fix(ckpt): correct safetensors path for decimal-suffix stems; return actual save path

[wenh06]

Summary

Two related bugs introduced when the checkpoint format switched from .pth.tar to .safetensors.

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Bug A — CkptMixin.save() silently truncates filenames with decimal values

File: torch_ecg/utils/utils_nn.py

Trainer generates checkpoint folder names like …_metric_0.91. pathlib treats .91 as the file extension, so the old path.with_suffix(".safetensors") replaced .91 instead of appending, producing …metric_0.safetensors instead of the correct …metric_0.91.safetensors.

Fix: after determining use_safetensors=True, if path.suffix != ".safetensors" we use string concatenation instead of with_suffix:

path = Path(str(path) + ".safetensors")   # append, never replace

The now-redundant path.with_suffix(".safetensors") inside the single-file save_file call is also removed (path is already normalised at that point).

save() now returns Path (the actual file/directory written) instead of None.

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Bug B — BaseTrainer checkpoint cleanup always fails

File: torch_ecg/components/trainer.py

saved_models stored the raw stem path (…metric_0.91), but the file on disk was …metric_0.91.safetensors. Every os.remove(model_to_remove) in the keep_checkpoint_max cleanup therefore raised FileNotFoundError silently.

Fix: save_checkpoint() forwards the Path returned by model.save(); the training loop stores that actual path:

actual_save_path = self.save_checkpoint(str(save_path))
self.saved_models.append(actual_save_path if actual_save_path is not None else save_path)

Directory-style checkpoints (non-single-file mode) are now cleaned up with shutil.rmtree instead of os.remove. shutil is promoted to a top-level import.

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Changes

File	What changed
torch_ecg/utils/utils_nn.py	Path normalisation fix; save() returns Path
torch_ecg/components/trainer.py	Use returned path in saved_models; handle dir cleanup; top-level shutil import
test/test_utils/test_utils_nn.py	New test_ckpt_decimal_suffix_path covering all three save branches
CHANGELOG.rst	Two Fixed entries under Unreleased

Tests

pytest test/test_utils/test_utils_nn.py -k "not test_mixin_classes"
# 9 passed

test_mixin_classes is excluded only because it requires a Dropbox network connection (pre-existing, unrelated).

[Copilot]

Pull request overview

The PR is described as a focused fix for two checkpoint-related bugs (decimal-suffix paths being truncated by pathlib.with_suffix, and BaseTrainer silently failing to clean up checkpoints because it stored the un-normalised path). In practice the diff is much broader: it also performs a sweeping migration from numbers.Real to int / float / Union[int, float] across ~40 files, adds input validation (with new warnings/errors) to bandpass_filter, and makes a few small ancillary changes (view → reshape in baseline_removal, Tuple[Union[type(None), int], ...] → Tuple[Union[None, int], ...], etc.).

Changes:

• Fix CkptMixin.save() decimal-suffix truncation; make save() and save_checkpoint() return the actual Path; clean up directory-style checkpoints with shutil.rmtree.
• Replace numbers.Real annotations/isinstance checks with int/float/Union[int, float] throughout the codebase.
• Add validation and warnings to bandpass_filter and update related tests.

Reviewed changes

Copilot reviewed 62 out of 62 changed files in this pull request and generated 7 comments.

Show a summary per file

File	Description
torch_ecg/utils/utils_nn.py	Append .safetensors instead of with_suffix; return saved Path; drop Real.
torch_ecg/components/trainer.py	Use returned Path from save(); shutil.rmtree for dir checkpoints; promote shutil import.
torch_ecg/utils/utils_signal_t.py	New input validation in bandpass_filter; view→reshape in baseline_removal; Real→int/float.
torch_ecg/utils/utils_metrics.py, utils_interval.py, _preproc.py, _edr.py	Real → int/float; _getxy now returns a Python float via .item().
torch_ecg/models/_nets.py	Real → float/(float, dict) in several isinstance checks (regression: int no longer accepted).
torch_ecg/models/cnn/{xception,resnet,regnet,mobilenet}.py, models/loss.py, models/ecg_fcn.py	Real → (int, float, …) in isinstance checks and annotations.
torch_ecg/preprocessors/.py, _preprocessors/normalize.py, augmenters/.py	Type-hint cleanup (Real → int/float); minor dtype additions in augmenters.
torch_ecg/databases/**/*.py, components/{inputs,outputs,metrics,loggers}.py	Doc/type updates from Real to int/float; Union[str, type(None)] → Union[str, None].
test/test_utils/test_utils_nn.py	New regression test test_ckpt_decimal_suffix_path covering the three save branches.
test/test_preprocessors.py, test/test_preprocessors_t.py, test/test_databases/test_shhs.py	Tests updated to drop Real and to cover new bandpass_filter validation.
CHANGELOG.rst	Two Fixed entries for the checkpoint bugs (the broader Real migration and bandpass validation are not noted).
benchmarks/**/*.py, torch_ecg/preprocessors/README.md	Annotation updates from Real to int/float and minor import cleanups.

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[chatgpt-codex-connector]

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[chatgpt-codex-connector]

Accept integer dropout values

When callers pass dropouts=0 (a common way to disable dropout and previously accepted because numbers.Real includes int), this now falls into the else branch and executes list(0), raising TypeError during model construction. This also affects the same replacement in BranchedConv/SeqLin; keep int in the scalar check so existing integer dropout configs continue to work.

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[codecov]

❌ 1 Tests Failed:

Tests completed	Failed	Passed	Skipped
483	1	482	34

View the top 1 failed test(s) by shortest run time

test/test_databases/test_cpsc2020.py::TestCPSC2020::test_locate_premature_beats

Stack Traces | 0.001s run time

self = <test_cpsc2020.TestCPSC2020 object at 0x7fd49b24e100>

    def test_locate_premature_beats(self):
>       premature_beat_intervals = reader.locate_premature_beats(0)

test/test_databases/test_cpsc2020.py:78: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
.../databases/cpsc_databases/cpsc2020.py:577: in locate_premature_beats
    premature_intervals = get_optimal_covering(
torch_ecg/utils/utils_interval.py:584: in get_optimal_covering
    if (tot_start > min([item if isinstance(item, (int, float)) else item[0] for item in to_cover])) or (
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

.0 = <iterator object at 0x7fd4017cf8b0>

>   if (tot_start > min([item if isinstance(item, (int, float)) else item[0] for item in to_cover])) or (
        tot_end < max([item if isinstance(item, (int, float)) else item[-1] for item in to_cover])
    ):
E   IndexError: invalid index to scalar variable.

torch_ecg/utils/utils_interval.py:584: IndexError

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