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fix: fix PT AutoBatchSize OOM bug and merge execute_all into base (#4047
) Fix #4036. Fix #4037. <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **New Features** - Improved batch processing methods to enhance compatibility with various array-like objects through Array API integration. - Added a new test suite to validate the functionality of the `AutoBatchSize` class under different conditions, ensuring robust behavior with GPU resources. - **Bug Fixes** - Removed the outdated `execute_all` method, streamlining batch execution processes. - **Documentation** - Updated minimum TensorFlow version requirement to 2.7 for backend compatibility. - Clarified installation instructions to reflect the updated TensorFlow version requirement. - **Chores** - Specified minimum NumPy version dependency as 1.21 in project configuration. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: Jinzhe Zeng <[email protected]> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,141 @@ | ||
| # SPDX-License-Identifier: LGPL-3.0-or-later | ||
| import os | ||
| import sys | ||
| import unittest | ||
|
|
||
| from deepmd.utils.batch_size import ( | ||
| AutoBatchSize, | ||
| ) | ||
| from deepmd.utils.errors import ( | ||
| OutOfMemoryError, | ||
| ) | ||
|
|
||
| if sys.version_info >= (3, 9): | ||
| import array_api_strict as xp | ||
| else: | ||
| raise unittest.SkipTest("array_api_strict doesn't support Python<=3.8") | ||
|
|
||
|
|
||
| class CustomizedAutoBatchSizeCPU(AutoBatchSize): | ||
| def is_gpu_available(self): | ||
| return False | ||
|
|
||
| def is_oom_error(self, e): | ||
| return isinstance(e, OutOfMemoryError) | ||
|
|
||
|
|
||
| class CustomizedAutoBatchSizeGPU(AutoBatchSize): | ||
| def is_gpu_available(self): | ||
| return True | ||
|
|
||
| def is_oom_error(self, e): | ||
| return isinstance(e, OutOfMemoryError) | ||
|
|
||
|
|
||
| class TestAutoBatchSize(unittest.TestCase): | ||
| def oom(self, batch_size, start_index): | ||
| if batch_size >= 512: | ||
| raise OutOfMemoryError | ||
| return batch_size, xp.zeros((batch_size, 2)) | ||
|
|
||
| def test_execute_oom_gpu(self): | ||
| # initial batch size 256 = 128 * 2 | ||
| auto_batch_size = CustomizedAutoBatchSizeGPU(256, 2.0) | ||
| # no error - 128 | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| # no error - 256 | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 256) | ||
| self.assertEqual(result.shape, (256, 2)) | ||
| # error - 512 return 0, None | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 0) | ||
| self.assertIsNone(result) | ||
| # 256 again | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 256) | ||
| self.assertEqual(result.shape, (256, 2)) | ||
| # 256 again | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 256) | ||
| self.assertEqual(result.shape, (256, 2)) | ||
|
|
||
| def test_execute_oom_cpu(self): | ||
| # initial batch size 256 = 128 * 2, nb is always 128 | ||
| auto_batch_size = CustomizedAutoBatchSizeCPU(256, 2.0) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
|
|
||
| @unittest.mock.patch.dict(os.environ, {"DP_INFER_BATCH_SIZE": "256"}, clear=True) | ||
| def test_execute_oom_environment_variables(self): | ||
| # DP_INFER_BATCH_SIZE = 256 = 128 * 2, nb is always 128 | ||
| auto_batch_size = CustomizedAutoBatchSizeGPU(999, 2.0) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
| nb, result = auto_batch_size.execute(self.oom, 1, 2) | ||
| self.assertEqual(nb, 128) | ||
| self.assertEqual(result.shape, (128, 2)) | ||
|
|
||
| def test_execute_all(self): | ||
| dd1 = xp.zeros((10000, 2, 1)) | ||
| auto_batch_size = CustomizedAutoBatchSizeGPU(256, 2.0) | ||
| dd2 = auto_batch_size.execute_all(xp.asarray, 10000, 2, dd1) | ||
| assert xp.all(dd1 == dd2) | ||
|
|
||
| def test_execute_all_dict(self): | ||
| dd0 = xp.zeros((10000, 2, 1, 3, 4)) | ||
| dd1 = xp.ones((10000, 2, 1, 3, 4)) | ||
| auto_batch_size = CustomizedAutoBatchSizeGPU(256, 2.0) | ||
|
|
||
| def func(dd1): | ||
| return { | ||
| "foo": xp.zeros_like(dd1), | ||
| "bar": xp.ones_like(dd1), | ||
| } | ||
|
|
||
| dd2 = auto_batch_size.execute_all(func, 10000, 2, dd1) | ||
| assert xp.all(dd0 == dd2["foo"]) | ||
| assert xp.all(dd1 == dd2["bar"]) | ||
|
|
||
| def test_execute_all_dict_oom(self): | ||
| # to reproduce #4036 when commenting "if n_batch == 0: continue" | ||
| dd0 = xp.zeros((10, 2, 1, 3, 4)) | ||
| dd1 = xp.ones((10, 2, 1, 3, 4)) | ||
| auto_batch_size = CustomizedAutoBatchSizeGPU(4, 2.0) | ||
|
|
||
| def func(dd1): | ||
| if dd1.shape[0] >= 2: | ||
| raise OutOfMemoryError | ||
| return { | ||
| "foo": xp.zeros_like(dd1), | ||
| "bar": xp.ones_like(dd1), | ||
| } | ||
|
|
||
| dd2 = auto_batch_size.execute_all(func, 10, 2, dd1) | ||
| assert xp.all(dd0 == dd2["foo"]) | ||
| assert xp.all(dd1 == dd2["bar"]) |