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⚡️ Speed up function longest_increasing_subsequence_length by 40,778% #1072

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⚡️ Speed up function longest_increasing_subsequence_length by 40,778% #1072

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22 changes: 11 additions & 11 deletions code_to_optimize/sample_code.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import bisect
from functools import partial

import jax.numpy as jnp
Expand Down Expand Up @@ -97,19 +98,18 @@ def longest_increasing_subsequence_length(arr: np.ndarray) -> int:
if n == 0:
return 0

dp = np.ones(n, dtype=np.int64)
# Use patience sorting / tails method for O(n log n) time.
tails = [] # tails[k] = smallest tail value of an increasing subsequence of length k+1

for i in range(1, n):
for j in range(i):
if arr[j] < arr[i]:
if dp[j] + 1 > dp[i]:
dp[i] = dp[j] + 1

max_length = dp[0]
for i in range(1, n):
if dp[i] > max_length:
max_length = dp[i]
for x in arr:
# Find the insertion point for x in tails to maintain sorted order.
i = bisect.bisect_left(tails, x)
if i == len(tails):
tails.append(x)
else:
tails[i] = x

max_length = np.int64(len(tails))
return max_length


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