!13789 dataset: Pybind change for data transforms

From: @cathwong
Reviewed-by: @robingrosman,@pandoublefeng
Signed-off-by: @pandoublefeng

mindspore/ccsrc/minddata/dataset/api/python/bindings/dataset/kernels/data/bindings.cc

@@ -20,15 +20,11 @@
 #include "minddata/dataset/api/python/pybind_register.h"
 #include "minddata/dataset/core/tensor_helpers.h"
 #include "minddata/dataset/kernels/data/concatenate_op.h"
-#include "minddata/dataset/kernels/data/duplicate_op.h"
 #include "minddata/dataset/kernels/data/fill_op.h"
 #include "minddata/dataset/kernels/data/mask_op.h"
-#include "minddata/dataset/kernels/data/one_hot_op.h"
 #include "minddata/dataset/kernels/data/pad_end_op.h"
 #include "minddata/dataset/kernels/data/slice_op.h"
 #include "minddata/dataset/kernels/data/to_float16_op.h"
-#include "minddata/dataset/kernels/data/type_cast_op.h"
-#include "minddata/dataset/kernels/data/unique_op.h"
 
 namespace mindspore {
 namespace dataset {
@@ -38,15 +34,6 @@ PYBIND_REGISTER(ConcatenateOp, 1, ([](const py::module *m) {
                     .def(py::init<int8_t, std::shared_ptr<Tensor>, std::shared_ptr<Tensor>>());
                 }));
 
-PYBIND_REGISTER(
-  DuplicateOp, 1, ([](const py::module *m) {
-    (void)py::class_<DuplicateOp, TensorOp, std::shared_ptr<DuplicateOp>>(*m, "DuplicateOp").def(py::init<>());
-  }));
-
-PYBIND_REGISTER(UniqueOp, 1, ([](const py::module *m) {
-                  (void)py::class_<UniqueOp, TensorOp, std::shared_ptr<UniqueOp>>(*m, "UniqueOp").def(py::init<>());
-                }));
-
 PYBIND_REGISTER(
   FillOp, 1, ([](const py::module *m) {
     (void)py::class_<FillOp, TensorOp, std::shared_ptr<FillOp>>(*m, "FillOp").def(py::init<std::shared_ptr<Tensor>>());
@@ -57,11 +44,6 @@ PYBIND_REGISTER(MaskOp, 1, ([](const py::module *m) {
                     .def(py::init<RelationalOp, std::shared_ptr<Tensor>, DataType>());
                 }));
 
-PYBIND_REGISTER(
-  OneHotOp, 1, ([](const py::module *m) {
-    (void)py::class_<OneHotOp, TensorOp, std::shared_ptr<OneHotOp>>(*m, "OneHotOp").def(py::init<int32_t>());
-  }));
-
 PYBIND_REGISTER(PadEndOp, 1, ([](const py::module *m) {
                   (void)py::class_<PadEndOp, TensorOp, std::shared_ptr<PadEndOp>>(*m, "PadEndOp")
                     .def(py::init<TensorShape, std::shared_ptr<Tensor>>());
@@ -111,12 +93,6 @@ PYBIND_REGISTER(ToFloat16Op, 1, ([](const py::module *m) {
                     .def(py::init<>());
                 }));
 
-PYBIND_REGISTER(TypeCastOp, 1, ([](const py::module *m) {
-                  (void)py::class_<TypeCastOp, TensorOp, std::shared_ptr<TypeCastOp>>(*m, "TypeCastOp")
-                    .def(py::init<DataType>())
-                    .def(py::init<std::string>());
-                }));
-
 PYBIND_REGISTER(RelationalOp, 0, ([](const py::module *m) {
                   (void)py::enum_<RelationalOp>(*m, "RelationalOp", py::arithmetic())
                     .value("EQ", RelationalOp::kEqual)

mindspore/ccsrc/minddata/dataset/api/python/bindings/dataset/kernels/ir/bindings.cc

@@ -64,6 +64,28 @@ PYBIND_REGISTER(
       }));
   }));
 
+PYBIND_REGISTER(
+  DuplicateOperation, 1, ([](const py::module *m) {
+    (void)py::class_<transforms::DuplicateOperation, TensorOperation, std::shared_ptr<transforms::DuplicateOperation>>(
+      *m, "DuplicateOperation")
+      .def(py::init([]() {
+        auto duplicate = std::make_shared<transforms::DuplicateOperation>();
+        THROW_IF_ERROR(duplicate->ValidateParams());
+        return duplicate;
+      }));
+  }));
+
+PYBIND_REGISTER(
+  OneHotOperation, 1, ([](const py::module *m) {
+    (void)py::class_<transforms::OneHotOperation, TensorOperation, std::shared_ptr<transforms::OneHotOperation>>(
+      *m, "OneHotOperation")
+      .def(py::init([](int32_t num_classes) {
+        auto one_hot = std::make_shared<transforms::OneHotOperation>(num_classes);
+        THROW_IF_ERROR(one_hot->ValidateParams());
+        return one_hot;
+      }));
+  }));
+
 PYBIND_REGISTER(RandomChoiceOperation, 1, ([](const py::module *m) {
                   (void)py::class_<transforms::RandomChoiceOperation, TensorOperation,
                                    std::shared_ptr<transforms::RandomChoiceOperation>>(*m, "RandomChoiceOperation")
@@ -87,5 +109,28 @@ PYBIND_REGISTER(RandomApplyOperation, 1, ([](const py::module *m) {
                       return random_apply;
                     }));
                 }));
+
+PYBIND_REGISTER(
+  TypeCastOperation, 1, ([](const py::module *m) {
+    (void)py::class_<transforms::TypeCastOperation, TensorOperation, std::shared_ptr<transforms::TypeCastOperation>>(
+      *m, "TypeCastOperation")
+      .def(py::init([](std::string data_type) {
+        auto type_cast = std::make_shared<transforms::TypeCastOperation>(data_type);
+        THROW_IF_ERROR(type_cast->ValidateParams());
+        return type_cast;
+      }));
+  }));
+
+PYBIND_REGISTER(
+  UniqueOperation, 1, ([](const py::module *m) {
+    (void)py::class_<transforms::UniqueOperation, TensorOperation, std::shared_ptr<transforms::UniqueOperation>>(
+      *m, "UniqueOperation")
+      .def(py::init([]() {
+        auto unique = std::make_shared<transforms::UniqueOperation>();
+        THROW_IF_ERROR(unique->ValidateParams());
+        return unique;
+      }));
+  }));
+
 }  // namespace dataset
 }  // namespace mindspore

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

@@ -64,7 +64,7 @@ std::shared_ptr<TensorOperation> Duplicate::Parse() { return std::make_shared<Du
 // Constructor to OneHot
 struct OneHot::Data {
   explicit Data(int32_t num_classes) : num_classes_(num_classes) {}
-  float num_classes_;
+  int32_t num_classes_;
 };
 
 OneHot::OneHot(int32_t num_classes) : data_(std::make_shared<Data>(num_classes)) {}

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

@@ -351,7 +351,7 @@ class SentencePieceTokenizer final : public TensorTransform {
   /// \param[in] vocab a SentencePieceVocab object.
   /// \param[in] out_type The type of output.
   SentencePieceTokenizer(const std::shared_ptr<SentencePieceVocab> &vocab,
-                         mindspore::dataset::SPieceTokenizerOutType out_typee);
+                         mindspore::dataset::SPieceTokenizerOutType out_type);
 
   /// \brief Constructor.
   /// \param[in] vocab_path vocab model file path.
@@ -398,14 +398,14 @@ class SlidingWindow final : public TensorTransform {
 };
 
 /// \brief Tensor operation to convert every element of a string tensor to a number.
-///   Strings are casted according to the rules specified in the following links:
+///   Strings are cast according to the rules specified in the following links:
 ///   https://en.cppreference.com/w/cpp/string/basic_string/stof,
 ///   https://en.cppreference.com/w/cpp/string/basic_string/stoul,
 ///   except that any strings which represent negative numbers cannot be cast to an unsigned integer type.
 class ToNumber final : public TensorTransform {
  public:
   /// \brief Constructor.
-  /// \param[in] data_type of the tensor to be casted to. Must be a numeric type.
+  /// \param[in] data_type of the tensor to be cast to. Must be a numeric type.
   explicit ToNumber(const std::string &data_type) : ToNumber(StringToChar(data_type)) {}
 
   explicit ToNumber(const std::vector<char> &data_type);

mindspore/ccsrc/minddata/dataset/kernels/data/one_hot_op.cc

@@ -38,11 +38,5 @@ Status OneHotOp::OutputShape(const std::vector<TensorShape> &inputs, std::vector
   return Status(StatusCode::kMDUnexpectedError, "OneHot: invalid input shape.");
 }
 
-Status OneHotOp::to_json(nlohmann::json *out_json) {
-  nlohmann::json args;
-  args["num_classes"] = num_classes_;
-  *out_json = args;
-  return Status::OK();
-}
 }  // namespace dataset
 }  // namespace mindspore

mindspore/ccsrc/minddata/dataset/kernels/data/one_hot_op.h

@@ -37,8 +37,6 @@ class OneHotOp : public TensorOp {
 
   std::string Name() const override { return kOneHotOp; }
 
-  Status to_json(nlohmann::json *out_json) override;
-
  private:
   int num_classes_;
 };

mindspore/ccsrc/minddata/dataset/kernels/data/type_cast_op.cc

@@ -34,11 +34,5 @@ Status TypeCastOp::OutputType(const std::vector<DataType> &inputs, std::vector<D
   return Status::OK();
 }
 
-Status TypeCastOp::to_json(nlohmann::json *out_json) {
-  nlohmann::json args;
-  args["data_type"] = type_.ToString();
-  *out_json = args;
-  return Status::OK();
-}
 }  // namespace dataset
 }  // namespace mindspore

mindspore/ccsrc/minddata/dataset/kernels/data/type_cast_op.h

@@ -43,8 +43,6 @@ class TypeCastOp : public TensorOp {
 
   std::string Name() const override { return kTypeCastOp; }
 
-  Status to_json(nlohmann::json *out_json) override;
-
  private:
   DataType type_;
 };

mindspore/ccsrc/minddata/dataset/kernels/ir/data/transforms_ir.cc

@@ -78,6 +78,13 @@ Status OneHotOperation::ValidateParams() {
 
 std::shared_ptr<TensorOp> OneHotOperation::Build() { return std::make_shared<OneHotOp>(num_classes_); }
 
+Status OneHotOperation::to_json(nlohmann::json *out_json) {
+  nlohmann::json args;
+  args["num_classes"] = num_classes_;
+  *out_json = args;
+  return Status::OK();
+}
+
 // PreBuiltOperation
 PreBuiltOperation::PreBuiltOperation(std::shared_ptr<TensorOp> tensor_op) : op_(tensor_op) {
 #ifdef ENABLE_PYTHON
@@ -149,6 +156,13 @@ Status TypeCastOperation::ValidateParams() {
 
 std::shared_ptr<TensorOp> TypeCastOperation::Build() { return std::make_shared<TypeCastOp>(data_type_); }
 
+Status TypeCastOperation::to_json(nlohmann::json *out_json) {
+  nlohmann::json args;
+  args["data_type"] = data_type_;
+  *out_json = args;
+  return Status::OK();
+}
+
 #ifndef ENABLE_ANDROID
 // UniqueOperation
 Status UniqueOperation::ValidateParams() { return Status::OK(); }

mindspore/ccsrc/minddata/dataset/kernels/ir/data/transforms_ir.h

@@ -81,8 +81,10 @@ class OneHotOperation : public TensorOperation {
 
   std::string Name() const override { return kOneHotOperation; }
 
+  Status to_json(nlohmann::json *out_json) override;
+
  private:
-  float num_classes_;
+  int32_t num_classes_;
 };
 
 class PreBuiltOperation : public TensorOperation {
@@ -147,6 +149,8 @@ class TypeCastOperation : public TensorOperation {
 
   std::string Name() const override { return kTypeCastOperation; }
 
+  Status to_json(nlohmann::json *out_json) override;
+
  private:
   std::string data_type_;
 };

mindspore/dataset/engine/serializer_deserializer.py

@@ -362,8 +362,7 @@ def construct_tensor_ops(operations):
 
         if hasattr(op_module_vis, op_name):
             op_class = getattr(op_module_vis, op_name, None)
-        elif hasattr(op_module_trans, op_name[:-2]):
-            op_name = op_name[:-2]  # to remove op from the back of the name
+        elif hasattr(op_module_trans, op_name):
             op_class = getattr(op_module_trans, op_name, None)
         else:
             raise RuntimeError(op_name + " is not yet supported by deserialize().")

mindspore/dataset/text/transforms.py

@@ -387,18 +387,18 @@ class ToNumber(TextTensorOperation):
     """
     Tensor operation to convert every element of a string tensor to a number.
 
-    Strings are casted according to the rules specified in the following links:
+    Strings are cast according to the rules specified in the following links:
     https://en.cppreference.com/w/cpp/string/basic_string/stof,
     https://en.cppreference.com/w/cpp/string/basic_string/stoul,
     except that any strings which represent negative numbers cannot be cast to an
     unsigned integer type.
 
     Args:
-        data_type (mindspore.dtype): mindspore.dtype to be casted to. Must be
+        data_type (mindspore.dtype): mindspore.dtype to be cast to. Must be
             a numeric type.
 
     Raises:
-        RuntimeError: If strings are invalid to cast, or are out of range after being casted.
+        RuntimeError: If strings are invalid to cast, or are out of range after being cast.
 
     Examples:
         >>> import mindspore.common.dtype as mstype

mindspore/dataset/transforms/c_transforms.py

@@ -21,7 +21,7 @@ import numpy as np
 import mindspore.common.dtype as mstype
 import mindspore._c_dataengine as cde
 
-from .validators import check_num_classes, check_de_type, check_fill_value, check_slice_option, check_slice_op, \
+from .validators import check_num_classes, check_ms_type, check_fill_value, check_slice_option, check_slice_op, \
     check_mask_op, check_pad_end, check_concat_type, check_random_transform_ops
 from ..core.datatypes import mstype_to_detype
 
@@ -52,7 +52,7 @@ class TensorOperation:
         raise NotImplementedError("TensorOperation has to implement parse() method.")
 
 
-class OneHot(cde.OneHotOp):
+class OneHot(TensorOperation):
     """
     Tensor operation to apply one hot encoding.
 
@@ -72,7 +72,9 @@ class OneHot(cde.OneHotOp):
     @check_num_classes
     def __init__(self, num_classes):
         self.num_classes = num_classes
-        super().__init__(num_classes)
+
+    def parse(self):
+        return cde.OneHotOperation(self.num_classes)
 
 
 class Fill(cde.FillOp):
@@ -102,7 +104,7 @@ class Fill(cde.FillOp):
         super().__init__(cde.Tensor(np.array(fill_value)))
 
 
-class TypeCast(cde.TypeCastOp):
+class TypeCast(TensorOperation):
     """
     Tensor operation to cast to a given MindSpore data type.
 
@@ -123,11 +125,13 @@ class TypeCast(cde.TypeCastOp):
         >>> dataset = dataset.map(operations=type_cast_op)
     """
 
-    @check_de_type
+    @check_ms_type
     def __init__(self, data_type):
         data_type = mstype_to_detype(data_type)
         self.data_type = str(data_type)
-        super().__init__(data_type)
+
+    def parse(self):
+        return cde.TypeCastOperation(self.data_type)
 
 
 class _SliceOption(cde.SliceOption):
@@ -314,7 +318,7 @@ class Concatenate(cde.ConcatenateOp):
         super().__init__(axis, prepend, append)
 
 
-class Duplicate(cde.DuplicateOp):
+class Duplicate(TensorOperation):
     """
     Duplicate the input tensor to output, only support transform one column each time.
 
@@ -337,8 +341,11 @@ class Duplicate(cde.DuplicateOp):
         >>> # +---------+---------+
     """
 
+    def parse(self):
+        return cde.DuplicateOperation()
+
 
-class Unique(cde.UniqueOp):
+class Unique(TensorOperation):
     """
     Perform the unique operation on the input tensor, only support transform one column each time.
 
@@ -373,9 +380,11 @@ class Unique(cde.UniqueOp):
         >>> # +---------+-----------------+---------+
 
     """
+    def parse(self):
+        return cde.UniqueOperation()
 
 
-class Compose():
+class Compose(TensorOperation):
     """
     Compose a list of transforms into a single transform.
 
@@ -401,7 +410,7 @@ class Compose():
         return cde.ComposeOperation(operations)
 
 
-class RandomApply():
+class RandomApply(TensorOperation):
     """
     Randomly perform a series of transforms with a given probability.
 
@@ -429,7 +438,7 @@ class RandomApply():
         return cde.RandomApplyOperation(self.prob, operations)
 
 
-class RandomChoice():
+class RandomChoice(TensorOperation):
     """
     Randomly select one transform from a list of transforms to perform operation.
 

mindspore/dataset/transforms/validators.py

@@ -87,7 +87,7 @@ def check_num_classes(method):
     return new_method
 
 
-def check_de_type(method):
+def check_ms_type(method):
     """Wrapper method to check the parameters of data type."""
 
     @wraps(method)