Support resource manager scoped Sentencepiece resources.

PiperOrigin-RevId: 596019271

tensorflow_text/python/ops/sentencepiece_tokenizer.py

@@ -19,6 +19,8 @@
 from __future__ import division
 from __future__ import print_function
 
+import uuid
+
 from tensorflow.python.eager import monitoring
 from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import ops
@@ -43,16 +45,24 @@
 class _SentencepieceModelResource(resource.TrackableResource):
   """Utility to track the model resource tensor (for SavedModel support)."""
 
-  def __init__(self, model, name):
+  def __init__(self, model, name, use_unique_shared_resource_name):
     super(_SentencepieceModelResource, self).__init__()
     self._model = model
     self._name = name
+    self._use_unique_shared_resource_name = use_unique_shared_resource_name
     _ = self.resource_handle  # Accessing this property creates the resource.
 
   def _create_resource(self):
     model, name = self._model, self._name
     with ops.name_scope(name, "SentenceTokenizerInitializer", [model]):
-      return gen_sentencepiece_tokenizer.sentencepiece_op(model=model)
+      # TODO(b/318839908): Switch to ref-counted resources and remove this.
+      shared_name = ""
+      if self._use_unique_shared_resource_name:
+        shared_name = str(uuid.uuid4())
+      return gen_sentencepiece_tokenizer.sentencepiece_op(
+          model=model,
+          shared_name=shared_name,
+      )
 
 
 class SentencepieceTokenizer(TokenizerWithOffsets, Detokenizer):
@@ -79,7 +89,8 @@ def __init__(self,
                add_bos=False,
                add_eos=False,
                return_nbest=False,
-               name=None):
+               name=None,
+               use_unique_shared_resource_name=False):
     """Creates & initializes a Sentencepiece processor.
 
     Args:
@@ -104,6 +115,10 @@ def __init__(self,
         of a single one. The returned tensor has shape
         `[batch * nbest, (tokens)]`.
       name: The name argument that is passed to the op function.
+      use_unique_shared_resource_name: Whether to set a unique `shared_name` for
+        the Sentencepiece resource. This is useful for allowing the resource to
+        outlive the kernel that created it in eager mode. The resource's
+        lifetime will instead be tied to the eager context.
 
     Returns:
       pieces: A SentencepieceTokenizer.
@@ -117,7 +132,8 @@ def __init__(self,
     self.add_bos = add_bos
     self.add_eos = add_eos
     self.return_nbest = return_nbest
-    self._model_resource = _SentencepieceModelResource(model, name)
+    self._model_resource = _SentencepieceModelResource(
+        model, name, use_unique_shared_resource_name)
 
   def tokenize(self, input, name=None):  # pylint: disable=redefined-builtin
     """Tokenizes a tensor of UTF-8 strings.

tensorflow_text/python/ops/sentencepiece_tokenizer_test.py

@@ -485,11 +485,15 @@ def testSavedModel(self):
     self.assertAllEqual(restored_model.tokenize(inputs), expected_result)
     file_io.delete_recursively(temp_dir)
 
-  def testBasicPipeline(self):
+  @parameterized.parameters([True, False])
+  def testBasicPipeline(self, use_unique_shared_resource_name):
     if not context.executing_eagerly():
       self.skipTest('testBasicPipeline only supported in eager mode.')
 
-    sp = SentencepieceTokenizer(self.model)
+    sp = SentencepieceTokenizer(
+        self.model,
+        use_unique_shared_resource_name=use_unique_shared_resource_name,
+    )
 
     strings = ['hello', 'world']
     dataset = dataset_ops.Dataset.from_tensor_slices(strings)