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rename power law sampler to adaptive p

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Concedo
2025-12-27 17:50:58 +08:00
parent 445aad5e00
commit 6548645aaa
5 changed files with 38 additions and 38 deletions
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koboldcpp.py
+4 -4
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@@ -265,7 +265,7 @@ class generation_inputs(ctypes.Structure):
("dynatemp_exponent", ctypes.c_float),
("smoothing_factor", ctypes.c_float),
("smoothing_curve", ctypes.c_float),
("power_law_target", ctypes.c_float),
("adaptive_target", ctypes.c_float),
("dry_multiplier", ctypes.c_float),
("dry_base", ctypes.c_float),
("dry_allowed_length", ctypes.c_int),
@@ -1604,8 +1604,8 @@ def generate(genparams, stream_flag=False):
dynatemp_exponent = tryparsefloat(genparams.get('dynatemp_exponent', 1.0),1.0)
smoothing_factor = tryparsefloat(genparams.get('smoothing_factor', 0.0),0.0)
smoothing_curve = tryparsefloat(genparams.get('smoothing_curve', 1.0),1.0)
power_law_target = tryparsefloat(genparams.get('power_law_target', -1.0),-1.0)
if power_law_target>0 and min_p<=0 and top_p>=1.0: #power law sampler requires a truncation sampler first, force a tiny min-p
adaptive_target = tryparsefloat(genparams.get('adaptive_target', -1.0),-1.0)
if adaptive_target>0 and min_p<=0 and top_p>=1.0: #adaptive p sampler requires a truncation sampler first, force a tiny min-p
min_p = 0.01
logit_biases = genparams.get('logit_bias', {})
render_special = genparams.get('render_special', False)
@@ -1670,7 +1670,7 @@ def generate(genparams, stream_flag=False):
inputs.dynatemp_exponent = dynatemp_exponent
inputs.smoothing_factor = smoothing_factor
inputs.smoothing_curve = smoothing_curve
inputs.power_law_target = power_law_target
inputs.adaptive_target = adaptive_target
inputs.grammar = grammar.encode("UTF-8")
inputs.grammar_retain_state = grammar_retain_state
inputs.allow_eos_token = not ban_eos_token