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Bug fix: Loader.__len__ returns wrong length #144

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Merged
ilan-gold merged 4 commits into from
Feb 11, 2026
Merged

Bug fix: Loader.__len__ returns wrong length #144

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9b6717e
Fix issue where loader.__len__ returns wrong len
felix0097 Feb 10, 2026
f73b6e2
Add test to check for correctness of loader.__len__
felix0097 Feb 10, 2026
7ad4f0d
Removed unnecessary test parametrization
felix0097 Feb 10, 2026
a23b021
Merge branch 'main' into fix/len-loader
felix0097 Feb 10, 2026
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17 changes: 16 additions & 1 deletion src/annbatch/abc/sampler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ def batch_size(self) -> int | None:
@abstractmethod
def shuffle(self) -> bool:
"""Whether data is shuffled.

If `batch_size` is provided and {attr}`annbatch.types.LoadRequest.splits` is not, in-memory loaded data will be shuffled or not based on this param.

Shuffling of on-disk data is up to the user (controlled by `chunks` parameter in {class}`annbatch.types.LoadRequest`).
Expand All @@ -52,6 +52,21 @@ def shuffle(self) -> bool:
True if data should be shuffled, False otherwise.
"""

@abstractmethod
def n_iters(self, n_obs: int) -> int:
"""Return the number of batches.

Parameters
----------
n_obs
The total number of observations available.

Returns
-------
int
The total number of batches this sampler will produce.
"""

def sample(self, n_obs: int) -> Iterator[LoadRequest]:
"""Sample load requests given the total number of observations.

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2 changes: 1 addition & 1 deletion src/annbatch/loader.py
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Expand Up @@ -213,7 +213,7 @@ def __init__(
self._concat_strategy = concat_strategy

def __len__(self) -> int:
return self.n_obs
return self._batch_sampler.n_iters(self.n_obs)

@property
def _sp_module(self) -> ModuleType:
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5 changes: 5 additions & 0 deletions src/annbatch/samplers/_chunk_sampler.py
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Expand Up @@ -97,6 +97,11 @@ def batch_size(self) -> int:
def shuffle(self) -> bool:
return self._shuffle

def n_iters(self, n_obs: int) -> int:
start, stop = self._mask.start or 0, self._mask.stop or n_obs
total_obs = stop - start
return total_obs // self._batch_size if self._drop_last else math.ceil(total_obs / self._batch_size)

def validate(self, n_obs: int) -> None:
"""Validate the sampler configuration against the loader's n_obs.

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30 changes: 30 additions & 0 deletions tests/test_dataset.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
from __future__ import annotations

import math
from importlib.util import find_spec
from types import NoneType
from typing import TYPE_CHECKING, TypedDict
Expand Down Expand Up @@ -333,6 +334,32 @@ def test_drop_last(adata_with_zarr_path_same_var_space: tuple[ad.AnnData, Path],
np.testing.assert_allclose(X, X_expected)


@pytest.mark.parametrize("drop_last", [True, False], ids=["drop", "kept"])
def test_len(
adata_with_zarr_path_same_var_space: tuple[ad.AnnData, Path],
drop_last: bool,
):
zarr_path = next(adata_with_zarr_path_same_var_space[1].glob("*.zarr"))
data = open_sparse(zarr_path)
n_obs = data["dataset"].shape[0]
batch_size = 32

loader = Loader(
shuffle=False,
batch_size=batch_size,
preload_to_gpu=False,
to_torch=False,
drop_last=drop_last,
)
loader.add_dataset(**data)

expected_len = n_obs // batch_size if drop_last else math.ceil(n_obs / batch_size)
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@ilan-gold ilan-gold Feb 10, 2026

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Put this as a parametrized number explicitly. Also not sure why we're parametrizing on chunk size or number of chunks to preload. Can you remove? Seems unrelated

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@felix0097 felix0097 Feb 10, 2026

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It's supposed to also check the n_iters function of the ChunkSampler. This covers different edge cases. I can remove it, if we only wanna check the n_iters.

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@ilan-gold ilan-gold Feb 10, 2026

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But https://github.com/scverse/annbatch/pull/144/changes#diff-102eacca529505a20b2ae79d187762c2125e058343b16a2452f981a82f7c17bcR100-R103 doesn't use those parameters - it's just batch_size and n_obs dependent along with the mask - so maybe parametrize by mask start/end?

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@felix0097 felix0097 Feb 10, 2026

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ok, so this rathe tests if the ChunkSampler handles this correctly. Thinking about this, this isn't really the point of this test. I've removed it now 👍

assert len(loader) == expected_len
# Also verify len matches the actual number of yielded batches
actual_batches = sum(1 for _ in loader)
assert len(loader) == actual_batches


def test_bad_adata_X_hdf5(adata_with_h5_path_different_var_space: tuple[ad.AnnData, Path]):
with h5py.File(next(adata_with_h5_path_different_var_space[1].glob("*.h5ad"))) as f:
data = ad.io.sparse_dataset(f["X"])
Expand Down Expand Up @@ -579,6 +606,9 @@ class FailOnSecondValidateSampler(Sampler):
def __init__(self):
self._validate_count = 0

def n_iters(self, n_obs: int) -> int:
return math.ceil(n_obs / self.batch_size)

def validate(self, n_obs: int) -> None:
self._validate_count += 1
if self._validate_count > 1:
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7 changes: 7 additions & 0 deletions tests/test_sampler.py
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Expand Up @@ -2,6 +2,8 @@

from __future__ import annotations

import math

import numpy as np
import pytest

Expand Down Expand Up @@ -275,6 +277,11 @@ def batch_size(self) -> int | None:
def shuffle(self) -> bool | None:
return self._shuffle

def n_iters(self, n_obs: int) -> int:
if self._batch_size is None or self._batch_size == 0:
return 1
return math.ceil(n_obs / self._batch_size)

def validate(self, n_obs: int) -> None:
"""No validation needed for test sampler."""
pass
Expand Down
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