Add UnicodeCharTokenizer for nlp

mindspore/ccsrc/dataset/CMakeLists.txt

@@ -61,7 +61,7 @@ set(submodules
     $<TARGET_OBJECTS:kernels>
     $<TARGET_OBJECTS:kernels-image>
     $<TARGET_OBJECTS:kernels-data>
-    $<TARGET_OBJECTS:kernels-nlp>
+    $<TARGET_OBJECTS:kernels-text>
     $<TARGET_OBJECTS:APItoPython>
     $<TARGET_OBJECTS:engine-datasetops-source>
     $<TARGET_OBJECTS:engine-datasetops-source-sampler>

mindspore/ccsrc/dataset/api/python_bindings.cc

@@ -39,6 +39,7 @@
 #include "dataset/kernels/image/uniform_aug_op.h"
 #include "dataset/kernels/data/type_cast_op.h"
 #include "dataset/kernels/text/jieba_tokenizer_op.h"
+#include "dataset/kernels/text/unicode_char_tokenizer_op.h"
 #include "dataset/engine/datasetops/source/cifar_op.h"
 #include "dataset/engine/datasetops/source/image_folder_op.h"
 #include "dataset/engine/datasetops/source/io_block.h"
@@ -407,12 +408,16 @@ void bindTensorOps4(py::module *m) {
          py::arg("fillR") = PadOp::kDefFillR, py::arg("fillG") = PadOp::kDefFillG, py::arg("fillB") = PadOp::kDefFillB);
 }
 
-void bindTensorOps6(py::module *m) {
+void bindTensorOps5(py::module *m) {
   (void)py::class_<JiebaTokenizerOp, TensorOp, std::shared_ptr<JiebaTokenizerOp>>(*m, "JiebaTokenizerOp", "")
     .def(py::init<const std::string, std::string, JiebaMode>(), py::arg("hmm_path"), py::arg("mp_path"),
          py::arg("mode") = JiebaMode::kMix)
     .def("add_word",
          [](JiebaTokenizerOp &self, const std::string word, int freq) { THROW_IF_ERROR(self.AddWord(word, freq)); });
+
+  (void)py::class_<UnicodeCharTokenizerOp, TensorOp, std::shared_ptr<UnicodeCharTokenizerOp>>(
+    *m, "UnicodeCharTokenizerOp", "Tokenize a scalar tensor of UTF-8 string to Unicode characters.")
+    .def(py::init<>());
 }
 
 void bindSamplerOps(py::module *m) {
@@ -534,7 +539,7 @@ PYBIND11_MODULE(_c_dataengine, m) {
   bindTensorOps2(&m);
   bindTensorOps3(&m);
   bindTensorOps4(&m);
-  bindTensorOps6(&m);
+  bindTensorOps5(&m);
   bindSamplerOps(&m);
   bindDatasetOps(&m);
   bindInfoObjects(&m);

mindspore/ccsrc/dataset/kernels/text/CMakeLists.txt

@@ -1,5 +1,6 @@
 file(GLOB_RECURSE _CURRENT_SRC_FILES RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "*.cc")
 set_property(SOURCE ${_CURRENT_SRC_FILES} PROPERTY COMPILE_DEFINITIONS SUBMODULE_ID=mindspore::SubModuleId::SM_MD)
-add_library(kernels-nlp OBJECT
+add_library(kernels-text OBJECT
     jieba_tokenizer_op.cc
+    unicode_char_tokenizer_op.cc
 )

mindspore/ccsrc/dataset/kernels/text/jieba_tokenizer_op.h

@@ -13,8 +13,8 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
-#ifndef DATASET_ENGINE_NLP_JIEBA_OP_H_
+#ifndef DATASET_ENGINE_TEXT_JIEBA_OP_H_
-#define DATASET_ENGINE_NLP_JIEBA_OP_H_
+#define DATASET_ENGINE_TEXT_JIEBA_OP_H_
 
 #include <string>
 #include <memory>
@@ -61,4 +61,4 @@ class JiebaTokenizerOp : public TensorOp {
 };
 }  // namespace dataset
 }  // namespace mindspore
-#endif  // DATASET_ENGINE_NLP_JIEBA_OP_H_
+#endif  // DATASET_ENGINE_TEXT_JIEBA_OP_H_

mindspore/ccsrc/dataset/kernels/text/unicode_char_tokenizer_op.cc

@@ -0,0 +1,52 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "dataset/kernels/text/unicode_char_tokenizer_op.h"
+#include <memory>
+#include <string>
+#include <string_view>
+#include <vector>
+
+#include "cppjieba/Unicode.hpp"
+
+using cppjieba::DecodeRunesInString;
+using cppjieba::RuneStrArray;
+
+namespace mindspore {
+namespace dataset {
+
+Status UnicodeCharTokenizerOp::Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) {
+  if (input->Rank() != 0 || input->type() != DataType::DE_STRING) {
+    RETURN_STATUS_UNEXPECTED("The input tensor should be scalar string tensor");
+  }
+  std::string_view str;
+  RETURN_IF_NOT_OK(input->GetItemAt(&str, {}));
+
+  RuneStrArray runes;
+  if (!DecodeRunesInString(str.data(), str.size(), runes)) {
+    RETURN_STATUS_UNEXPECTED("Decode utf8 string failed.");
+  }
+  std::vector<std::string> splits(runes.size());
+  for (size_t i = 0; i < runes.size(); i++) {
+    splits[i] = str.substr(runes[i].offset, runes[i].len);
+  }
+  if (splits.empty()) {
+    splits.emplace_back("");
+  }
+  *output = std::make_shared<Tensor>(splits, TensorShape({(dsize_t)splits.size()}));
+  return Status::OK();
+}
+}  // namespace dataset
+}  // namespace mindspore

mindspore/ccsrc/dataset/kernels/text/unicode_char_tokenizer_op.h

@@ -0,0 +1,40 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef DATASET_KERNELS_TEXT_UNICODE_CHAR_TOKENIZER_OP_H_
+#define DATASET_KERNELS_TEXT_UNICODE_CHAR_TOKENIZER_OP_H_
+#include <memory>
+
+#include "dataset/core/tensor.h"
+#include "dataset/kernels/tensor_op.h"
+#include "dataset/util/status.h"
+
+namespace mindspore {
+namespace dataset {
+
+class UnicodeCharTokenizerOp : public TensorOp {
+ public:
+  UnicodeCharTokenizerOp() {}
+
+  ~UnicodeCharTokenizerOp() override = default;
+
+  void Print(std::ostream &out) const override { out << "UnicodeCharTokenizerOp"; }
+
+  Status Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) override;
+};
+
+}  // namespace dataset
+}  // namespace mindspore
+#endif  // DATASET_KERNELS_TEXT_UNICODE_CHAR_TOKENIZER_OP_H_

mindspore/dataset/engine/datasets.py

@@ -284,10 +284,10 @@ class Dataset:
 
         Examples:
             >>> import mindspore.dataset as ds
-            >>> import mindspore.dataset.transforms.nlp.utils as nlp
+            >>> import mindspore.dataset.transforms.text.utils as text
             >>> # declare a function which returns a Dataset object
             >>> def flat_map_func(x):
-            >>>     data_dir = nlp.as_text(x[0])
+            >>>     data_dir = text.as_text(x[0])
             >>>     d = ds.ImageFolderDatasetV2(data_dir)
             >>>     return d
             >>> # data is a Dataset object

mindspore/dataset/transforms/text/__init__.py

@@ -18,3 +18,4 @@ image augmentation module which is developed with c++ opencv. Py_transforms
 provide more kinds of image augmentations which is developed with python PIL.
 """
 from .utils import as_text, JiebaMode
+from . import c_transforms

mindspore/dataset/transforms/text/c_transforms.py

@@ -123,3 +123,9 @@ class JiebaTokenizer(cde.JiebaTokenizerOp):
         if not os.path.exists(model_path):
             raise ValueError(
                 " jieba mode file {} is not exist".format(model_path))
+
+
+class UnicodeCharTokenizer(cde.UnicodeCharTokenizerOp):
+    """
+    Tokenize a scalar tensor of UTF-8 string to Unicode characters.
+    """

mindspore/dataset/transforms/text/utils.py

@@ -33,9 +33,7 @@ def as_text(array, encoding='utf8'):
     if not isinstance(array, np.ndarray):
         raise ValueError('input should be a numpy array')
 
-    def decode(x):
+    decode = np.vectorize(lambda x: x.decode(encoding))
-        return x.decode(encoding)
-    decode = np.vectorize(decode)
     return decode(array)
 
 

tests/ut/cpp/dataset/CMakeLists.txt

@@ -69,6 +69,7 @@ SET(DE_UT_SRCS
     filter_op_test.cc
     concat_op_test.cc
     jieba_tokenizer_op_test.cc
+    tokenizer_op_test.cc
     )
 
 add_executable(de_ut_tests ${DE_UT_SRCS})

tests/ut/cpp/dataset/tokenizer_op_test.cc

@@ -0,0 +1,107 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <memory>
+#include <string>
+#include <string_view>
+
+#include "common/common.h"
+#include "dataset/kernels/text/unicode_char_tokenizer_op.h"
+#include "gtest/gtest.h"
+#include "utils/log_adapter.h"
+
+using namespace mindspore::dataset;
+
+class MindDataTestTokenizerOp : public UT::Common {
+ public:
+  void CheckEqual(const std::shared_ptr<Tensor> &o,
+                  const std::vector<dsize_t> &index,
+                  const std::string &expect) {
+    std::string_view str;
+    Status s = o->GetItemAt(&str, index);
+    EXPECT_TRUE(s.IsOk());
+    EXPECT_EQ(str, expect);
+  }
+};
+
+TEST_F(MindDataTestTokenizerOp, TestUnicodeCharTokenizerOp) {
+  MS_LOG(INFO) << "Doing TestUnicodeCharTokenizerOp.";
+  std::unique_ptr<UnicodeCharTokenizerOp> op(new UnicodeCharTokenizerOp());
+  std::shared_ptr<Tensor> input = std::make_shared<Tensor>("Hello World!");
+  std::shared_ptr<Tensor> output;
+  Status s = op->Compute(input, &output);
+  EXPECT_TRUE(s.IsOk());
+  EXPECT_EQ(output->Size(), 12);
+  EXPECT_EQ(output->Rank(), 1);
+  MS_LOG(INFO) << "Out tensor1: " << output->ToString();
+  CheckEqual(output, {0}, "H");
+  CheckEqual(output, {1}, "e");
+  CheckEqual(output, {2}, "l");
+  CheckEqual(output, {3}, "l");
+  CheckEqual(output, {4}, "o");
+  CheckEqual(output, {5}, " ");
+  CheckEqual(output, {6}, "W");
+  CheckEqual(output, {7}, "o");
+  CheckEqual(output, {8}, "r");
+  CheckEqual(output, {9}, "l");
+  CheckEqual(output, {10}, "d");
+  CheckEqual(output, {11}, "!");
+
+  input = std::make_shared<Tensor>("中国 你好!");
+  s = op->Compute(input, &output);
+  EXPECT_TRUE(s.IsOk());
+  EXPECT_EQ(output->Size(), 6);
+  EXPECT_EQ(output->Rank(), 1);
+  MS_LOG(INFO) << "Out tensor2: " << output->ToString();
+  CheckEqual(output, {0}, "中");
+  CheckEqual(output, {1}, "国");
+  CheckEqual(output, {2}, " ");
+  CheckEqual(output, {3}, "你");
+  CheckEqual(output, {4}, "好");
+  CheckEqual(output, {5}, "!");
+
+  input = std::make_shared<Tensor>("中");
+  s = op->Compute(input, &output);
+  EXPECT_TRUE(s.IsOk());
+  EXPECT_EQ(output->Size(), 1);
+  EXPECT_EQ(output->Rank(), 1);
+  MS_LOG(INFO) << "Out tensor3: " << output->ToString();
+  CheckEqual(output, {0}, "中");
+
+  input = std::make_shared<Tensor>("H");
+  s = op->Compute(input, &output);
+  EXPECT_TRUE(s.IsOk());
+  EXPECT_EQ(output->Size(), 1);
+  EXPECT_EQ(output->Rank(), 1);
+  MS_LOG(INFO) << "Out tensor4: " << output->ToString();
+  CheckEqual(output, {0}, "H");
+
+  input = std::make_shared<Tensor>("  ");
+  s = op->Compute(input, &output);
+  EXPECT_TRUE(s.IsOk());
+  EXPECT_EQ(output->Size(), 2);
+  EXPECT_EQ(output->Rank(), 1);
+  MS_LOG(INFO) << "Out tensor5: " << output->ToString();
+  CheckEqual(output, {0}, " ");
+  CheckEqual(output, {1}, " ");
+
+  input = std::make_shared<Tensor>("");
+  s = op->Compute(input, &output);
+  EXPECT_TRUE(s.IsOk());
+  EXPECT_EQ(output->Size(), 1);
+  EXPECT_EQ(output->Rank(), 1);
+  MS_LOG(INFO) << "Out tensor6: " << output->ToString();
+  CheckEqual(output, {0}, "");
+}

tests/ut/data/dataset/testTokenizerData/1.txt

@@ -0,0 +1,4 @@
+Welcome to Beijing!
+北京欢迎您！
+我喜欢English!
+  

tests/ut/python/dataset/test_tokenizer.py

@@ -0,0 +1,53 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""
+Testing UnicodeCharTokenizer op in DE
+"""
+import mindspore.dataset as ds
+from mindspore import log as logger
+import mindspore.dataset.transforms.text.c_transforms as nlp
+import mindspore.dataset.transforms.text.utils as nlp_util
+
+DATA_FILE = "../data/dataset/testTokenizerData/1.txt"
+
+
+def split_by_unicode_char(input_strs):
+    """
+    Split utf-8 strings to unicode characters
+    """
+    out = []
+    for s in input_strs:
+        out.append([c for c in s])
+    return out
+
+
+def test_unicode_char_tokenizer():
+    """
+    Test UnicodeCharTokenizer
+    """
+    input_strs = ("Welcome to Beijing!", "北京欢迎您！", "我喜欢English!", "  ")
+    dataset = ds.TextFileDataset(DATA_FILE, shuffle=False)
+    tokenizer = nlp.UnicodeCharTokenizer()
+    dataset = dataset.map(operations=tokenizer)
+    tokens = []
+    for i in dataset.create_dict_iterator():
+        text = nlp_util.as_text(i['text']).tolist()
+        tokens.append(text)
+    logger.info("The out tokens is : {}".format(tokens))
+    assert split_by_unicode_char(input_strs) == tokens
+
+
+if __name__ == '__main__':
+    test_unicode_char_tokenizer()