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feat: Add mmap support for reading sparse vectors to avoid OOM error in CI #129

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Merged
merged 5 commits into from
Apr 17, 2024
Merged

feat: Add mmap support for reading sparse vectors to avoid OOM error in CI #129

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55a3dfb
fix: Manual benchmarks
KShivendu Apr 17, 2024
9faf268
fix: Remove gcs secrets
KShivendu Apr 17, 2024
869024b
feat: Use mmap to read sparse vectors
KShivendu Apr 17, 2024
8e2fd43
fix: Format
KShivendu Apr 17, 2024
63d332c
fix: Make unused var private
KShivendu Apr 17, 2024
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2 changes: 0 additions & 2 deletions .github/workflows/continuous-benchmark.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -18,8 +18,6 @@ jobs:
- name: Benches
run: |
export HCLOUD_TOKEN=${{ secrets.HCLOUD_TOKEN }}
export GCS_KEY=${{ secrets.GCS_KEY }}
export GCS_SECRET=${{ secrets.GCS_SECRET }}
export POSTGRES_PASSWORD=${{ secrets.POSTGRES_PASSWORD }}
export POSTGRES_HOST=${{ secrets.POSTGRES_HOST }}
bash -x tools/setup_ci.sh
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3 changes: 1 addition & 2 deletions .github/workflows/manual-benchmark.yaml
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Expand Up @@ -23,11 +23,10 @@ jobs:
- name: Benches
run: |
export HCLOUD_TOKEN=${{ secrets.HCLOUD_TOKEN }}
export GCS_KEY=${{ secrets.GCS_KEY }}
export GCS_SECRET=${{ secrets.GCS_SECRET }}
export POSTGRES_PASSWORD=${{ secrets.POSTGRES_PASSWORD }}
export POSTGRES_HOST=${{ secrets.POSTGRES_HOST }}
export QDRANT_VERSION=${{ inputs.qdrant_version }}
export DATASETS=${{ inputs.dataset }}
export POSTGRES_TABLE=benchmark_manual
bash -x tools/setup_ci.sh
bash -x tools/run_ci.sh
26 changes: 24 additions & 2 deletions dataset_reader/sparse_reader.py
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Expand Up @@ -23,9 +23,28 @@ def read_sparse_matrix_fields(
return values, columns, index_pointer


def mmap_sparse_matrix_fields(fname):
"""mmap the fields of a CSR matrix without instantiating it"""
with open(fname, "rb") as f:
sizes = np.fromfile(f, dtype="int64", count=3)
n_row, _n_col, n_non_zero = sizes
offset = sizes.nbytes
index_pointer = np.memmap(
fname, dtype="int64", mode="r", offset=offset, shape=n_row + 1
)
offset += index_pointer.nbytes
columns = np.memmap(fname, dtype="int32", mode="r", offset=offset, shape=n_non_zero)
offset += columns.nbytes
values = np.memmap(
fname, dtype="float32", mode="r", offset=offset, shape=n_non_zero
)
return values, columns, index_pointer


def csr_to_sparse_vectors(
values: List[float], columns: List[int], index_pointer: List[int]
) -> Iterator[SparseVector]:
"""Convert a CSR matrix to a list of SparseVectors"""
num_rows = len(index_pointer) - 1

for i in range(num_rows):
Expand All @@ -38,9 +57,12 @@ def csr_to_sparse_vectors(
yield SparseVector(indices=row_indices, values=row_values)


def read_csr_matrix(filename: Union[Path, str]) -> Iterator[SparseVector]:
def read_csr_matrix(filename: Union[Path, str], do_mmap=True) -> Iterator[SparseVector]:
"""Read a CSR matrix in spmat format"""
values, columns, index_pointer = read_sparse_matrix_fields(filename)
if do_mmap:
values, columns, index_pointer = mmap_sparse_matrix_fields(filename)
else:
values, columns, index_pointer = read_sparse_matrix_fields(filename)
values = values.tolist()
columns = columns.tolist()
index_pointer = index_pointer.tolist()
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