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https://github.com/lancedb/lancedb.git
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fix(python): cover FP16 GPU index queries
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@@ -91,19 +91,13 @@ def test_quickstart(tmp_path):
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}
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)
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# --8<-- [end:alter_columns_vector]
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# Change it back since we can get a panic with fp16
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tbl.alter_columns(
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{
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"path": "vector",
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"data_type": pa.list_(pa.float32(), list_size=2),
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}
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)
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# --8<-- [start:drop_columns]
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tbl.drop_columns(["dbl_price"])
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# --8<-- [end:drop_columns]
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# --8<-- [start:create_index]
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tbl.create_index(num_sub_vectors=1)
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# --8<-- [end:create_index]
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tbl.search([100, 100]).limit(2).to_pandas()
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# --8<-- [start:delete_rows]
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tbl.delete('item = "fizz"')
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# --8<-- [end:delete_rows]
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@@ -185,13 +179,6 @@ async def test_quickstart_async(tmp_path):
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}
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)
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# --8<-- [end:alter_columns_async_vector]
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# Change it back since we can get a panic with fp16
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await tbl.alter_columns(
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{
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"path": "vector",
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"data_type": pa.list_(pa.float32(), list_size=2),
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}
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)
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# --8<-- [start:drop_columns_async]
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await tbl.drop_columns(["dbl_price"])
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# --8<-- [end:drop_columns_async]
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@@ -200,6 +187,7 @@ async def test_quickstart_async(tmp_path):
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# --8<-- [start:create_index_async]
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await tbl.create_index("vector")
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# --8<-- [end:create_index_async]
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await tbl.vector_search([100, 100]).limit(2).to_pandas()
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# --8<-- [start:delete_rows_async]
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await tbl.delete('item = "fizz"')
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# --8<-- [end:delete_rows_async]
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@@ -2559,25 +2559,42 @@ def test_create_with_embedding_function(mem_db: DBConnection):
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assert actual == expected
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def test_create_f16_table(mem_db: DBConnection):
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@pytest.mark.parametrize("accelerator", [None, "cuda"])
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def test_create_f16_table(tmp_path, accelerator):
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if accelerator == "cuda":
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torch = pytest.importorskip("torch")
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if not torch.cuda.is_available():
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pytest.skip("CUDA not available")
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class MyTable(LanceModel):
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text: str
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vector: Vector(32, value_type=pa.float16())
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rng = np.random.default_rng(42)
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vectors = rng.standard_normal((512, 32)).astype(np.float16)
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df = pa.table(
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{
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"text": [f"s-{i}" for i in range(512)],
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"vector": [np.random.randn(32).astype(np.float16) for _ in range(512)],
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"vector": list(vectors),
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}
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)
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table = mem_db.create_table(
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db = lancedb.connect(tmp_path)
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table = db.create_table(
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"f16_tbl",
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schema=MyTable,
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)
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table.add(df)
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table.create_index(num_partitions=2, num_sub_vectors=2)
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table.create_index(
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"vector",
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config=IvfPq(
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num_partitions=2,
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num_sub_vectors=2,
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accelerator=accelerator,
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),
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)
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query = df["vector"][2].as_py()
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# Match the issue's float64 query against an explicitly typed float16 column.
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query = vectors[2].astype(np.float64)
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expected = table.search(query).limit(2).to_arrow()
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assert "s-2" in expected["text"].to_pylist()
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