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Closes #3245. > **BREAKING CHANGE:** `with_format("torch")` no longer returns a list of stacked row tensors. It now returns per-row dicts so PyTorch's default `DataLoader` collate stacks them into `{col: tensor(B,)}`. Switch to `with_format("torch_row")` to keep the old shape. ### What changed `"torch"` now returns a list of per-row dicts (`[{col: tensor}, ...]`) at every indexed access path. The default `DataLoader` collate stacks them into a column-keyed batched dict, no custom `collate_fn` needed. The old shape is preserved under a new `"torch_row"` literal. `"torch_col"` is unchanged. The unbatching lives inside the transform (`batch_to_tensor_dict`), not `__getitems__`, so the shape survives pickling and works under `DataLoader(num_workers>0, multiprocessing_context="spawn")`. ### Format comparison | Format | `iter(batch_size=N)` | `__getitems__([0,1,2])` | `DataLoader` default collate | |---|---|---|---| | `"torch"` (new) | `list[{col: tensor}]` length N | `list[{col: tensor}]` length 3 | `{col: tensor(B,)}` | | `"torch_row"` (old `"torch"` behavior) | `list[tensor(n_cols,)]` length N | `list[tensor(n_cols,)]` length 3 | `tensor(B, n_cols)` | | `"torch_col"` (unchanged) | `tensor(n_cols, N)` | `tensor(n_cols, 3)` | needs `collate_fn=lambda x: x` | Output matches HuggingFace `Dataset.set_format("torch")` on container shape, keys, and values at every access path. The only divergence: HuggingFace downcasts `float64` to `torch.float32` by default, LanceDB preserves dtype. Verified by `scripts/verify_torch_format.py`. ### Migration ```python # Old default — column names lost, shape was tensor(B, n_cols) DataLoader(Permutation.identity(table).with_format("torch")) # New default — column names preserved DataLoader(Permutation.identity(table).with_format("torch")) # {col: tensor(B,)} # Keep old behavior DataLoader(Permutation.identity(table).with_format("torch_row")) # tensor(B, n_cols) ```
LanceDB Python SDK
A Python library for LanceDB.
Installation
pip install lancedb
Preview Releases
Stable releases are created about every 2 weeks. For the latest features and bug fixes, you can install the preview release. These releases receive the same level of testing as stable releases, but are not guaranteed to be available for more than 6 months after they are released. Once your application is stable, we recommend switching to stable releases.
pip install --pre --extra-index-url https://pypi.fury.io/lancedb/ lancedb
Usage
Basic Example
import lancedb
db = lancedb.connect('<PATH_TO_LANCEDB_DATASET>')
table = db.open_table('my_table')
results = table.search([0.1, 0.3]).limit(20).to_list()
print(results)
Development
See CONTRIBUTING.md for information on how to contribute to LanceDB.