Skip to content

construct the hashtables iteratively to save memory up to B times #2

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
xu3kev wants to merge 1 commit into
base: main
Choose a base branch
from
Open

construct the hashtables iteratively to save memory up to B times #2

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
23 changes: 13 additions & 10 deletions pile/processing/dedup/grouped_dedup.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -225,7 +225,6 @@ def run(
start_time = time.time()
B, R = optimal_param(threshold, num_perm)
HASH_RANGES = [(i * R, (i + 1) * R) for i in range(B)]
HASH_TABLES = [defaultdict(set) for _ in range(B)]
group = []
time_measures["load_dataset"] = time.time()
for name in data[group_name][:2]:
Expand Down Expand Up @@ -279,24 +278,28 @@ def run(
with_indices=True,
desc="Fingerprinting...",
)

time_measures["minhash"] = time.time() - time_measures["minhash"]

time_measures["clustering"] = time.time()
batch_size: int = 10000
for i in tqdm(
range(0, len(embedded), batch_size), dynamic_ncols=True, desc="Iterating MinHashes..." # noqa: E501
):
batch = embedded[i : i + batch_size]
for key, Hs in zip(batch["__id__"], batch["__signatures__"]):
for H, hashtable in zip(Hs, HASH_TABLES):
hashtable[H].add(key)
for table in tqdm(HASH_TABLES, dynamic_ncols=True, desc="Clustering..."):
for cluster in table.values():

for table_idx in range(B):
new_hash_table = defaultdict(set)
for i in tqdm(
range(0, len(embedded), batch_size), dynamic_ncols=True, desc="Iterating MinHashes..." # noqa: E501
):
batch = embedded[i : i + batch_size]
for key, Hs in zip(batch["__id__"], batch["__signatures__"]):
new_hash_table[Hs[table_idx]].add(key)

for cluster in new_hash_table.values():
if len(cluster) <= 1:
continue
idx = min(cluster)
for x in cluster:
uf.union(x, idx)

time_measures["clustering"] = time.time() - time_measures["clustering"]

time_measures["filtering"] = time.time()
Expand Down