ci: Manual Backport of PR 3128 to 1.2.x (#3130)

pop get bug fix data splitter backport 1.2.x

---------

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Co-authored-by: ori-kron-wis <[email protected]>
Co-authored-by: Lumberbot (aka Jack) <[email protected]>
Co-authored-by: Martin Kim <[email protected]>
Co-authored-by: Can Ergen <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Justin Hong <[email protected]>
Co-authored-by: Yishen Miao <[email protected]>
Co-authored-by: Ramon Viñas <[email protected]>
Co-authored-by: Martin Kim <[email protected]>
Co-authored-by: Ethan Weinberger <[email protected]>
Co-authored-by: Ethan Weinberger <[email protected]>
Co-authored-by: access <[email protected]>

Author: 12 people

CHANGELOG.md

@@ -20,6 +20,8 @@ to [Semantic Versioning]. Full commit history is available in the
 
 #### Fixed
 
+- Fixed batch_size pop to get in {class}`scvi.dataloaders.DataSplitter` {pr}`3128`.
+
 #### Changed
 
 - Updated the CI workflow with internet, private and optional tests {pr}`3082`.

docs/tutorials/notebooks

@@ -4,7 +4,7 @@ requires = ["hatchling"]
 
 [project]
 name = "scvi-tools"
-version = "1.2.2.post1"
+version = "1.2.2.post2"
 description = "Deep probabilistic analysis of single-cell omics data."
 readme = "README.md"
 requires-python = ">=3.10"

pyproject.toml

@@ -251,15 +251,15 @@ def __init__(
             self.n_train, self.n_val = validate_data_split_with_external_indexing(
                 self.adata_manager.adata.n_obs,
                 self.external_indexing,
-                self.data_loader_kwargs.pop("batch_size", settings.batch_size),
+                self.data_loader_kwargs.get("batch_size", settings.batch_size),
                 self.drop_last,
             )
         else:
             self.n_train, self.n_val = validate_data_split(
                 self.adata_manager.adata.n_obs,
                 self.train_size,
                 self.validation_size,
-                self.data_loader_kwargs.pop("batch_size", settings.batch_size),
+                self.data_loader_kwargs.get("batch_size", settings.batch_size),
                 self.drop_last,
                 self.train_size_is_none,
             )
@@ -434,15 +434,15 @@ def setup(self, stage: str | None = None):
                 n_labeled_train, n_labeled_val = validate_data_split_with_external_indexing(
                     n_labeled_idx,
                     [labeled_idx_train, labeled_idx_val, labeled_idx_test],
-                    self.data_loader_kwargs.pop("batch_size", settings.batch_size),
+                    self.data_loader_kwargs.get("batch_size", settings.batch_size),
                     self.drop_last,
                 )
             else:
                 n_labeled_train, n_labeled_val = validate_data_split(
                     n_labeled_idx,
                     self.train_size,
                     self.validation_size,
-                    self.data_loader_kwargs.pop("batch_size", settings.batch_size),
+                    self.data_loader_kwargs.get("batch_size", settings.batch_size),
                     self.drop_last,
                     self.train_size_is_none,
                 )
@@ -475,15 +475,15 @@ def setup(self, stage: str | None = None):
                 n_unlabeled_train, n_unlabeled_val = validate_data_split_with_external_indexing(
                     n_unlabeled_idx,
                     [unlabeled_idx_train, unlabeled_idx_val, unlabeled_idx_test],
-                    self.data_loader_kwargs.pop("batch_size", settings.batch_size),
+                    self.data_loader_kwargs.get("batch_size", settings.batch_size),
                     self.drop_last,
                 )
             else:
                 n_unlabeled_train, n_unlabeled_val = validate_data_split(
                     n_unlabeled_idx,
                     self.train_size,
                     self.validation_size,
-                    self.data_loader_kwargs.pop("batch_size", settings.batch_size),
+                    self.data_loader_kwargs.get("batch_size", settings.batch_size),
                     self.drop_last,
                     self.train_size_is_none,
                 )

src/scvi/dataloaders/_data_splitting.py

@@ -474,8 +474,7 @@ def test_scvi_n_obs_error(n_latent: int = 5):
     with pytest.raises(ValueError):
         model.train(1, train_size=1.0)
     with pytest.raises(ValueError):
-        # Warning is emitted if last batch less than 3 cells + failure.
-        model.train(1, train_size=1.0, batch_size=127)
+        model.train(1, train_size=1.0, batch_size=128)
     model.train(1, train_size=1.0, datasplitter_kwargs={"drop_last": True})
 
     adata = synthetic_iid()
@@ -484,9 +483,7 @@ def test_scvi_n_obs_error(n_latent: int = 5):
     model = SCVI(adata, n_latent=n_latent)
     with pytest.raises(ValueError):
         model.train(1, train_size=0.9)  # np.ceil(n_cells * 0.9) % 128 == 1
-    model.train(
-        1, train_size=0.9, datasplitter_kwargs={"drop_last": True}
-    )  # np.ceil(n_cells * 0.9) % 128 == 1
+    model.train(1, train_size=0.9, datasplitter_kwargs={"drop_last": True})
     model.train(1)
     assert model.is_trained is True