change output of WordpieceTokenizer and BertTokenizer to 1-D string tensors

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

@@ -32,23 +32,6 @@ WordpieceTokenizerOp::WordpieceTokenizerOp(const std::shared_ptr<Vocab> &vocab,
       max_bytes_per_token_(max_bytes_per_token),
       unknown_token_(unknown_token) {}
 
-void WordpieceTokenizerOp::PadTokens(const std::vector<std::vector<std::string>> &tokens, const std::string &padded_str,
-                                     std::vector<std::string> *out_padded_tokens, int *out_cols) const {
-  int rows = tokens.size();
-  int max_cols = 0;
-  for (int i = 0; i < rows; i++) {
-    max_cols = std::max(max_cols, static_cast<int>(tokens[i].size()));
-  }
-  out_padded_tokens->resize(rows * max_cols, padded_str);
-  for (int i = 0; i < rows; i++) {
-    int index = i * max_cols;
-    for (int j = 0; j < tokens[i].size(); j++) {
-      (*out_padded_tokens)[index++] = tokens[i][j];
-    }
-  }
-  *out_cols = max_cols;
-}
-
 Status WordpieceTokenizerOp::LookupWord(const std::string &input_token, const RuneStrArray &runes, const int start,
                                         bool *out_found, int *out_end) const {
   CHECK_FAIL_RETURN_UNEXPECTED(start >= 0 && start < input_token.size(), "Out of range");
@@ -117,20 +100,16 @@ Status WordpieceTokenizerOp::Compute(const std::shared_ptr<Tensor> &input, std::
   if (input->Rank() > 1 || input->type() != DataType::DE_STRING) {
     RETURN_STATUS_UNEXPECTED("The input tensor should be scalar or 1-D string tensor");
   }
-  std::vector<std::vector<std::string>> out_tokens(input->Size());
-  int i = 0;
+  std::vector<std::string> out_tokens;
   for (auto iter = input->begin<std::string_view>(); iter != input->end<std::string_view>(); iter++) {
-    RETURN_IF_NOT_OK(GetTokens(std::string(*iter), &out_tokens[i++]));
+    std::vector<std::string> temp_tokens;
+    RETURN_IF_NOT_OK(GetTokens(std::string(*iter), &temp_tokens));
+    out_tokens.insert(out_tokens.end(), temp_tokens.begin(), temp_tokens.end());
   }
-  std::vector<std::string> padded_tokens;
-  int cols = 0;
-  PadTokens(out_tokens, "<pad>", &padded_tokens, &cols);
-  std::vector<dsize_t> shapes;
-  if (input->Rank() == 1) {
-    shapes.push_back(out_tokens.size());
+  if (out_tokens.empty()) {
+    out_tokens.emplace_back("");
   }
-  shapes.push_back(cols);
-  *output = std::make_shared<Tensor>(std::move(padded_tokens), TensorShape(shapes));
+  *output = std::make_shared<Tensor>(out_tokens, TensorShape({(dsize_t)out_tokens.size()}));
   return Status::OK();
 }
 

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

@@ -48,8 +48,6 @@ class WordpieceTokenizerOp : public TensorOp {
   Status Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) override;
 
  protected:
-  void PadTokens(const std::vector<std::vector<std::string>> &tokens, const std::string &padded_str,
-                 std::vector<std::string> *out_padded_tokens, int *out_cols) const;
   Status AddSubword(const std::string &input_token, const int start, const int end,
                     std::vector<std::string> *out_token) const;
   Status FoundNoToken(const std::string &input_token, std::vector<std::string> *out_tokens) const;

mindspore/dataset/text/transforms.py

@@ -188,7 +188,7 @@ class UnicodeCharTokenizer(cde.UnicodeCharTokenizerOp):
 
 class WordpieceTokenizer(cde.WordpieceTokenizerOp):
     """
-    Tokenize scalar token or 1-D tokens to subword tokens.
+    Tokenize scalar token or 1-D tokens to 1-D subword tokens.
 
     Args
         vocab(Vocab): a Vocab object.

tests/ut/python/dataset/test_bert_tokenizer.py

@@ -35,38 +35,24 @@ test_paras = [
     dict(
         first=1,
         last=4,
-        expect_str=[[['床'], ['前'], ['明'], ['月'], ['光']],
-                    [['疑'], ['是'], ['地'], ['上'], ['霜']],
-                    [['举'], ['头'], ['望'], ['明'], ['月']],
-                    [['低'], ['头'], ['思'], ['故'], ['乡']]],
+        expect_str=[['床', '前', '明', '月', '光'],
+                    ['疑', '是', '地', '上', '霜'],
+                    ['举', '头', '望', '明', '月'],
+                    ['低', '头', '思', '故', '乡']],
         vocab_list=vocab_bert
     ),
     # test english text
     dict(
         first=5,
         last=5,
-        expect_str=[[['i', pad],
-                     ["am", pad],
-                     ['mak', '##ing'],
-                     ['small', pad],
-                     ['mistake', '##s'],
-                     ['during', pad],
-                     ['work', '##ing'],
-                     ['hour', '##s']]],
+        expect_str=[['i', 'am', 'mak', '##ing', 'small', 'mistake', '##s', 'during', 'work', '##ing', 'hour', '##s']],
         lower_case=True,
         vocab_list=vocab_bert
     ),
     dict(
         first=5,
         last=5,
-        expect_str=[[['I', pad],
-                     ["am", pad],
-                     ['mak', '##ing'],
-                     ['small', pad],
-                     ['mistake', '##s'],
-                     ['during', pad],
-                     ['work', '##ing'],
-                     ['hour', '##s']]],
+        expect_str=[['I', "am", 'mak', '##ing', 'small', 'mistake', '##s', 'during', 'work', '##ing', 'hour', '##s']],
         lower_case=False,
         vocab_list=vocab_bert
     ),
@@ -75,8 +61,8 @@ test_paras = [
         first=6,
         last=7,
         expect_str=[
-            [['😀'], ['嘿'], ['嘿'], ['😃'], ['哈'], ['哈'], ['😄'], ['大'], ['笑'], ['😁'], ['嘻'], ['嘻']],
-            [['繁'], ['體'], ['字']]],
+            ['😀', '嘿', '嘿', '😃', '哈', '哈', '😄', '大', '笑', '😁', '嘻', '嘻'],
+            ['繁', '體', '字']],
         normalization_form=nlp.utils.NormalizeForm.NFKC,
         vocab_list=vocab_bert
     ),
@@ -85,11 +71,11 @@ test_paras = [
         first=8,
         last=12,
         expect_str=[
-            [['[UNK]'], ['[CLS]']],
-            [['[UNK]'], ['[SEP]']],
-            [['[UNK]'], ['[UNK]']],
-            [['[UNK]'], ['[PAD]']],
-            [['[UNK]'], ['[MASK]']],
+            ['[UNK]', '[CLS]'],
+            ['[UNK]', '[SEP]'],
+            ['[UNK]', '[UNK]'],
+            ['[UNK]', '[PAD]'],
+            ['[UNK]', '[MASK]'],
         ],
         lower_case=False,
         vocab_list=vocab_bert,
@@ -99,7 +85,7 @@ test_paras = [
     dict(
         first=13,
         last=13,
-        expect_str=[[['12'], ['+'], ['/'], ['-'], ['28'], ['='], ['40'], ['/'], ['-'], ['16']]],
+        expect_str=[['12', '+', '/', '-', '28', '=', '40', '/', '-', '16']],
         preserve_unused_token=True,
         vocab_list=vocab_bert
     ),
@@ -107,9 +93,7 @@ test_paras = [
     dict(
         first=8,
         last=8,
-        expect_str=[
-            [['[UNK]'], [' '], ['[CLS]']],
-        ],
+        expect_str=[['[UNK]', ' ', '[CLS]']],
         lower_case=False,
         vocab_list=vocab_bert,
         preserve_unused_token=True,
@@ -118,9 +102,7 @@ test_paras = [
     dict(
         first=8,
         last=8,
-        expect_str=[
-            [['unused'], [' '], ['[CLS]']],
-        ],
+        expect_str=[['unused', ' ', '[CLS]']],
         lower_case=False,
         vocab_list=vocab_bert,
         preserve_unused_token=True,
@@ -130,9 +112,7 @@ test_paras = [
     dict(
         first=8,
         last=8,
-        expect_str=[
-            [['unused'], [' '], ['['], ['CLS'], [']']],
-        ],
+        expect_str=[['unused', ' ', '[', 'CLS', ']']],
         lower_case=False,
         vocab_list=vocab_bert,
         preserve_unused_token=False,