| import unittest |
|
|
| import torch |
| from torch.utils.data import DataLoader, TensorDataset |
|
|
| from accelerate.accelerator import Accelerator |
| from accelerate.state import AcceleratorState |
|
|
|
|
| def create_components(): |
| model = torch.nn.Linear(2, 4) |
| optimizer = torch.optim.AdamW(model.parameters(), lr=1.0) |
| scheduler = torch.optim.lr_scheduler.OneCycleLR(optimizer, max_lr=0.01, steps_per_epoch=2, epochs=1) |
| train_dl = DataLoader(TensorDataset(torch.tensor([1, 2, 3]))) |
| valid_dl = DataLoader(TensorDataset(torch.tensor([4, 5, 6]))) |
|
|
| return model, optimizer, scheduler, train_dl, valid_dl |
|
|
|
|
| class AcceleratorTester(unittest.TestCase): |
| def test_prepared_objects_are_referenced(self): |
| accelerator = Accelerator() |
| model, optimizer, scheduler, train_dl, valid_dl = create_components() |
|
|
| ( |
| prepared_model, |
| prepared_optimizer, |
| prepared_scheduler, |
| prepared_train_dl, |
| prepared_valid_dl, |
| ) = accelerator.prepare(model, optimizer, scheduler, train_dl, valid_dl) |
|
|
| self.assertTrue(prepared_model in accelerator._models) |
| self.assertTrue(prepared_optimizer in accelerator._optimizers) |
| self.assertTrue(prepared_scheduler in accelerator._schedulers) |
| self.assertTrue(prepared_train_dl in accelerator._dataloaders) |
| self.assertTrue(prepared_valid_dl in accelerator._dataloaders) |
| AcceleratorState._reset_state() |
|
|
| def test_free_memory_dereferences_prepared_components(self): |
| accelerator = Accelerator() |
| model, optimizer, scheduler, train_dl, valid_dl = create_components() |
| accelerator.prepare(model, optimizer, scheduler, train_dl, valid_dl) |
|
|
| accelerator.free_memory() |
|
|
| self.assertTrue(len(accelerator._models) == 0) |
| self.assertTrue(len(accelerator._optimizers) == 0) |
| self.assertTrue(len(accelerator._schedulers) == 0) |
| self.assertTrue(len(accelerator._dataloaders) == 0) |
| AcceleratorState._reset_state() |
|
|
