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d9af7ee | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 | """Legacy single-constraint patching helpers kept for backward compatibility."""
from __future__ import annotations
from typing import List
import numpy as np
def patch_global_threshold(metric: np.ndarray, threshold: float) -> List[List[int]]:
"""
Patch when metric exceeds threshold.
Args:
metric: Entropy or perplexity values
threshold: Threshold value
Returns:
List of patches (each patch is list of token indices)
"""
patches = []
current_patch = []
for i, value in enumerate(metric):
current_patch.append(i)
if value > threshold:
patches.append(current_patch)
current_patch = []
if current_patch:
patches.append(current_patch)
return patches
def patch_additive_monotonic(metric: np.ndarray, threshold: float) -> List[List[int]]:
"""Patch when metric increase exceeds threshold."""
patches = []
current_patch = [0]
for i in range(1, len(metric)):
delta = metric[i] - metric[i - 1]
if delta > threshold:
patches.append(current_patch)
current_patch = [i]
else:
current_patch.append(i)
if current_patch:
patches.append(current_patch)
return patches
def patch_multiplicative_monotonic(metric: np.ndarray, threshold: float) -> List[List[int]]:
"""Patch when metric ratio exceeds threshold."""
patches = []
current_patch = [0]
for i in range(1, len(metric)):
if metric[i - 1] > 1e-6:
ratio = metric[i] / metric[i - 1]
else:
ratio = 1.0
if ratio > threshold:
patches.append(current_patch)
current_patch = [i]
else:
current_patch.append(i)
if current_patch:
patches.append(current_patch)
return patches
def patch_additive_min(metric: np.ndarray, threshold: float) -> List[List[int]]:
"""Patch when metric increase from minimum in current patch exceeds threshold."""
patches = []
current_patch = [0]
patch_min = metric[0]
for i in range(1, len(metric)):
delta = metric[i] - patch_min
if delta > threshold:
patches.append(current_patch)
current_patch = [i]
patch_min = metric[i]
else:
current_patch.append(i)
patch_min = min(patch_min, metric[i])
if current_patch:
patches.append(current_patch)
return patches
def patch_multiplicative_min(metric: np.ndarray, threshold: float) -> List[List[int]]:
"""Patch when metric ratio to minimum in current patch exceeds threshold."""
patches = []
current_patch = [0]
patch_min = metric[0]
for i in range(1, len(metric)):
if patch_min > 1e-6:
ratio = metric[i] / patch_min
else:
ratio = 1.0
if ratio > threshold:
patches.append(current_patch)
current_patch = [i]
patch_min = metric[i]
else:
current_patch.append(i)
patch_min = min(patch_min, metric[i])
if current_patch:
patches.append(current_patch)
return patches
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