Convert SamplingParams to msgspec Struct (#29198)
Co-authored-by: Rain Jiang <96632942+rainj-me@users.noreply.github.com>
This commit is contained in:
co-authored by
Rain Jiang
parent
d5e9176f65
commit
fd87a85388
@@ -15,7 +15,9 @@
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import logging
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import math
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from typing import Any, Dict, List, Optional, Union
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from typing import Any, Dict, List, Optional, Set, Union
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import msgspec
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# sre_parse is deprecated in Python 3.11+, use re._parser instead
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try:
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@@ -59,7 +61,7 @@ def raise_if_tokenizer_required(
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)
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class SamplingParams:
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class SamplingParams(msgspec.Struct, kw_only=True, omit_defaults=True):
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"""
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The sampling parameters.
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@@ -68,77 +70,89 @@ class SamplingParams:
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for the documentation.
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"""
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def __init__(
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self,
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max_new_tokens: int = 128,
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stop: Optional[Union[str, List[str]]] = None,
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stop_token_ids: Optional[List[int]] = None,
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stop_regex: Optional[Union[str, List[str]]] = None,
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temperature: float = 1.0,
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top_p: float = 1.0,
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top_k: int = -1,
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min_p: float = 0.0,
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frequency_penalty: float = 0.0,
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presence_penalty: float = 0.0,
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repetition_penalty: float = 1.0,
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min_new_tokens: int = 0,
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n: int = 1,
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json_schema: Optional[str] = None,
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regex: Optional[str] = None,
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ebnf: Optional[str] = None,
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structural_tag: Optional[str] = None,
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ignore_eos: bool = False,
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skip_special_tokens: bool = True,
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spaces_between_special_tokens: bool = True,
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no_stop_trim: bool = False,
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custom_params: Optional[Dict[str, Any]] = None,
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stream_interval: Optional[int] = None,
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logit_bias: Optional[Dict[str, float]] = None,
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sampling_seed: Optional[int] = None,
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) -> None:
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# --- API parameters (set by callers) ---
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max_new_tokens: Optional[int] = 128
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stop: Optional[Union[str, List[str]]] = (
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None # API input alias, copied to stop_strs then cleared in normalize()
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)
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stop_token_ids: Optional[Set[int]] = None
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stop_regex: Optional[Union[str, List[str]]] = (
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None # API input alias, copied to stop_regex_strs then cleared in normalize()
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)
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temperature: float = 1.0
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top_p: float = 1.0
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top_k: int = TOP_K_ALL
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min_p: float = 0.0
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frequency_penalty: float = 0.0
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presence_penalty: float = 0.0
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repetition_penalty: float = 1.0
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min_new_tokens: int = 0
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n: int = 1
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json_schema: Optional[str] = None
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regex: Optional[str] = None
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ebnf: Optional[str] = None
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structural_tag: Optional[str] = None
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ignore_eos: bool = False
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skip_special_tokens: bool = True
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spaces_between_special_tokens: bool = True
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no_stop_trim: bool = False
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custom_params: Optional[Dict[str, Any]] = None
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stream_interval: Optional[int] = None
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logit_bias: Optional[Dict[str, float]] = None
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sampling_seed: Optional[int] = None
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# --- Internal fields (populated by __post_init__ or normalize(), not API-facing) ---
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stop_strs: Optional[Union[str, List[str]]] = None # from stop
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stop_regex_strs: Optional[Union[str, List[str]]] = None # from stop_regex
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stop_str_max_len: int = 0 # set by normalize()
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stop_regex_max_len: int = 0 # set by normalize()
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is_normalized: bool = False # set by normalize()
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def __post_init__(self):
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# For non-optional params, treat None as "use default" so that callers
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# (e.g. /generate) can pass null without crashing verify().
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self.max_new_tokens = max_new_tokens
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self.stop_strs = stop
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if stop_token_ids:
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filtered = {int(t) for t in stop_token_ids if t is not None}
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# msgspec calls __post_init__ after deserialization. Once normalize()
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# has populated tokenizer-derived fields, avoid resetting them.
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if self.is_normalized:
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return
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self.stop_strs = self.stop
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if self.stop_token_ids:
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filtered = {int(t) for t in self.stop_token_ids if t is not None}
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self.stop_token_ids = filtered or None
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else:
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self.stop_token_ids = None
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self.stop_regex_strs = stop_regex
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self.temperature = temperature if temperature is not None else 1.0
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self.top_p = top_p if top_p is not None else 1.0
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self.top_k = top_k if top_k is not None else -1
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self.min_p = min_p if min_p is not None else 0.0
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self.stop_regex_strs = self.stop_regex
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self.temperature = self.temperature if self.temperature is not None else 1.0
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self.top_p = self.top_p if self.top_p is not None else 1.0
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self.top_k = self.top_k if self.top_k is not None else -1
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self.min_p = self.min_p if self.min_p is not None else 0.0
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self.frequency_penalty = (
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frequency_penalty if frequency_penalty is not None else 0.0
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self.frequency_penalty if self.frequency_penalty is not None else 0.0
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)
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self.presence_penalty = (
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presence_penalty if presence_penalty is not None else 0.0
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self.presence_penalty if self.presence_penalty is not None else 0.0
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)
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self.repetition_penalty = (
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repetition_penalty if repetition_penalty is not None else 1.0
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self.repetition_penalty if self.repetition_penalty is not None else 1.0
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)
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self.min_new_tokens = min_new_tokens if min_new_tokens is not None else 0
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self.regex = regex
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self.n = n if n is not None else 1
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self.json_schema = json_schema
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self.ebnf = ebnf
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self.structural_tag = structural_tag
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self.ignore_eos = ignore_eos if ignore_eos is not None else False
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self.min_new_tokens = (
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self.min_new_tokens if self.min_new_tokens is not None else 0
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)
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self.n = self.n if self.n is not None else 1
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self.ignore_eos = self.ignore_eos if self.ignore_eos is not None else False
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self.skip_special_tokens = (
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skip_special_tokens if skip_special_tokens is not None else True
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self.skip_special_tokens if self.skip_special_tokens is not None else True
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)
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self.spaces_between_special_tokens = (
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spaces_between_special_tokens
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if spaces_between_special_tokens is not None
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self.spaces_between_special_tokens
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if self.spaces_between_special_tokens is not None
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else True
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)
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self.no_stop_trim = no_stop_trim if no_stop_trim is not None else False
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self.custom_params = custom_params
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self.stream_interval = stream_interval
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self.logit_bias = logit_bias
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self.sampling_seed = sampling_seed
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self.no_stop_trim = (
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self.no_stop_trim if self.no_stop_trim is not None else False
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)
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# Process some special cases
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if 0 <= self.temperature < _SAMPLING_EPS:
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@@ -245,6 +259,11 @@ class SamplingParams:
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tokenizer, self.stop_strs, self.stop_regex_strs, self.min_new_tokens
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)
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# Clear API input aliases so omit_defaults=True drops them from the wire.
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self.stop = None
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self.stop_regex = None
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self.is_normalized = True
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# This function gets a strict upperbound on the maximum number of tokens that would need
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# to be buffered to match the input regex string
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@@ -38,7 +38,7 @@ _TARGET_BACKENDS = {HWBackend.CUDA, HWBackend.CPU}
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# base-a is the critical-path entry gate; pin its fanout to smoke-coverage
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# defaults instead of est_time. max_parallel = size (no throttle).
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_BASE_A_OVERRIDES = {
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"base-a-test-cpu": 4,
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"base-a-test-cpu": 8,
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"base-a-test-1-gpu-small": 1,
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}
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@@ -6,9 +6,12 @@ register_cpu_ci(est_time=7, suite="base-a-test-cpu")
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register_cpu_ci(est_time=7, suite="base-c-test-cpu")
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register_xpu_ci(est_time=10, suite="stage-a-test-1-gpu-xpu")
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import copy
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import unittest
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from unittest.mock import MagicMock
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import msgspec
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from sglang.srt.sampling.sampling_params import (
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MAX_LEN,
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TOP_K_ALL,
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@@ -363,6 +366,84 @@ class TestSamplingParamsNormalize(CustomTestCase):
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self.assertEqual(sp.stop_regex_max_len, 3)
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class TestSamplingParamsMsgspecStruct(CustomTestCase):
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def test_copy_remains_mutable_and_independent(self):
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sp = SamplingParams(max_new_tokens=8, custom_params={"a": 1})
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copied = copy.copy(sp)
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copied.max_new_tokens = 16
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copied.custom_params = {"b": 2}
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self.assertEqual(sp.max_new_tokens, 8)
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self.assertEqual(sp.custom_params, {"a": 1})
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self.assertEqual(copied.max_new_tokens, 16)
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self.assertEqual(copied.custom_params, {"b": 2})
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def test_none_values_still_use_constructor_defaults(self):
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sp = SamplingParams(
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temperature=None,
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top_p=None,
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top_k=None,
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min_p=None,
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frequency_penalty=None,
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presence_penalty=None,
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repetition_penalty=None,
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min_new_tokens=None,
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n=None,
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ignore_eos=None,
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skip_special_tokens=None,
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spaces_between_special_tokens=None,
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no_stop_trim=None,
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)
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self.assertEqual(sp.temperature, 1.0)
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self.assertEqual(sp.top_p, 1.0)
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self.assertEqual(sp.top_k, TOP_K_ALL)
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self.assertEqual(sp.min_p, 0.0)
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self.assertEqual(sp.frequency_penalty, 0.0)
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self.assertEqual(sp.presence_penalty, 0.0)
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self.assertEqual(sp.repetition_penalty, 1.0)
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self.assertEqual(sp.min_new_tokens, 0)
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self.assertEqual(sp.n, 1)
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self.assertFalse(sp.ignore_eos)
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self.assertTrue(sp.skip_special_tokens)
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self.assertTrue(sp.spaces_between_special_tokens)
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self.assertFalse(sp.no_stop_trim)
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def test_msgpack_omits_default_fields(self):
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encoded = msgspec.msgpack.encode(SamplingParams())
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self.assertEqual(msgspec.msgpack.decode(encoded), {})
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def test_msgpack_round_trip_preserves_normalized_state(self):
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tokenizer = MagicMock()
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tokenizer.encode.side_effect = lambda s, add_special_tokens=False: {
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"hello": [101, 102],
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"world": [201],
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}[s]
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sp = SamplingParams(
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stop=["hello", "world"],
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stop_regex=r"[a-z]{3}",
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stop_token_ids=[1, 2],
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temperature=0.5,
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)
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sp.normalize(tokenizer)
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encoder = msgspec.msgpack.Encoder()
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decoder = msgspec.msgpack.Decoder(SamplingParams)
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rebuilt = decoder.decode(encoder.encode(sp))
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self.assertIsInstance(rebuilt, SamplingParams)
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self.assertTrue(rebuilt.is_normalized)
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self.assertEqual(rebuilt.stop_strs, ["hello", "world"])
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self.assertEqual(rebuilt.stop_str_max_len, 2)
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self.assertEqual(rebuilt.stop_regex_strs, [r"[a-z]{3}"])
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self.assertEqual(rebuilt.stop_regex_max_len, 3)
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self.assertEqual(rebuilt.stop_token_ids, {1, 2})
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self.assertEqual(rebuilt.temperature, 0.5)
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class TestRegexMaxLength(CustomTestCase):
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def test_literal_string(self):
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