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perf: use a set for pivot-column lookups #75

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perf: use a set for pivot-column lookups #75

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6 changes: 4 additions & 2 deletions src/bpdecoderplus/batch_osd.py
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Original file line number Diff line number Diff line change
Expand Up @@ -109,12 +109,13 @@ def _evaluate_candidates_gpu(self, candidates: torch.Tensor, augmented: np.ndarr
# Set pivot variables based on target syndromes (vectorized)
# Build pivot row mapping
augmented_torch = torch.from_numpy(augmented[:, :self.num_errors]).to(self.device)
pivot_cols_set = set(pivot_cols)
for r in range(augmented.shape[0]):
# Find pivot column in this row
row_pivots = torch.where(augmented_torch[r, :] == 1)[0]
if len(row_pivots) > 0:
pivot_c = row_pivots[0].item()
if pivot_c in pivot_cols:
if pivot_c in pivot_cols_set:
# Set this pivot variable for all candidates
cand_solutions[:, pivot_c] = target_syndromes[:, r]

Expand Down Expand Up @@ -176,11 +177,12 @@ def solve(self, syndrome: np.ndarray, error_probs: np.ndarray,

# Build the row mapping: the pivot column c corresponds to which row r
pivot_row_map = {}
pivot_cols_set = set(pivot_cols)
for r in range(augmented.shape[0]):
row_pivots = np.where(augmented[r, :self.num_errors] == 1)[0]
if len(row_pivots) > 0:
col = row_pivots[0]
if col in pivot_cols:
if col in pivot_cols_set:
pivot_row_map[col] = r
solution_base[col] = augmented[r, -1]

Expand Down