Internal change

PiperOrigin-RevId: 428078415

official/projects/qat/vision/registry_imports.py

+# Copyright 2022 The TensorFlow 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.
+
+"""All necessary imports for registration on qat project."""
+# pylint: disable=unused-import
+from official.projects.qat.vision import configs
+from official.projects.qat.vision.modeling import layers
+from official.projects.qat.vision.tasks import image_classification
+from official.projects.qat.vision.tasks import retinanet
+from official.projects.qat.vision.tasks import semantic_segmentation

official/projects/qat/vision/tasks/__init__.py

+# Copyright 2022 The TensorFlow 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.
+
+# Lint as: python3
+"""Tasks package definition."""
+
+from official.projects.qat.vision.tasks import image_classification

official/projects/qat/vision/tasks/image_classification.py

+# Copyright 2022 The TensorFlow 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.
+
+# Lint as: python3
+"""Image classification task definition."""
+import tensorflow as tf
+
+from official.core import task_factory
+from official.projects.qat.vision.configs import image_classification as exp_cfg
+from official.projects.qat.vision.modeling import factory
+from official.vision.beta.tasks import image_classification
+
+
+@task_factory.register_task_cls(exp_cfg.ImageClassificationTask)
+class ImageClassificationTask(image_classification.ImageClassificationTask):
+  """A task for image classification with QAT."""
+
+  def build_model(self) -> tf.keras.Model:
+    """Builds classification model with QAT."""
+    input_specs = tf.keras.layers.InputSpec(
+        shape=[None] + self.task_config.model.input_size)
+
+    l2_weight_decay = self.task_config.losses.l2_weight_decay
+    # Divide weight decay by 2.0 to match the implementation of tf.nn.l2_loss.
+    # (https://www.tensorflow.org/api_docs/python/tf/keras/regularizers/l2)
+    # (https://www.tensorflow.org/api_docs/python/tf/nn/l2_loss)
+    l2_regularizer = (tf.keras.regularizers.l2(
+        l2_weight_decay / 2.0) if l2_weight_decay else None)
+
+    model = super(ImageClassificationTask, self).build_model()
+    if self.task_config.quantization:
+      model = factory.build_qat_classification_model(
+          model,
+          self.task_config.quantization,
+          input_specs=input_specs,
+          model_config=self.task_config.model,
+          l2_regularizer=l2_regularizer)
+
+    return model

official/projects/qat/vision/tasks/image_classification_test.py

+# Copyright 2022 The TensorFlow 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 image classification task."""
+
+# pylint: disable=unused-import
+from absl.testing import parameterized
+import orbit
+import tensorflow as tf
+
+from official.core import exp_factory
+from official.modeling import optimization
+from official.projects.qat.vision.tasks import image_classification as img_cls_task
+from official.vision import beta
+
+
+class ImageClassificationTaskTest(tf.test.TestCase, parameterized.TestCase):
+
+  @parameterized.parameters(('resnet_imagenet_qat'),
+                            ('mobilenet_imagenet_qat'))
+  def test_task(self, config_name):
+    config = exp_factory.get_exp_config(config_name)
+    config.task.train_data.global_batch_size = 2
+
+    task = img_cls_task.ImageClassificationTask(config.task)
+    model = task.build_model()
+    metrics = task.build_metrics()
+    strategy = tf.distribute.get_strategy()
+
+    dataset = orbit.utils.make_distributed_dataset(strategy, task.build_inputs,
+                                                   config.task.train_data)
+
+    iterator = iter(dataset)
+    opt_factory = optimization.OptimizerFactory(config.trainer.optimizer_config)
+    optimizer = opt_factory.build_optimizer(opt_factory.build_learning_rate())
+    logs = task.train_step(next(iterator), model, optimizer, metrics=metrics)
+    for metric in metrics:
+      logs[metric.name] = metric.result()
+    self.assertIn('loss', logs)
+    self.assertIn('accuracy', logs)
+    self.assertIn('top_5_accuracy', logs)
+    logs = task.validation_step(next(iterator), model, metrics=metrics)
+    for metric in metrics:
+      logs[metric.name] = metric.result()
+    self.assertIn('loss', logs)
+    self.assertIn('accuracy', logs)
+    self.assertIn('top_5_accuracy', logs)
+
+
+if __name__ == '__main__':
+  tf.test.main()

official/projects/qat/vision/train.py

+# Copyright 2022 The TensorFlow 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.
+
+"""TensorFlow Model Garden Vision training driver, including QAT configs.."""
+
+from absl import app
+
+from official.common import flags as tfm_flags
+from official.projects.qat.vision import registry_imports  # pylint: disable=unused-import
+from official.vision.beta import train
+
+
+if __name__ == '__main__':
+  tfm_flags.define_flags()
+  app.run(train.main)