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Fix flaky memory usage test by guaranteeing array size. #10114

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Jan 24, 2022
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Fix flaky memory usage test by guaranteeing array size. #10114

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14 changes: 10 additions & 4 deletions python/cudf/cudf/tests/test_dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5474,20 +5474,26 @@ def test_memory_usage_list():
@pytest.mark.parametrize("rows", [10, 100])
def test_memory_usage_multi(rows):
deep = True
# We need to sample without replacement to guarantee that the size of the
# levels are always the same.
df = pd.DataFrame(
{
"A": np.arange(rows, dtype="int32"),
"B": np.random.choice(np.arange(3, dtype="int64"), rows),
"C": np.random.choice(np.arange(3, dtype="float64"), rows),
"B": np.random.choice(
np.arange(rows, dtype="int64"), rows, replace=False
),
"C": np.random.choice(
np.arange(rows, dtype="float64"), rows, replace=False
),
}
).set_index(["B", "C"])
gdf = cudf.from_pandas(df)
# Assume MultiIndex memory footprint is just that
# of the underlying columns, levels, and codes
expect = rows * 16 # Source Columns
expect += rows * 16 # Codes
expect += 3 * 8 # Level 0
expect += 3 * 8 # Level 1
expect += rows * 8 # Level 0
expect += rows * 8 # Level 1

assert expect == gdf.index.memory_usage(deep=deep)

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