# Copyright 2021 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 # Copyright 2020 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. # ============================================================================== """Abstraction of multi-task model.""" from typing import Text, Dict import tensorflow as tf class MultiTaskBaseModel(tf.Module): """Base class that holds multi-task model computation.""" def __init__(self, **kwargs): super().__init__(**kwargs) self._sub_tasks = self._instantiate_sub_tasks() def _instantiate_sub_tasks(self) -> Dict[Text, tf.keras.Model]: """Abstract function that sets up the computation for each sub-task. Returns: A map from task name (as string) to a tf.keras.Model object that represents the sub-task in the multi-task pool. """ raise NotImplementedError( "_instantiate_sub_task_models() is not implemented.") @property def sub_tasks(self): """Fetch a map of task name (string) to task model (tf.keras.Model).""" return self._sub_tasks def initialize(self): """Optional function that loads a pre-train checkpoint.""" return