Initial commit

trl/trainer/base.py

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+# Copyright 2022 The HuggingFace Team. 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.
+
+from huggingface_hub import PyTorchModelHubMixin
+
+
+class BaseTrainer(PyTorchModelHubMixin):
+    r"""
+    Base class for all trainers - this base class implements the basic functions that we
+    need for a trainer.
+
+    The trainer needs to have the following functions:
+        - step: takes in a batch of data and performs a step of training
+        - loss: takes in a batch of data and returns the loss
+        - compute_rewards: takes in a batch of data and returns the rewards
+        - _build_models_and_tokenizer: builds the models and tokenizer
+        - _build_dataset: builds the dataset
+    Each user is expected to implement their own trainer class that inherits from this base
+    if they want to use a new training algorithm.
+    """
+
+    def __init__(self, config):
+        self.config = config
+
+    def step(self, *args):
+        raise NotImplementedError("Not implemented")
+
+    def loss(self, *args):
+        raise NotImplementedError("Not implemented")
+
+    def compute_rewards(self, *args):
+        raise NotImplementedError("Not implemented")
+
+    def _save_pretrained(self, save_directory):
+        raise NotImplementedError("Not implemented")