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| # Copyright (c) 2021 GradsFlow. 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. | |
| import torch | |
| from gradsflow.models import Model | |
| class DummyModel(Model): | |
| def __init__(self): | |
| learner = torch.nn.Linear(1, 4) | |
| super().__init__(learner) | |
| def backward(self, loss: torch.Tensor): | |
| return None | |
| def train_step(self, batch): | |
| return {"loss": torch.as_tensor(1), "metrics": {"accuracy": 1}} | |
| def val_step(self, batch): | |
| return {"loss": torch.as_tensor(1), "metrics": {"accuracy": 1}} | |