Improve the checkpoint upgrade utility script

docs/source-pytorch/common/checkpointing.rst

@@ -12,33 +12,41 @@ Checkpointing
 .. Add callout items below this line
 
 .. displayitem::
-   :header: Basic
+   :header: Saving and loading checkpoints
    :description: Learn to save and load checkpoints
-   :col_css: col-md-3
+   :col_css: col-md-4
    :button_link: checkpointing_basic.html
    :height: 150
    :tag: basic
 
 .. displayitem::
-   :header: Intermediate
-   :description: Customize checkpointing behavior
-   :col_css: col-md-3
+   :header: Customize checkpointing behavior
+   :description: Learn how to change the behavior of checkpointing
+   :col_css: col-md-4
    :button_link: checkpointing_intermediate.html
    :height: 150
    :tag: intermediate
 
 .. displayitem::
-   :header: Advanced
+   :header: Upgrading checkpoints
+   :description: Learn how to upgrade old checkpoints to the newest Lightning version
+   :col_css: col-md-4
+   :button_link: checkpointing_migration.html
+   :height: 150
+   :tag: intermediate
+
+.. displayitem::
+   :header: Cloud-based checkpoints
    :description: Enable cloud-based checkpointing and composable checkpoints.
-   :col_css: col-md-3
+   :col_css: col-md-4
    :button_link: checkpointing_advanced.html
    :height: 150
    :tag: advanced
 
 .. displayitem::
-   :header: Expert
+   :header: Distributed checkpoints
    :description: Customize checkpointing for custom distributed strategies and accelerators.
-   :col_css: col-md-3
+   :col_css: col-md-4
    :button_link: checkpointing_expert.html
    :height: 150
    :tag: expert

docs/source-pytorch/common/checkpointing_advanced.rst

@@ -1,8 +1,8 @@
 .. _checkpointing_advanced:
 
-########################
-Checkpointing (advanced)
-########################
+##################################
+Cloud-based checkpoints (advanced)
+##################################
 
 
 *****************

docs/source-pytorch/common/checkpointing_basic.rst

@@ -2,9 +2,9 @@
 
 .. _checkpointing_basic:
 
-#####################
-Checkpointing (basic)
-#####################
+######################################
+Saving and loading checkpoints (basic)
+######################################
 **Audience:** All users
 
 ----

docs/source-pytorch/common/checkpointing_expert.rst

@@ -2,9 +2,9 @@
 
 .. _checkpointing_expert:
 
-######################
-Checkpointing (expert)
-######################
+################################
+Distributed checkpoints (expert)
+################################
 
 *********************************
 Writing your own Checkpoint class

docs/source-pytorch/common/checkpointing_intermediate.rst

@@ -2,9 +2,9 @@
 
 .. _checkpointing_intermediate:
 
-############################
-Checkpointing (intermediate)
-############################
+###############################################
+Customize checkpointing behavior (intermediate)
+###############################################
 **Audience:** Users looking to customize the checkpointing behavior
 
 ----

docs/source-pytorch/common/checkpointing_migration.rst

@@ -0,0 +1,51 @@
+:orphan:
+
+.. _checkpointing_basic:
+
+####################################
+Upgrading checkpoints (intermediate)
+####################################
+**Audience:** Users who are upgrading Lightning and their code and want to reuse their old checkpoints.
+
+----
+
+**************************************
+Resume training from an old checkpoint
+**************************************
+
+Next to the model weights and trainer state, a Lightning checkpoint contains the version number of Lightning with which the checkpoint was saved.
+When you load a checkpoint file, either by resuming training
+
+.. code-block:: python
+
+    trainer = Trainer(...)
+    trainer.fit(model, ckpt_path="path/to/checkpoint.ckpt")
+
+or by loading the state directly into your model,
+
+.. code-block:: python
+
+    model = LitModel.load_from_checkpoint("path/to/checkpoint.ckpt")
+
+Lightning will automatically recognize that it is from an older version and migrates the internal structure so it can be loaded properly.
+This is done without any action required by the user.
+
+----
+
+************************************
+Upgrade checkpoint files permanently
+************************************
+
+When Lightning loads a checkpoint, it applies the version migration on-the-fly as explained above, but it does not modify your checkpoint files.
+You can upgrade checkpoint files permanently with the following command
+
+.. code-block::
+
+    python -m lightning.pytorch.utilities.upgrade_checkpoint path/to/model.ckpt
+
+
+or a folder with multiple files:
+
+.. code-block::
+
+    python -m lightning.pytorch.utilities.upgrade_checkpoint /path/to/checkpoints/folder

src/pytorch_lightning/CHANGELOG.md

@@ -12,7 +12,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Added utilities to migrate checkpoints from one Lightning version to another ([#15237](https://github.com/Lightning-AI/lightning/pull/15237))
 
--
+- Added support to upgrade all checkpoints in a folder using the `pl.utilities.upgrade_checkpoint` script ([#15333](https://github.com/Lightning-AI/lightning/pull/15333))
 
 -
 

src/pytorch_lightning/utilities/upgrade_checkpoint.py

@@ -11,30 +11,81 @@
 # 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 argparse
+import glob
 import logging
+from argparse import ArgumentParser, Namespace
+from pathlib import Path
 from shutil import copyfile
+from typing import List
 
 import torch
+from tqdm import tqdm
 
 from pytorch_lightning.utilities.migration import migrate_checkpoint, pl_legacy_patch
 
-log = logging.getLogger(__name__)
+_log = logging.getLogger(__name__)
 
-if __name__ == "__main__":
 
-    parser = argparse.ArgumentParser(
+def _upgrade(args: Namespace) -> None:
+    path = Path(args.path).absolute()
+    extension: str = args.extension if args.extension.startswith(".") else f".{args.extension}"
+    files: List[Path] = []
+
+    if not path.exists():
+        _log.error(
+            f"The path {path} does not exist. Please provide a valid path to a checkpoint file or a directory"
+            f" containing checkpoints ending in {extension}."
+        )
+        exit(1)
+
+    if path.is_file():
+        files = [path]
+    if path.is_dir():
+        files = [Path(p) for p in glob.glob(str(path / "**" / f"*{extension}"), recursive=True)]
+    if not files:
+        _log.error(
+            f"No checkpoint files with extension {extension} were found in {path}."
+            f" HINT: Try setting the `--extension` option to specify the right file extension to look for."
+        )
+        exit(1)
+
+    _log.info("Creating a backup of the existing checkpoint files before overwriting in the upgrade process.")
+    for file in files:
+        backup_file = file.with_suffix(".bak")
+        if backup_file.exists():
+            # never overwrite backup files - they are the original, untouched checkpoints
+            continue
+        copyfile(file, backup_file)
+
+    _log.info("Upgrading checkpoints ...")
+    progress = tqdm if len(files) > 1 else lambda x: x
+    for file in progress(files):
+        with pl_legacy_patch():
+            checkpoint = torch.load(file)
+        migrate_checkpoint(checkpoint)
+        torch.save(checkpoint, file)
+
+    _log.info("Done.")
+
+
+def main() -> None:
+    parser = ArgumentParser(
         description=(
-            "Upgrade an old checkpoint to the current schema. This will also save a backup of the original file."
+            "A utility to upgrade old checkpoints to the format of the current Lightning version."
+            " This will also save a backup of the original files."
         )
     )
-    parser.add_argument("--file", help="filepath for a checkpoint to upgrade")
-
+    parser.add_argument("path", type=str, help="Path to a checkpoint file or a directory with checkpoints to upgrade")
+    parser.add_argument(
+        "--extension",
+        "-e",
+        type=str,
+        default=".ckpt",
+        help="The file extension to look for when searching for checkpoint files in a directory.",
+    )
     args = parser.parse_args()
+    _upgrade(args)
+
 
-    log.info("Creating a backup of the existing checkpoint file before overwriting in the upgrade process.")
-    copyfile(args.file, args.file + ".bak")
-    with pl_legacy_patch():
-        checkpoint = torch.load(args.file)
-    migrate_checkpoint(checkpoint)
-    torch.save(checkpoint, args.file)
+if __name__ == "__main__":
+    main()

tests/tests_pytorch/utilities/test_upgrade_checkpoint.py

@@ -11,12 +11,18 @@
 # 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 logging
+from pathlib import Path
+from unittest import mock
+from unittest.mock import ANY, call
+
 import pytest
 
 import pytorch_lightning as pl
 from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
 from pytorch_lightning.utilities.migration import migrate_checkpoint
 from pytorch_lightning.utilities.migration.utils import _get_version, _set_legacy_version, _set_version
+from pytorch_lightning.utilities.upgrade_checkpoint import main as upgrade_main
 
 
 @pytest.mark.parametrize(
@@ -47,3 +53,71 @@ def test_upgrade_checkpoint(tmpdir, old_checkpoint, new_checkpoint):
     updated_checkpoint, _ = migrate_checkpoint(old_checkpoint)
     assert updated_checkpoint == old_checkpoint == new_checkpoint
     assert _get_version(updated_checkpoint) == pl.__version__
+
+
+def test_upgrade_checkpoint_file_missing(tmp_path, caplog):
+    # path to single file (missing)
+    file = tmp_path / "checkpoint.ckpt"
+    with mock.patch("sys.argv", ["upgrade_checkpoint.py", str(file)]):
+        with caplog.at_level(logging.ERROR):
+            with pytest.raises(SystemExit):
+                upgrade_main()
+            assert f"The path {file} does not exist" in caplog.text
+
+    caplog.clear()
+
+    # path to non-empty directory, but no checkpoints with matching extension
+    file.touch()
+    with mock.patch("sys.argv", ["upgrade_checkpoint.py", str(tmp_path), "--extension", ".other"]):
+        with caplog.at_level(logging.ERROR):
+            with pytest.raises(SystemExit):
+                upgrade_main()
+            assert "No checkpoint files with extension .other were found" in caplog.text
+
+
+@mock.patch("pytorch_lightning.utilities.upgrade_checkpoint.torch.save")
+@mock.patch("pytorch_lightning.utilities.upgrade_checkpoint.torch.load")
+@mock.patch("pytorch_lightning.utilities.upgrade_checkpoint.migrate_checkpoint")
+def test_upgrade_checkpoint_single_file(migrate_mock, load_mock, save_mock, tmp_path):
+    file = tmp_path / "checkpoint.ckpt"
+    file.touch()
+    with mock.patch("sys.argv", ["upgrade_checkpoint.py", str(file)]):
+        upgrade_main()
+
+    load_mock.assert_called_once_with(Path(file))
+    migrate_mock.assert_called_once()
+    save_mock.assert_called_once_with(ANY, Path(file))
+
+
+@mock.patch("pytorch_lightning.utilities.upgrade_checkpoint.torch.save")
+@mock.patch("pytorch_lightning.utilities.upgrade_checkpoint.torch.load")
+@mock.patch("pytorch_lightning.utilities.upgrade_checkpoint.migrate_checkpoint")
+def test_upgrade_checkpoint_directory(migrate_mock, load_mock, save_mock, tmp_path):
+    top_files = [tmp_path / "top0.ckpt", tmp_path / "top1.ckpt"]
+    nested_files = [
+        tmp_path / "subdir0" / "nested0.ckpt",
+        tmp_path / "subdir0" / "nested1.other",
+        tmp_path / "subdir1" / "nested2.ckpt",
+    ]
+
+    for file in top_files + nested_files:
+        file.parent.mkdir(exist_ok=True, parents=True)
+        file.touch()
+
+    # directory with recursion
+    with mock.patch("sys.argv", ["upgrade_checkpoint.py", str(tmp_path)]):
+        upgrade_main()
+
+    assert load_mock.call_args_list == [
+        call(tmp_path / "top1.ckpt"),
+        call(tmp_path / "top0.ckpt"),
+        call(tmp_path / "subdir0" / "nested0.ckpt"),
+        call(tmp_path / "subdir1" / "nested2.ckpt"),
+    ]
+    assert migrate_mock.call_count == 4
+    assert save_mock.call_args_list == [
+        call(ANY, tmp_path / "top1.ckpt"),
+        call(ANY, tmp_path / "top0.ckpt"),
+        call(ANY, tmp_path / "subdir0" / "nested0.ckpt"),
+        call(ANY, tmp_path / "subdir1" / "nested2.ckpt"),
+    ]