Merge pull request #3820 from kinaryml:text-classifier-python

PiperOrigin-RevId: 486566800

mediapipe/python/BUILD

@@ -87,6 +87,7 @@ cc_library(
 cc_library(
     name = "builtin_task_graphs",
     deps = [
+        "//mediapipe/tasks/cc/text/text_classifier:text_classifier_graph",
         "//mediapipe/tasks/cc/vision/gesture_recognizer:gesture_recognizer_graph",
         "//mediapipe/tasks/cc/vision/image_classifier:image_classifier_graph",
         "//mediapipe/tasks/cc/vision/image_segmenter:image_segmenter_graph",

mediapipe/tasks/python/test/test_utils.py

@@ -157,7 +157,7 @@ def _normalize_number_fields(pb):
                        descriptor.FieldDescriptor.TYPE_ENUM):
       normalized_values = [int(x) for x in values]
     elif desc.type == descriptor.FieldDescriptor.TYPE_FLOAT:
-      normalized_values = [round(x, 5) for x in values]
+      normalized_values = [round(x, 4) for x in values]
     elif desc.type == descriptor.FieldDescriptor.TYPE_DOUBLE:
       normalized_values = [round(float(x), 6) for x in values]
 

mediapipe/tasks/python/test/text/BUILD

@@ -0,0 +1,36 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.
+
+# Placeholder for internal Python strict test compatibility macro.
+
+package(default_visibility = ["//mediapipe/tasks:internal"])
+
+licenses(["notice"])
+
+py_test(
+    name = "text_classifier_test",
+    srcs = ["text_classifier_test.py"],
+    data = [
+        "//mediapipe/tasks/testdata/text:bert_text_classifier_models",
+        "//mediapipe/tasks/testdata/text:text_classifier_models",
+    ],
+    deps = [
+        "//mediapipe/tasks/python/components/containers:category",
+        "//mediapipe/tasks/python/components/containers:classifications",
+        "//mediapipe/tasks/python/components/processors:classifier_options",
+        "//mediapipe/tasks/python/core:base_options",
+        "//mediapipe/tasks/python/test:test_utils",
+        "//mediapipe/tasks/python/text:text_classifier",
+    ],
+)

mediapipe/tasks/python/test/text/__init__.py

@@ -0,0 +1,13 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.

mediapipe/tasks/python/test/text/text_classifier_test.py

@@ -0,0 +1,244 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.
+"""Tests for text classifier."""
+
+import enum
+import os
+
+from absl.testing import absltest
+from absl.testing import parameterized
+
+from mediapipe.tasks.python.components.containers import category
+from mediapipe.tasks.python.components.containers import classifications as classifications_module
+from mediapipe.tasks.python.components.processors import classifier_options
+from mediapipe.tasks.python.core import base_options as base_options_module
+from mediapipe.tasks.python.test import test_utils
+from mediapipe.tasks.python.text import text_classifier
+
+_BaseOptions = base_options_module.BaseOptions
+_ClassifierOptions = classifier_options.ClassifierOptions
+_Category = category.Category
+_ClassificationEntry = classifications_module.ClassificationEntry
+_Classifications = classifications_module.Classifications
+_TextClassificationResult = classifications_module.ClassificationResult
+_TextClassifier = text_classifier.TextClassifier
+_TextClassifierOptions = text_classifier.TextClassifierOptions
+
+_BERT_MODEL_FILE = 'bert_text_classifier.tflite'
+_REGEX_MODEL_FILE = 'test_model_text_classifier_with_regex_tokenizer.tflite'
+_TEST_DATA_DIR = 'mediapipe/tasks/testdata/text'
+
+_NEGATIVE_TEXT = 'What a waste of my time.'
+_POSITIVE_TEXT = ('This is the best movie I’ve seen in recent years.'
+                  'Strongly recommend it!')
+
+_BERT_NEGATIVE_RESULTS = _TextClassificationResult(classifications=[
+    _Classifications(
+        entries=[
+            _ClassificationEntry(
+                categories=[
+                    _Category(
+                        index=0,
+                        score=0.999479,
+                        display_name='',
+                        category_name='negative'),
+                    _Category(
+                        index=1,
+                        score=0.00052154,
+                        display_name='',
+                        category_name='positive')
+                ],
+                timestamp_ms=0)
+        ],
+        head_index=0,
+        head_name='probability')
+])
+_BERT_POSITIVE_RESULTS = _TextClassificationResult(classifications=[
+    _Classifications(
+        entries=[
+            _ClassificationEntry(
+                categories=[
+                    _Category(
+                        index=1,
+                        score=0.999466,
+                        display_name='',
+                        category_name='positive'),
+                    _Category(
+                        index=0,
+                        score=0.000533596,
+                        display_name='',
+                        category_name='negative')
+                ],
+                timestamp_ms=0)
+        ],
+        head_index=0,
+        head_name='probability')
+])
+_REGEX_NEGATIVE_RESULTS = _TextClassificationResult(classifications=[
+    _Classifications(
+        entries=[
+            _ClassificationEntry(
+                categories=[
+                    _Category(
+                        index=0,
+                        score=0.81313,
+                        display_name='',
+                        category_name='Negative'),
+                    _Category(
+                        index=1,
+                        score=0.1868704,
+                        display_name='',
+                        category_name='Positive')
+                ],
+                timestamp_ms=0)
+        ],
+        head_index=0,
+        head_name='probability')
+])
+_REGEX_POSITIVE_RESULTS = _TextClassificationResult(classifications=[
+    _Classifications(
+        entries=[
+            _ClassificationEntry(
+                categories=[
+                    _Category(
+                        index=1,
+                        score=0.5134273,
+                        display_name='',
+                        category_name='Positive'),
+                    _Category(
+                        index=0,
+                        score=0.486573,
+                        display_name='',
+                        category_name='Negative')
+                ],
+                timestamp_ms=0)
+        ],
+        head_index=0,
+        head_name='probability')
+])
+
+
+class ModelFileType(enum.Enum):
+  FILE_CONTENT = 1
+  FILE_NAME = 2
+
+
+class ImageClassifierTest(parameterized.TestCase):
+
+  def setUp(self):
+    super().setUp()
+    self.model_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, _BERT_MODEL_FILE))
+
+  def test_create_from_file_succeeds_with_valid_model_path(self):
+    # Creates with default option and valid model file successfully.
+    with _TextClassifier.create_from_model_path(self.model_path) as classifier:
+      self.assertIsInstance(classifier, _TextClassifier)
+
+  def test_create_from_options_succeeds_with_valid_model_path(self):
+    # Creates with options containing model file successfully.
+    base_options = _BaseOptions(model_asset_path=self.model_path)
+    options = _TextClassifierOptions(base_options=base_options)
+    with _TextClassifier.create_from_options(options) as classifier:
+      self.assertIsInstance(classifier, _TextClassifier)
+
+  def test_create_from_options_fails_with_invalid_model_path(self):
+    # Invalid empty model path.
+    with self.assertRaisesRegex(
+        ValueError,
+        r"ExternalFile must specify at least one of 'file_content', "
+        r"'file_name', 'file_pointer_meta' or 'file_descriptor_meta'."):
+      base_options = _BaseOptions(model_asset_path='')
+      options = _TextClassifierOptions(base_options=base_options)
+      _TextClassifier.create_from_options(options)
+
+  def test_create_from_options_succeeds_with_valid_model_content(self):
+    # Creates with options containing model content successfully.
+    with open(self.model_path, 'rb') as f:
+      base_options = _BaseOptions(model_asset_buffer=f.read())
+      options = _TextClassifierOptions(base_options=base_options)
+      classifier = _TextClassifier.create_from_options(options)
+      self.assertIsInstance(classifier, _TextClassifier)
+
+  @parameterized.parameters(
+      (ModelFileType.FILE_NAME, _BERT_MODEL_FILE, _NEGATIVE_TEXT,
+       _BERT_NEGATIVE_RESULTS), (ModelFileType.FILE_CONTENT, _BERT_MODEL_FILE,
+                                 _NEGATIVE_TEXT, _BERT_NEGATIVE_RESULTS),
+      (ModelFileType.FILE_NAME, _BERT_MODEL_FILE, _POSITIVE_TEXT,
+       _BERT_POSITIVE_RESULTS), (ModelFileType.FILE_CONTENT, _BERT_MODEL_FILE,
+                                 _POSITIVE_TEXT, _BERT_POSITIVE_RESULTS),
+      (ModelFileType.FILE_NAME, _REGEX_MODEL_FILE, _NEGATIVE_TEXT,
+       _REGEX_NEGATIVE_RESULTS), (ModelFileType.FILE_CONTENT, _REGEX_MODEL_FILE,
+                                  _NEGATIVE_TEXT, _REGEX_NEGATIVE_RESULTS),
+      (ModelFileType.FILE_NAME, _REGEX_MODEL_FILE, _POSITIVE_TEXT,
+       _REGEX_POSITIVE_RESULTS), (ModelFileType.FILE_CONTENT, _REGEX_MODEL_FILE,
+                                  _POSITIVE_TEXT, _REGEX_POSITIVE_RESULTS))
+  def test_classify(self, model_file_type, model_name, text,
+                    expected_classification_result):
+    # Creates classifier.
+    model_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, model_name))
+    if model_file_type is ModelFileType.FILE_NAME:
+      base_options = _BaseOptions(model_asset_path=model_path)
+    elif model_file_type is ModelFileType.FILE_CONTENT:
+      with open(model_path, 'rb') as f:
+        model_content = f.read()
+      base_options = _BaseOptions(model_asset_buffer=model_content)
+    else:
+      # Should never happen
+      raise ValueError('model_file_type is invalid.')
+
+    options = _TextClassifierOptions(base_options=base_options)
+    classifier = _TextClassifier.create_from_options(options)
+
+    # Performs text classification on the input.
+    text_result = classifier.classify(text)
+    # Comparing results.
+    test_utils.assert_proto_equals(self, text_result.to_pb2(),
+                                   expected_classification_result.to_pb2())
+    # Closes the classifier explicitly when the classifier is not used in
+    # a context.
+    classifier.close()
+
+  @parameterized.parameters((ModelFileType.FILE_NAME, _BERT_MODEL_FILE,
+                             _NEGATIVE_TEXT, _BERT_NEGATIVE_RESULTS),
+                            (ModelFileType.FILE_CONTENT, _BERT_MODEL_FILE,
+                             _NEGATIVE_TEXT, _BERT_NEGATIVE_RESULTS))
+  def test_classify_in_context(self, model_file_type, model_name, text,
+                               expected_classification_result):
+    # Creates classifier.
+    model_path = test_utils.get_test_data_path(
+        os.path.join(_TEST_DATA_DIR, model_name))
+    if model_file_type is ModelFileType.FILE_NAME:
+      base_options = _BaseOptions(model_asset_path=model_path)
+    elif model_file_type is ModelFileType.FILE_CONTENT:
+      with open(model_path, 'rb') as f:
+        model_content = f.read()
+      base_options = _BaseOptions(model_asset_buffer=model_content)
+    else:
+      # Should never happen
+      raise ValueError('model_file_type is invalid.')
+
+    options = _TextClassifierOptions(base_options=base_options)
+
+    with _TextClassifier.create_from_options(options) as classifier:
+      # Performs text classification on the input.
+      text_result = classifier.classify(text)
+      # Comparing results.
+      test_utils.assert_proto_equals(self, text_result.to_pb2(),
+                                     expected_classification_result.to_pb2())
+
+
+if __name__ == '__main__':
+  absltest.main()

mediapipe/tasks/python/text/BUILD

@@ -0,0 +1,38 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.
+
+# Placeholder for internal Python strict library and test compatibility macro.
+
+package(default_visibility = ["//mediapipe/tasks:internal"])
+
+licenses(["notice"])
+
+py_library(
+    name = "text_classifier",
+    srcs = [
+        "text_classifier.py",
+    ],
+    deps = [
+        "//mediapipe/python:packet_creator",
+        "//mediapipe/python:packet_getter",
+        "//mediapipe/tasks/cc/components/containers/proto:classifications_py_pb2",
+        "//mediapipe/tasks/cc/text/text_classifier/proto:text_classifier_graph_options_py_pb2",
+        "//mediapipe/tasks/python/components/containers:classifications",
+        "//mediapipe/tasks/python/components/processors:classifier_options",
+        "//mediapipe/tasks/python/core:base_options",
+        "//mediapipe/tasks/python/core:optional_dependencies",
+        "//mediapipe/tasks/python/core:task_info",
+        "//mediapipe/tasks/python/text/core:base_text_task_api",
+    ],
+)

mediapipe/tasks/python/text/__init__.py

@@ -0,0 +1,13 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.

mediapipe/tasks/python/text/core/BUILD

@@ -0,0 +1,31 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.
+
+# Placeholder for internal Python strict library and test compatibility macro.
+
+package(default_visibility = ["//mediapipe/tasks:internal"])
+
+licenses(["notice"])
+
+py_library(
+    name = "base_text_task_api",
+    srcs = [
+        "base_text_task_api.py",
+    ],
+    deps = [
+        "//mediapipe/framework:calculator_py_pb2",
+        "//mediapipe/python:_framework_bindings",
+        "//mediapipe/tasks/python/core:optional_dependencies",
+    ],
+)

mediapipe/tasks/python/text/core/__init__.py

@@ -0,0 +1,16 @@
+"""Copyright 2022 The MediaPipe Authors.
+
+All Rights Reserved.
+
+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.
+"""

mediapipe/tasks/python/text/core/base_text_task_api.py

@@ -0,0 +1,55 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.
+"""MediaPipe text task base api."""
+
+from mediapipe.framework import calculator_pb2
+from mediapipe.python._framework_bindings import task_runner
+from mediapipe.tasks.python.core.optional_dependencies import doc_controls
+
+_TaskRunner = task_runner.TaskRunner
+
+
+class BaseTextTaskApi(object):
+  """The base class of the user-facing mediapipe text task api classes."""
+
+  def __init__(self,
+               graph_config: calculator_pb2.CalculatorGraphConfig) -> None:
+    """Initializes the `BaseVisionTaskApi` object.
+
+    Args:
+      graph_config: The mediapipe text task graph config proto.
+    """
+    self._runner = _TaskRunner.create(graph_config)
+
+  def close(self) -> None:
+    """Shuts down the mediapipe text task instance.
+
+    Raises:
+      RuntimeError: If the mediapipe text task failed to close.
+    """
+    self._runner.close()
+
+  @doc_controls.do_not_generate_docs
+  def __enter__(self):
+    """Returns `self` upon entering the runtime context."""
+    return self
+
+  @doc_controls.do_not_generate_docs
+  def __exit__(self, unused_exc_type, unused_exc_value, unused_traceback):
+    """Shuts down the mediapipe text task instance on exit of the context manager.
+
+    Raises:
+      RuntimeError: If the mediapipe text task failed to close.
+    """
+    self.close()

mediapipe/tasks/python/text/text_classifier.py

@@ -0,0 +1,140 @@
+# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
+#
+# 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.
+"""MediaPipe text classifier task."""
+
+import dataclasses
+
+from mediapipe.python import packet_creator
+from mediapipe.python import packet_getter
+from mediapipe.tasks.cc.components.containers.proto import classifications_pb2
+from mediapipe.tasks.cc.text.text_classifier.proto import text_classifier_graph_options_pb2
+from mediapipe.tasks.python.components.containers import classifications
+from mediapipe.tasks.python.components.processors import classifier_options
+from mediapipe.tasks.python.core import base_options as base_options_module
+from mediapipe.tasks.python.core import task_info as task_info_module
+from mediapipe.tasks.python.core.optional_dependencies import doc_controls
+from mediapipe.tasks.python.text.core import base_text_task_api
+
+TextClassificationResult = classifications.ClassificationResult
+_BaseOptions = base_options_module.BaseOptions
+_TextClassifierGraphOptionsProto = text_classifier_graph_options_pb2.TextClassifierGraphOptions
+_ClassifierOptions = classifier_options.ClassifierOptions
+_TaskInfo = task_info_module.TaskInfo
+
+_CLASSIFICATION_RESULT_OUT_STREAM_NAME = 'classification_result_out'
+_CLASSIFICATION_RESULT_TAG = 'CLASSIFICATION_RESULT'
+_TEXT_IN_STREAM_NAME = 'text_in'
+_TEXT_TAG = 'TEXT'
+_TASK_GRAPH_NAME = 'mediapipe.tasks.text.text_classifier.TextClassifierGraph'
+
+
+@dataclasses.dataclass
+class TextClassifierOptions:
+  """Options for the text classifier task.
+
+  Attributes:
+    base_options: Base options for the text classifier task.
+    classifier_options: Options for the text classification task.
+  """
+  base_options: _BaseOptions
+  classifier_options: _ClassifierOptions = _ClassifierOptions()
+
+  @doc_controls.do_not_generate_docs
+  def to_pb2(self) -> _TextClassifierGraphOptionsProto:
+    """Generates an TextClassifierOptions protobuf object."""
+    base_options_proto = self.base_options.to_pb2()
+    classifier_options_proto = self.classifier_options.to_pb2()
+
+    return _TextClassifierGraphOptionsProto(
+        base_options=base_options_proto,
+        classifier_options=classifier_options_proto)
+
+
+class TextClassifier(base_text_task_api.BaseTextTaskApi):
+  """Class that performs classification on text."""
+
+  @classmethod
+  def create_from_model_path(cls, model_path: str) -> 'TextClassifier':
+    """Creates an `TextClassifier` object from a TensorFlow Lite model and the default `TextClassifierOptions`.
+
+    Args:
+      model_path: Path to the model.
+
+    Returns:
+      `TextClassifier` object that's created from the model file and the
+      default `TextClassifierOptions`.
+
+    Raises:
+      ValueError: If failed to create `TextClassifier` object from the provided
+        file such as invalid file path.
+      RuntimeError: If other types of error occurred.
+    """
+    base_options = _BaseOptions(model_asset_path=model_path)
+    options = TextClassifierOptions(base_options=base_options)
+    return cls.create_from_options(options)
+
+  @classmethod
+  def create_from_options(cls,
+                          options: TextClassifierOptions) -> 'TextClassifier':
+    """Creates the `TextClassifier` object from text classifier options.
+
+    Args:
+      options: Options for the text classifier task.
+
+    Returns:
+      `TextClassifier` object that's created from `options`.
+
+    Raises:
+      ValueError: If failed to create `TextClassifier` object from
+        `TextClassifierOptions` such as missing the model.
+      RuntimeError: If other types of error occurred.
+    """
+    task_info = _TaskInfo(
+        task_graph=_TASK_GRAPH_NAME,
+        input_streams=[':'.join([_TEXT_TAG, _TEXT_IN_STREAM_NAME])],
+        output_streams=[
+            ':'.join([
+                _CLASSIFICATION_RESULT_TAG,
+                _CLASSIFICATION_RESULT_OUT_STREAM_NAME
+            ])
+        ],
+        task_options=options)
+    return cls(task_info.generate_graph_config())
+
+  def classify(self, text: str) -> TextClassificationResult:
+    """Performs classification on the input `text`.
+
+    Args:
+      text: The input text.
+
+    Returns:
+      A `TextClassificationResult` object that contains a list of text
+      classifications.
+
+    Raises:
+      ValueError: If any of the input arguments is invalid.
+      RuntimeError: If text classification failed to run.
+    """
+    output_packets = self._runner.process(
+        {_TEXT_IN_STREAM_NAME: packet_creator.create_string(text)})
+
+    classification_result_proto = classifications_pb2.ClassificationResult()
+    classification_result_proto.CopyFrom(
+        packet_getter.get_proto(
+            output_packets[_CLASSIFICATION_RESULT_OUT_STREAM_NAME]))
+
+    return TextClassificationResult([
+        classifications.Classifications.create_from_pb2(classification)
+        for classification in classification_result_proto.classifications
+    ])