New Progress Bar, Backoff, Batching #165
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soldni
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undfined and
kyleclo
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undfined
undfined
approved these changes
May 28, 2024
| @@ -2,4 +2,4 @@ | |||
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| PATH=/home/vscode/.cargo/bin:$PATH | |||
| cd dolma | |||
| source /home/vscode/miniforge3/bin/activate && pip install cmake "maturin[patchelf]>=1.1,<2.0" | |||
| source /home/vscode/miniforge3/bin/activate && pip install cmake "maturin>=1.5,<2.0" | |||
| @@ -30,6 +31,8 @@ dependencies = [ | |||
| "numpy", | |||
| "necessary>=0.4.3", | |||
| "charset-normalizer>=3.2.0", | |||
| "zstandard>=0.20.0", | |||
| "backoff>=2.0.0", | |||
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Is this version required? There's 2 minor versions since this 2.0 release "2.2.1"
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| def __radd__(self: BPP, other: BPP) -> BPP: | ||
| """Combine two parallel processors into one.""" | ||
| return other.__add__(self) |
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Can you describe when this is useful?
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| """Process multiple files. Naively calls process_single for each file, but can be overridden.""" | ||
| for src_path, dst_path, single_kwargs in zip(source_paths, destination_paths, kwargs): | ||
| cls.process_single(source_path=src_path, destination_path=dst_path, queue=queue, **single_kwargs) |
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Maybe include an example of overloading this processing method?
| cls.get_logger().warning(message) | ||
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| @classmethod | ||
| def _process_batch_and_save_status( |
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Is this actually saving status or just the metadata outcome?
| len(all_process_kwargs), | ||
| ) | ||
| # no need to be wasteful with processes: we only need as many cores a the number of batches | ||
| num_processes = min(self.num_processes, len(batches)) |
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Can you have more batches than available procs/cores?
| Args: | ||
| iterables (Iterable[T]): One or more iterables to group into batches. | ||
| batch_size (int): The size of each batch. Defaults to 1. | ||
| drop_last (bool): Whether to drop the last batch if it is smaller than `batch_size`. Defaults to False. |
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What scenario would you want to drop the last batch?
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| if not hasattr(self, "PROGRESS_BAR_CLS"): | ||
| self.PROGRESS_BAR_CLS = BaseProgressBar.from_increment_function(self) |
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Can this be run without a progress bar at all?
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| class TestBatching(TestCase): | ||
| def test_batching(self): | ||
| a = [1, 2, 3, 4, 5] | ||
| b = [6, 7, 8, 9, 0] | ||
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| output = list(batch_iterator(a, b, batch_size=2)) | ||
| self.assertEqual(len(output), 3) | ||
| self.assertEqual(output[0], [(1, 2), (6, 7)]) | ||
| self.assertEqual(output[1], [(3, 4), (8, 9)]) | ||
| self.assertEqual(output[2], [(5,), (0,)]) | ||
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| def test_single_batching(self): | ||
| a = [1, 2, 3, 4, 5] | ||
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| output = list(batch_iterator(a, batch_size=2)) | ||
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| self.assertEqual(len(output), 3) | ||
| self.assertEqual(output[0], [(1, 2)]) | ||
| self.assertEqual(output[1], [(3, 4)]) | ||
| self.assertEqual(output[2], [(5,)]) | ||
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| def test_longer_batch_than_slice(self): | ||
| a = list(range(3)) | ||
| b = list(range(3, 6)) | ||
| c = list(range(6, 9)) | ||
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| output = list(batch_iterator(a, b, c, batch_size=4)) | ||
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| self.assertEqual(len(output), 1) | ||
| self.assertEqual(output[0], [(0, 1, 2), (3, 4, 5), (6, 7, 8)]) | ||
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| def test_drop_last(self): | ||
| a = [1, 2, 3, 4, 5] | ||
| b = [6, 7, 8, 9, 0] | ||
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| output = list(batch_iterator(a, b, batch_size=2, drop_last=True)) | ||
| self.assertEqual(len(output), 2) | ||
| self.assertEqual(output[0], [(1, 2), (6, 7)]) | ||
| self.assertEqual(output[1], [(3, 4), (8, 9)]) |
| dolma_tests_skip = os.environ.get(DOLMA_TESTS_SKIP_AWS_ENV_VAR) | ||
| LOGGER.info(f"{DOLMA_TESTS_SKIP_AWS_ENV_VAR}: {dolma_tests_skip}") | ||
| return (dolma_tests_skip or "false").lower() == "true" | ||
| dolma_tests_skip = yaml.safe_load(os.environ.get(DOLMA_TESTS_SKIP_AWS_ENV_VAR) or "false") |
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safe_load is duplicative if casting to bool() regardless below right? More a nit than anything, I guess it wouldn't hurt...
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This PR adds three nice features to
BaseParallelProcessor:parallel.pyPoolWithDebugwrapper aroundmultiprocessing.Poolthat transparently disables multiprocessing when debuggingbackofflibrary to implement backoff and retries in case of failure