandomChoice::RandomChoice(const std::vector<std::reference_wrapper<TensorTransform>> &transforms) {
-  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(transforms_),
+RandomChoice::RandomChoice(const std::vector<std::reference_wrapper<TensorTransform>> &transforms)
+    : data_(std::make_shared<Data>()) {
+  (void)std::transform(transforms.begin(), transforms.end(), std::back_inserter(data_->transforms_),
                        [](TensorTransform &op) -> std::shared_ptr<TensorOperation> { return op.Parse(); });
 }
 
-std::shared_ptr<TensorOperation> RandomChoice::Parse() { return std::make_shared<RandomChoiceOperation>(transforms_); }
+std::shared_ptr<TensorOperation> RandomChoice::Parse() {
+  return std::make_shared<RandomChoiceOperation>(data_->transforms_);
+}
 
 // Constructor to TypeCast
-TypeCast::TypeCast(std::string data_type) : data_type_(data_type) {}
+struct TypeCast::Data {
+  explicit Data(const std::vector<char> &data_type) : data_type_(CharToString(data_type)) {}
+  std::string data_type_;
+};
+
+TypeCast::TypeCast(const std::vector<char> &data_type) : data_(std::make_shared<Data>(data_type)) {}
 
-std::shared_ptr<TensorOperation> TypeCast::Parse() { return std::make_shared<TypeCastOperation>(data_type_); }
+std::shared_ptr<TensorOperation> TypeCast::Parse() { return std::make_shared<TypeCastOperation>(data_->data_type_); }
 
 // Constructor to Unique
 Unique::Unique() {}

mindspore/ccsrc/minddata/dataset/engine/ir/cache/dataset_cache_impl.h

@@ -20,6 +20,8 @@
 #include <string>
 #include <optional>
 #include <utility>
+#include <vector>
+#include "include/api/dual_abi_helper.h"
 #include "minddata/dataset/engine/cache/cache_client.h"
 #include "minddata/dataset/engine/datasetops/cache_op.h"
 #include "minddata/dataset/engine/ir/cache/dataset_cache.h"
@@ -39,13 +41,13 @@ class DatasetCacheImpl : public DatasetCache {
   /// \param port optional port (default=50052).
   /// \param num_connections optional number of connections (default=12).
   /// \param prefetch_sz optional prefetch size (default=20).
-  DatasetCacheImpl(session_id_type id, uint64_t mem_sz, bool spill, std::optional<std::string> hostname,
+  DatasetCacheImpl(session_id_type id, uint64_t mem_sz, bool spill, std::optional<std::vector<char>> hostname,
                    std::optional<int32_t> port, std::optional<int32_t> num_connections,
                    std::optional<int32_t> prefetch_sz)
       : session_id_(id),
         cache_mem_sz_(mem_sz),
         spill_(spill),
-        hostname_(std::move(hostname)),
+        hostname_(OptionalCharToString(hostname)),
         port_(std::move(port)),
         num_connections_(std::move(num_connections)),
         prefetch_sz_(std::move(prefetch_sz)) {}

mindspore/ccsrc/minddata/dataset/include/config.h

@@ -19,6 +19,8 @@
 
 #include <cstdint>
 #include <string>
+#include <vector>
+#include "include/api/dual_abi_helper.h"
 
 namespace mindspore {
 namespace dataset {
@@ -70,7 +72,12 @@ int32_t get_callback_timeout();
 
 /// \brief Function to load configuration from a file.
 /// \param[in] file path of the configuration file to be loaded.
-bool load(std::string file);
+/// \note This api exists because std::string will constrained by ABI compile macro but char don't.
+bool load(const std::vector<char> &file);
+
+/// \brief Function to load configuration from a file.
+/// \param[in] file path of the configuration file to be loaded.
+inline bool load(std::string file) { return load(StringToChar(file)); }
 
 }  // namespace config
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/include/iterator.h

@@ -17,10 +17,12 @@
 #ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_ITERATOR_H_
 #define MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_ITERATOR_H_
 
+#include <map>
 #include <memory>
 #include <string>
 #include <unordered_map>
 #include <vector>
+#include "include/api/dual_abi_helper.h"
 #include "include/api/status.h"
 #include "include/api/types.h"
 
@@ -39,6 +41,7 @@ class IteratorConsumer;
 class Dataset;
 
 using MSTensorMap = std::unordered_map<std::string, mindspore::MSTensor>;
+using MSTensorMapChar = std::map<std::vector<char>, mindspore::MSTensor>;
 using MSTensorVec = std::vector<mindspore::MSTensor>;
 
 // Abstract class for iterating over the dataset.
@@ -60,7 +63,18 @@ class Iterator {
   /// \note Type of return data is a map(with column name).
   /// \param[out] row - the output tensor row.
   /// \return - a Status error code, returns OK if no error encountered.
-  Status GetNextRow(MSTensorMap *row);
+  Status GetNextRow(MSTensorMap *row) {
+    MSTensorMapChar row_;
+    row_.clear();
+    row->clear();
+    Status s = GetNextRowCharIF(&row_);
+    TensorMapCharToString(&row_, row);
+    return s;
+  }
+
+  // Char interface(CharIF) of GetNextRow
+  // This api exists because std::string will constrained by ABI compile macro but char don't.
+  Status GetNextRowCharIF(MSTensorMapChar *row);
 
   /// \brief Function to get the next row from the data pipeline.
   /// \note Type of return data is a vector(without column name).

mindspore/ccsrc/minddata/dataset/include/transforms.h

@@ -22,6 +22,7 @@
 #include <string>
 #include <vector>
 
+#include "include/api/dual_abi_helper.h"
 #include "include/api/status.h"
 #include "minddata/dataset/include/constants.h"
 
@@ -72,7 +73,8 @@ class Compose : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  std::vector<std::shared_ptr<TensorOperation>> transforms_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief Duplicate Op.
@@ -107,7 +109,8 @@ class OneHot : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  float num_classes_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief RandomApply Op.
@@ -129,8 +132,8 @@ class RandomApply : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  std::vector<std::shared_ptr<TensorOperation>> transforms_;
-  double prob_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief RandomChoice Op.
@@ -151,7 +154,8 @@ class RandomChoice : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  std::vector<std::shared_ptr<TensorOperation>> transforms_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief TypeCast Op.
@@ -160,7 +164,9 @@ class TypeCast : public TensorTransform {
  public:
   /// \brief Constructor.
   /// \param[in] data_type mindspore.dtype to be cast to.
-  explicit TypeCast(std::string data_type);
+  explicit TypeCast(std::string data_type) : TypeCast(StringToChar(data_type)) {}
+
+  explicit TypeCast(const std::vector<char> &data_type);
 
   /// \brief Destructor
   ~TypeCast() = default;
@@ -170,7 +176,8 @@ class TypeCast : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  std::string data_type_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief Unique Op.

mindspore/ccsrc/minddata/dataset/include/vision_ascend.h

@@ -50,7 +50,8 @@ class DvppDecodeResizeJpeg : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse(const MapTargetDevice &env) override;
 
  private:
-  std::vector<uint32_t> resize_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 class DvppDecodeResizeCropJpeg : public TensorTransform {
@@ -70,8 +71,8 @@ class DvppDecodeResizeCropJpeg : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse(const MapTargetDevice &env) override;
 
  private:
-  std::vector<uint32_t> crop_;
-  std::vector<uint32_t> resize_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 class DvppDecodePng : public TensorTransform {

mindspore/ccsrc/minddata/dataset/include/vision_lite.h

@@ -62,12 +62,8 @@ class Affine : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  float degrees_;
-  std::vector<float> translation_;
-  float scale_;
-  std::vector<float> shear_;
-  InterpolationMode interpolation_;
-  std::vector<uint8_t> fill_value_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief CenterCrop TensorTransform.
@@ -90,7 +86,8 @@ class CenterCrop : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse(const MapTargetDevice &env) override;
 
  private:
-  std::vector<int32_t> size_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief Crop TensorTransform.
@@ -112,8 +109,8 @@ class Crop : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  std::vector<int32_t> coordinates_;
-  std::vector<int32_t> size_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief Decode TensorTransform.
@@ -134,7 +131,8 @@ class Decode : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse(const MapTargetDevice &env) override;
 
  private:
-  bool rgb_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief Normalize TensorTransform.
@@ -158,8 +156,8 @@ class Normalize : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse(const MapTargetDevice &env) override;
 
  private:
-  std::vector<float> mean_;
-  std::vector<float> std_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief RandomAffine TensorTransform.
@@ -196,12 +194,8 @@ class RandomAffine : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse() override;
 
  private:
-  std::vector<float_t> degrees_;          // min_degree, max_degree
-  std::vector<float_t> translate_range_;  // maximum x translation percentage, maximum y translation percentage
-  std::vector<float_t> scale_range_;      // min_scale, max_scale
-  std::vector<float_t> shear_ranges_;     // min_x_shear, max_x_shear, min_y_shear, max_y_shear
-  InterpolationMode interpolation_;
-  std::vector<uint8_t> fill_value_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief Resize TensorTransform.
@@ -225,8 +219,8 @@ class Resize : public TensorTransform {
   std::shared_ptr<TensorOperation> Parse(const MapTargetDevice &env) override;
 
  private:
-  std::vector<int32_t> size_;
-  InterpolationMode interpolation_;
+  struct Data;
+  std::shared_ptr<Data> data_;
 };
 
 /// \brief Rotate TensorTransform.

mindspore/ccsrc/minddata/dataset/liteapi/include/execute.h

@@ -26,16 +26,27 @@
 namespace mindspore {
 namespace dataset {
 
+class DeviceResource;
 // class to run tensor operations in eager mode
 class Execute {
  public:
   /// \brief Constructor
-  explicit Execute(std::shared_ptr<TensorOperation> op);
+  // FIXME - Temporarily overload Execute to support both TensorOperation and TensorTransform
+  explicit Execute(std::shared_ptr<TensorOperation> op, MapTargetDevice deviceType = MapTargetDevice::kCpu);
+  explicit Execute(std::shared_ptr<TensorTransform> op, MapTargetDevice deviceType = MapTargetDevice::kCpu);
+  // explicit Execute(TensorTransform op, MapTargetDevice deviceType = MapTargetDevice::KCpu);
+  explicit Execute(TensorTransform *op, MapTargetDevice deviceType = MapTargetDevice::kCpu);
 
-  explicit Execute(std::vector<std::shared_ptr<TensorOperation>> ops);
+  explicit Execute(std::vector<std::shared_ptr<TensorOperation>> ops,
+                   MapTargetDevice deviceType = MapTargetDevice::kCpu);
+  explicit Execute(std::vector<std::shared_ptr<TensorTransform>> ops,
+                   MapTargetDevice deviceType = MapTargetDevice::kCpu);
+  explicit Execute(const std::vector<std::reference_wrapper<TensorTransform>> ops,
+                   MapTargetDevice deviceType = MapTargetDevice::kCpu);
+  explicit Execute(std::vector<TensorTransform *> ops, MapTargetDevice deviceType = MapTargetDevice::kCpu);
 
   /// \brief Destructor
-  ~Execute() = default;
+  ~Execute();
 
   /// \brief callable function to execute the TensorOperation in eager mode
   /// \param[in] input Tensor to be transformed
@@ -49,8 +60,16 @@ class Execute {
   /// \return - Status
   Status operator()(const std::vector<mindspore::MSTensor> &input_tensor_list, std::vector<mindspore::MSTensor> *out);
 
+  Status DeviceMemoryRelease();
+
  private:
+  Status validate_device_();
+
   std::vector<std::shared_ptr<TensorOperation>> ops_;
+
+  MapTargetDevice device_type_;
+
+  std::shared_ptr<DeviceResource> device_resource_;
 };
 
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/liteapi/include/iterator.h

@@ -17,10 +17,12 @@
 #ifndef MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_ITERATOR_H_
 #define MINDSPORE_CCSRC_MINDDATA_DATASET_INCLUDE_ITERATOR_H_
 
+#include <map>
 #include <memory>
 #include <string>
 #include <unordered_map>
 #include <vector>
+#include "include/api/dual_abi_helper.h"
 #include "include/api/status.h"
 #include "include/api/types.h"
 
@@ -39,6 +41,7 @@ class IteratorConsumer;
 class Dataset;
 
 using MSTensorMap = std::unordered_map<std::string, mindspore::MSTensor>;
+using MSTensorMapChar = std::map<std::vector<char>, mindspore::MSTensor>;
 using MSTensorVec = std::vector<mindspore::MSTensor>;
 
 // Abstract class for iterating over the dataset.
@@ -60,7 +63,18 @@ class Iterator {
   /// \note Type of return data is a map(with column name).
   /// \param[out] row - the output tensor row.
   /// \return - a Status error code, returns OK if no error encountered.
-  Status GetNextRow(MSTensorMap *row);
+  Status GetNextRow(MSTensorMap *row) {
+    MSTensorMapChar row_;
+    row_.clear();
+    row->clear();
+    Status s = GetNextRowCharIF(&row_);
+    TensorMapCharToString(&row_, row);
+    return s;
+  }
+
+  // Char interface(CharIF) of GetNextRow
+  // This api exists because std::string will constrained by ABI compile macro but char don't.
+  Status GetNextRowCharIF(MSTensorMapChar *row);
 
   /// \brief Function to get the next row from the data pipeline.
   /// \note Type of return data is a vector(without column name).