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| | from pathlib import Path
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| | from unittest.mock import Mock, patch
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| | from lerobot.constants import (
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| | CHECKPOINTS_DIR,
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| | LAST_CHECKPOINT_LINK,
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| | OPTIMIZER_PARAM_GROUPS,
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| | OPTIMIZER_STATE,
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| | RNG_STATE,
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| | SCHEDULER_STATE,
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| | TRAINING_STATE_DIR,
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| | TRAINING_STEP,
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| | )
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| | from lerobot.utils.train_utils import (
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| | get_step_checkpoint_dir,
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| | get_step_identifier,
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| | load_training_state,
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| | load_training_step,
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| | save_checkpoint,
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| | save_training_state,
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| | save_training_step,
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| | update_last_checkpoint,
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| | )
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| | def test_get_step_identifier():
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| | assert get_step_identifier(5, 1000) == "000005"
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| | assert get_step_identifier(123, 100_000) == "000123"
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| | assert get_step_identifier(456789, 1_000_000) == "0456789"
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| | def test_get_step_checkpoint_dir():
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| | output_dir = Path("/checkpoints")
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| | step_dir = get_step_checkpoint_dir(output_dir, 1000, 5)
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| | assert step_dir == output_dir / CHECKPOINTS_DIR / "000005"
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| | def test_save_load_training_step(tmp_path):
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| | save_training_step(5000, tmp_path)
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| | assert (tmp_path / TRAINING_STEP).is_file()
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| | def test_load_training_step(tmp_path):
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| | step = 5000
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| | save_training_step(step, tmp_path)
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| | loaded_step = load_training_step(tmp_path)
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| | assert loaded_step == step
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| | def test_update_last_checkpoint(tmp_path):
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| | checkpoint = tmp_path / "0005"
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| | checkpoint.mkdir()
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| | update_last_checkpoint(checkpoint)
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| | last_checkpoint = tmp_path / LAST_CHECKPOINT_LINK
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| | assert last_checkpoint.is_symlink()
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| | assert last_checkpoint.resolve() == checkpoint
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| |
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| | @patch("lerobot.utils.train_utils.save_training_state")
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| | def test_save_checkpoint(mock_save_training_state, tmp_path, optimizer):
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| | policy = Mock()
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| | cfg = Mock()
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| | save_checkpoint(tmp_path, 10, cfg, policy, optimizer)
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| | policy.save_pretrained.assert_called_once()
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| | cfg.save_pretrained.assert_called_once()
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| | mock_save_training_state.assert_called_once()
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| | def test_save_training_state(tmp_path, optimizer, scheduler):
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| | save_training_state(tmp_path, 10, optimizer, scheduler)
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| | assert (tmp_path / TRAINING_STATE_DIR).is_dir()
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| | assert (tmp_path / TRAINING_STATE_DIR / TRAINING_STEP).is_file()
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| | assert (tmp_path / TRAINING_STATE_DIR / RNG_STATE).is_file()
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| | assert (tmp_path / TRAINING_STATE_DIR / OPTIMIZER_STATE).is_file()
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| | assert (tmp_path / TRAINING_STATE_DIR / OPTIMIZER_PARAM_GROUPS).is_file()
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| | assert (tmp_path / TRAINING_STATE_DIR / SCHEDULER_STATE).is_file()
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| | def test_save_load_training_state(tmp_path, optimizer, scheduler):
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| | save_training_state(tmp_path, 10, optimizer, scheduler)
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| | loaded_step, loaded_optimizer, loaded_scheduler = load_training_state(tmp_path, optimizer, scheduler)
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| | assert loaded_step == 10
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| | assert loaded_optimizer is optimizer
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| | assert loaded_scheduler is scheduler
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