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Add type checks to batch size validators #36

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Merged
jp-dark merged 2 commits into from
Aug 13, 2025
Merged

Add type checks to batch size validators #36

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31d1012
Add type checks to batch size validators
jp-dark Aug 8, 2025
c347f1d
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jp-dark Aug 13, 2025
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30 changes: 9 additions & 21 deletions src/tiledbsoma_ml/dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@
import torch
from attr import evolve
from attrs import define, field
from attrs.validators import gt
from attrs.validators import and_, instance_of, gt
from tiledbsoma import ExperimentAxisQuery
from torch.utils.data import IterableDataset

Expand Down Expand Up @@ -117,9 +117,9 @@ class ExperimentDataset(IterableDataset[MiniBatch]): # type: ignore[misc]
"""Names of ``obs`` columns to return."""

# Configuration fields with defaults
batch_size: int = field(default=1, validator=gt(0))
batch_size: int = field(default=1, validator=and_(instance_of(int), gt(0)))
"""Number of rows of ``X`` and ``obs`` data to yield in each |MiniBatch|."""
io_batch_size: int = field(default=DEFAULT_IO_BATCH_SIZE, validator=gt(0))
io_batch_size: int = field(default=DEFAULT_IO_BATCH_SIZE, validator=and_(instance_of(int), gt(0)))
"""Number of ``obs``/``X`` rows to fetch together, when reading from the provided |ExperimentAxisQuery|."""
shuffle: bool = field(default=True)
"""Whether to shuffle the ``obs`` and ``X`` data being returned."""
Expand Down Expand Up @@ -223,9 +223,7 @@ def __init__(
"""
if query and layer_name:
if x_locator or query_ids:
raise ValueError(
"Expected `{query,layer_name}` xor `{x_locator,query_ids}`"
)
raise ValueError("Expected `{query,layer_name}` xor `{x_locator,query_ids}`")
query_ids = QueryIDs.create(query=query)
x_locator = XLocator.create(
query.experiment,
Expand All @@ -234,13 +232,9 @@ def __init__(
)
elif x_locator and query_ids:
if query or layer_name:
raise ValueError(
"Expected `{query,layer_name}` xor `{x_locator,query_ids}`"
)
raise ValueError("Expected `{query,layer_name}` xor `{x_locator,query_ids}`")
else:
raise ValueError(
"Expected `{query,layer_name}` xor `{x_locator,query_ids}`"
)
raise ValueError("Expected `{query,layer_name}` xor `{x_locator,query_ids}`")

self.__attrs_init__(
x_locator=x_locator,
Expand All @@ -264,14 +258,10 @@ def __attrs_post_init__(self) -> None:
if self.shuffle:
# Verify `io_batch_size` is a multiple of `shuffle_chunk_size`
if self.io_batch_size % self.shuffle_chunk_size:
raise ValueError(
f"{self.io_batch_size=} is not a multiple of {self.shuffle_chunk_size=}"
)
raise ValueError(f"{self.io_batch_size=} is not a multiple of {self.shuffle_chunk_size=}")

if self.seed is None:
object.__setattr__(
self, "seed", np.random.default_rng().integers(0, 2**32 - 1)
)
object.__setattr__(self, "seed", np.random.default_rng().integers(0, 2**32 - 1))

# Set distributed state
rank, world_size = get_distributed_rank_and_world_size()
Expand Down Expand Up @@ -425,6 +415,4 @@ def set_epoch(self, epoch: int) -> None:
self.epoch = epoch

def __getitem__(self, index: int) -> MiniBatch:
raise NotImplementedError(
"`Experiment` can only be iterated - does not support mapping"
)
raise NotImplementedError("`Experiment` can only be iterated - does not support mapping")
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