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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

525 行
21 KiB
Python

"""Unit tests for srt/sampling/sampling_params.py — no server, no model loading."""
from sglang.test.ci.ci_register import register_cpu_ci, register_xpu_ci
register_cpu_ci(est_time=7, suite="base-a-test-cpu")
register_cpu_ci(est_time=7, suite="base-c-test-cpu")
register_xpu_ci(est_time=10, suite="stage-a-test-1-gpu-xpu")
import copy
import unittest
from unittest.mock import MagicMock
import msgspec
from sglang.srt.sampling.sampling_params import (
MAX_LEN,
TOP_K_ALL,
SamplingParams,
get_max_seq_length,
)
from sglang.test.test_utils import CustomTestCase
class TestSamplingParamsInit(CustomTestCase):
def test_zero_temperature_becomes_greedy(self):
"""Test greedy conversion when temperature is 0."""
sp = SamplingParams(temperature=0.0)
self.assertEqual(sp.top_k, 1)
self.assertEqual(sp.temperature, 1.0)
def test_near_zero_temperature_becomes_greedy(self):
"""Test greedy conversion when temperature is near zero (1e-7)."""
sp = SamplingParams(temperature=1e-7)
self.assertEqual(sp.top_k, 1)
self.assertEqual(sp.temperature, 1.0)
def test_temperature_at_eps_boundary_not_greedy(self):
"""Test that temperature exactly at 1e-6 does not trigger greedy (strict <)."""
sp = SamplingParams(temperature=1e-6)
self.assertEqual(sp.temperature, 1e-6)
# top_k should remain at TOP_K_ALL (from -1 default)
self.assertEqual(sp.top_k, TOP_K_ALL)
def test_negative_temperature_not_modified(self):
"""Test that __init__ preserves negative temperature (rejected by verify instead)."""
sp = SamplingParams(temperature=-1.0)
self.assertEqual(sp.temperature, -1.0)
def test_top_k_minus_one_becomes_top_k_all(self):
"""Test that top_k=-1 is converted to TOP_K_ALL (whole vocabulary)."""
sp = SamplingParams(top_k=-1)
self.assertEqual(sp.top_k, TOP_K_ALL)
def test_positive_top_k_preserved(self):
"""Test that explicit positive top_k is kept as-is."""
sp = SamplingParams(top_k=50)
self.assertEqual(sp.top_k, 50)
def test_stop_token_ids_stored_as_set(self):
"""Test that stop_token_ids list is converted to set."""
sp = SamplingParams(stop_token_ids=[1, 2, 3])
self.assertIsInstance(sp.stop_token_ids, set)
self.assertEqual(sp.stop_token_ids, {1, 2, 3})
def test_stop_token_ids_none_stays_none(self):
"""Test that None stop_token_ids stays None."""
sp = SamplingParams(stop_token_ids=None)
self.assertIsNone(sp.stop_token_ids)
def test_empty_stop_token_ids_becomes_none(self):
"""Test that empty list is treated as None (falsy in Python)."""
sp = SamplingParams(stop_token_ids=[])
self.assertIsNone(sp.stop_token_ids)
class TestSamplingParamsVerify(CustomTestCase):
VOCAB_SIZE = 32000
def _make(self, **kwargs):
"""Helper: create SamplingParams with safe defaults, override with kwargs."""
defaults = dict(temperature=1.0, top_p=1.0, top_k=10, min_p=0.0)
defaults.update(kwargs)
return SamplingParams(**defaults)
def test_valid_params_pass(self):
"""Default valid params should pass verify() without raising."""
sp = self._make()
sp.verify(self.VOCAB_SIZE)
def test_negative_temperature_raises(self):
"""Test that verify() rejects negative temperature (must be >= 0)."""
sp = self._make(temperature=-0.5)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_nan_temperature_raises(self):
"""verify() must reject NaN temperature; the bare < 0.0 check alone lets it through."""
sp = self._make(temperature=float("nan"))
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_inf_temperature_raises(self):
"""verify() must reject non-finite (inf) temperature."""
sp = self._make(temperature=float("inf"))
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
# --- top_p ---
def test_top_p_negative_raises(self):
"""Test that verify() rejects negative top_p (valid range is (0, 1])."""
sp = self._make(top_p=-0.5)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_top_p_zero_raises(self):
"""Test that verify() rejects top_p=0 (not in (0, 1])."""
sp = self._make(top_p=0.0)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_top_p_above_one_raises(self):
"""Test that verify() rejects top_p > 1.0."""
sp = self._make(top_p=1.1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_top_p_exactly_one_is_valid(self):
"""Test that top_p=1.0 is accepted (inclusive upper bound)."""
sp = self._make(top_p=1.0)
sp.verify(self.VOCAB_SIZE)
def test_top_p_small_positive_is_valid(self):
"""Test that a small positive top_p (0.01) is accepted."""
sp = self._make(top_p=0.01)
sp.verify(self.VOCAB_SIZE)
# --- min_p ---
def test_min_p_negative_raises(self):
"""Test that verify() rejects negative min_p (valid range is [0, 1])."""
sp = self._make(min_p=-0.1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_min_p_above_one_raises(self):
"""Test that verify() rejects min_p > 1.0."""
sp = self._make(min_p=1.01)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_min_p_boundaries_valid(self):
"""Test that both 0.0 and 1.0 are accepted."""
self._make(min_p=0.0).verify(self.VOCAB_SIZE)
self._make(min_p=1.0).verify(self.VOCAB_SIZE)
def test_top_k_zero_raises(self):
"""Test that verify() rejects top_k=0 (must be >=1 or -1 for all)."""
sp = self._make()
sp.top_k = 0 # bypass __init__ conversion
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_top_k_negative_raises(self):
"""Test that top_k=-2 is rejected (__init__ only converts -1)."""
sp = self._make()
sp.top_k = -2 # bypass __init__ conversion
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
# --- frequency_penalty ---
def test_frequency_penalty_below_minus_two_raises(self):
"""Test that verify() rejects frequency_penalty < -2.0."""
sp = self._make(frequency_penalty=-2.1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_frequency_penalty_above_two_raises(self):
"""Test that verify() rejects frequency_penalty > 2.0."""
sp = self._make(frequency_penalty=2.1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_frequency_penalty_boundaries_valid(self):
"""Test that both -2.0 and 2.0 are accepted."""
self._make(frequency_penalty=-2.0).verify(self.VOCAB_SIZE)
self._make(frequency_penalty=2.0).verify(self.VOCAB_SIZE)
# --- presence_penalty ---
def test_presence_penalty_out_of_range_raises(self):
"""Test that verify() rejects presence_penalty outside [-2, 2]."""
sp = self._make(presence_penalty=2.5)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
# --- repetition_penalty ---
def test_repetition_penalty_negative_raises(self):
"""Test that verify() rejects negative repetition_penalty (valid range is (0, 2])."""
sp = self._make(repetition_penalty=-0.1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_repetition_penalty_zero_raises(self):
"""Test that verify() rejects repetition_penalty=0.
A value of 0 makes the sampling kernel divide logits by 0, producing
inf/NaN in the probability tensor and crashing every TP rank with a
device-side assert.
"""
sp = self._make(repetition_penalty=0.0)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_repetition_penalty_above_two_raises(self):
"""Test that verify() rejects repetition_penalty > 2.0."""
sp = self._make(repetition_penalty=2.1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_repetition_penalty_boundary_two_valid(self):
"""Test that the upper boundary value 2.0 is accepted."""
self._make(repetition_penalty=2.0).verify(self.VOCAB_SIZE)
def test_repetition_penalty_small_positive_valid(self):
"""Test that a small positive repetition_penalty (e.g. 1e-3) is accepted."""
self._make(repetition_penalty=1e-3).verify(self.VOCAB_SIZE)
# --- min_new_tokens / max_new_tokens ---
def test_negative_min_new_tokens_raises(self):
"""Test that verify() rejects negative min_new_tokens."""
sp = self._make(min_new_tokens=-1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_negative_max_new_tokens_raises(self):
"""Test that verify() rejects negative max_new_tokens."""
sp = self._make(max_new_tokens=-1)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_min_exceeds_max_new_tokens_raises(self):
"""Test that verify() rejects min_new_tokens > max_new_tokens."""
sp = self._make(min_new_tokens=100, max_new_tokens=50)
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_min_equals_max_new_tokens_valid(self):
"""Test that min_new_tokens == max_new_tokens is accepted."""
sp = self._make(min_new_tokens=10, max_new_tokens=10)
sp.verify(self.VOCAB_SIZE)
def test_max_new_tokens_none_skips_validation(self):
"""Test that max_new_tokens=None skips the min<=max check."""
sp = self._make(min_new_tokens=9999, max_new_tokens=None)
sp.verify(self.VOCAB_SIZE) # should not raise
# --- logit_bias ---
def test_logit_bias_token_exceeds_vocab_raises(self):
"""Test that verify() rejects logit_bias with token_id >= vocab_size."""
sp = self._make(logit_bias={"99999": 1.0})
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_logit_bias_negative_token_raises(self):
"""Test that verify() rejects logit_bias with negative token_id."""
sp = self._make(logit_bias={"-1": 1.0})
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_logit_bias_valid_tokens(self):
"""Test that logit_bias with token_ids within [0, vocab_size) is accepted."""
sp = self._make(logit_bias={"0": 1.0, "31999": -0.5})
sp.verify(self.VOCAB_SIZE)
def test_multiple_grammars_raises(self):
"""Test that verify() rejects setting both json_schema and regex (mutually exclusive)."""
sp = self._make(json_schema='{"type":"object"}', regex="abc")
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
def test_single_grammar_valid(self):
"""Test that setting only one grammar type is accepted."""
sp = self._make(json_schema='{"type":"object"}')
sp.verify(self.VOCAB_SIZE)
def test_all_three_grammars_set_raises(self):
"""Test that verify() rejects setting json_schema, regex, and ebnf together."""
sp = self._make(json_schema="{}", regex="a", ebnf="rule")
with self.assertRaises(ValueError):
sp.verify(self.VOCAB_SIZE)
class TestSamplingParamsNormalize(CustomTestCase):
def _mock_tokenizer(self, encode_map=None):
"""Create a mock tokenizer that returns predetermined token lists."""
tokenizer = MagicMock()
if encode_map:
tokenizer.encode.side_effect = (
lambda s, add_special_tokens=False: encode_map.get(s, [1])
)
else:
tokenizer.encode.return_value = [1] # Default: 1 token
return tokenizer
def test_none_stop_strs_becomes_empty_list(self):
"""Test that normalize() converts None stop to empty list with max_len=0."""
sp = SamplingParams(stop=None)
sp.normalize(tokenizer=None)
self.assertEqual(sp.stop_strs, [])
self.assertEqual(sp.stop_str_max_len, 0)
def test_string_stop_str_wrapped_in_list(self):
"""Test that normalize() wraps a single stop string into a list."""
sp = SamplingParams(stop="<|end|>")
tokenizer = self._mock_tokenizer()
sp.normalize(tokenizer=tokenizer)
self.assertEqual(sp.stop_strs, ["<|end|>"])
def test_list_stop_strs_unchanged(self):
"""Test that normalize() preserves a list of stop strings as-is."""
sp = SamplingParams(stop=["stop1", "stop2"])
tokenizer = self._mock_tokenizer()
sp.normalize(tokenizer=tokenizer)
self.assertEqual(sp.stop_strs, ["stop1", "stop2"])
def test_stop_str_max_len_uses_encoded_length(self):
"""Test that max_len is based on encoded token count, not character count."""
# "ab" encodes to 1 token, "cdef" encodes to 2 tokens
tokenizer = self._mock_tokenizer(encode_map={"ab": [1], "cdef": [2, 3]})
sp = SamplingParams(stop=["ab", "cdef"])
sp.normalize(tokenizer=tokenizer)
self.assertEqual(sp.stop_str_max_len, 2) # max token count
def test_stop_str_max_len_with_tokenizer(self):
"""Test that with a tokenizer, max_len counts encoded token IDs."""
tokenizer = MagicMock()
# "hello" encodes to 2 tokens, "world!!" to 3 tokens
tokenizer.encode.side_effect = lambda s, add_special_tokens=False: {
"hello": [101, 102],
"world!!": [201, 202, 203],
}[s]
sp = SamplingParams(stop=["hello", "world!!"])
sp.normalize(tokenizer=tokenizer)
self.assertEqual(sp.stop_str_max_len, 3)
def test_none_stop_regex_becomes_empty_list(self):
"""Test that normalize() converts None stop_regex to empty list with max_len=0."""
sp = SamplingParams(stop_regex=None)
sp.normalize(tokenizer=None)
self.assertEqual(sp.stop_regex_strs, [])
self.assertEqual(sp.stop_regex_max_len, 0)
def test_string_stop_regex_wrapped_in_list(self):
"""Test that normalize() wraps a single stop_regex string into a list."""
sp = SamplingParams(stop_regex=r"\d+")
tokenizer = self._mock_tokenizer()
sp.normalize(tokenizer=tokenizer)
self.assertEqual(sp.stop_regex_strs, [r"\d+"])
def test_stop_regex_max_len_computed(self):
"""Test that bounded regex computes a finite max length."""
sp = SamplingParams(stop_regex=r"[a-z]{3}")
tokenizer = self._mock_tokenizer()
sp.normalize(tokenizer=tokenizer)
self.assertEqual(sp.stop_regex_max_len, 3)
class TestSamplingParamsMsgspecStruct(CustomTestCase):
def test_copy_remains_mutable_and_independent(self):
sp = SamplingParams(max_new_tokens=8, custom_params={"a": 1})
copied = copy.copy(sp)
copied.max_new_tokens = 16
copied.custom_params = {"b": 2}
self.assertEqual(sp.max_new_tokens, 8)
self.assertEqual(sp.custom_params, {"a": 1})
self.assertEqual(copied.max_new_tokens, 16)
self.assertEqual(copied.custom_params, {"b": 2})
def test_none_values_still_use_constructor_defaults(self):
sp = SamplingParams(
temperature=None,
top_p=None,
top_k=None,
min_p=None,
frequency_penalty=None,
presence_penalty=None,
repetition_penalty=None,
min_new_tokens=None,
n=None,
ignore_eos=None,
skip_special_tokens=None,
spaces_between_special_tokens=None,
no_stop_trim=None,
)
self.assertEqual(sp.temperature, 1.0)
self.assertEqual(sp.top_p, 1.0)
self.assertEqual(sp.top_k, TOP_K_ALL)
self.assertEqual(sp.min_p, 0.0)
self.assertEqual(sp.frequency_penalty, 0.0)
self.assertEqual(sp.presence_penalty, 0.0)
self.assertEqual(sp.repetition_penalty, 1.0)
self.assertEqual(sp.min_new_tokens, 0)
self.assertEqual(sp.n, 1)
self.assertFalse(sp.ignore_eos)
self.assertTrue(sp.skip_special_tokens)
self.assertTrue(sp.spaces_between_special_tokens)
self.assertFalse(sp.no_stop_trim)
def test_msgpack_omits_default_fields(self):
encoded = msgspec.msgpack.encode(SamplingParams())
self.assertEqual(msgspec.msgpack.decode(encoded), {})
def test_msgpack_round_trip_preserves_normalized_state(self):
tokenizer = MagicMock()
tokenizer.encode.side_effect = lambda s, add_special_tokens=False: {
"hello": [101, 102],
"world": [201],
}[s]
sp = SamplingParams(
stop=["hello", "world"],
stop_regex=r"[a-z]{3}",
stop_token_ids=[1, 2],
temperature=0.5,
)
sp.normalize(tokenizer)
encoder = msgspec.msgpack.Encoder()
decoder = msgspec.msgpack.Decoder(SamplingParams)
rebuilt = decoder.decode(encoder.encode(sp))
self.assertIsInstance(rebuilt, SamplingParams)
self.assertTrue(rebuilt.is_normalized)
self.assertEqual(rebuilt.stop_strs, ["hello", "world"])
self.assertEqual(rebuilt.stop_str_max_len, 2)
self.assertEqual(rebuilt.stop_regex_strs, [r"[a-z]{3}"])
self.assertEqual(rebuilt.stop_regex_max_len, 3)
self.assertEqual(rebuilt.stop_token_ids, {1, 2})
self.assertEqual(rebuilt.temperature, 0.5)
class TestRegexMaxLength(CustomTestCase):
def test_literal_string(self):
"""Test that plain string 'abc' gives max length 3."""
self.assertEqual(get_max_seq_length("abc"), 3)
def test_character_class(self):
"""Test that character class '[a-z]' gives max length 1."""
self.assertEqual(get_max_seq_length("[a-z]"), 1)
def test_dot_any(self):
"""Test that dot wildcard '.' gives max length 1."""
self.assertEqual(get_max_seq_length("."), 1)
def test_unbounded_star(self):
"""Test that 'a*' (zero or more, no upper bound) returns MAX_LEN."""
result = get_max_seq_length("a*")
self.assertEqual(result, MAX_LEN)
def test_unbounded_plus(self):
"""Test that 'a+' (one or more, no upper bound) returns MAX_LEN."""
result = get_max_seq_length("a+")
self.assertEqual(result, MAX_LEN)
def test_bounded_repeat(self):
"""Test that exact repeat 'a{5}' gives max length 5."""
self.assertEqual(get_max_seq_length("a{5}"), 5)
def test_bounded_range_repeat(self):
"""Test that range repeat 'a{2,4}' uses upper bound, giving max length 4."""
self.assertEqual(get_max_seq_length("a{2,4}"), 4)
def test_branch_takes_max(self):
"""Test that alternation 'abc|de' takes the longer branch: max(3, 2) = 3."""
self.assertEqual(get_max_seq_length("abc|de"), 3)
def test_subpattern_group(self):
"""Test that capturing group '(abc)' gives max length 3 from inner content."""
self.assertEqual(get_max_seq_length("(abc)"), 3)
def test_zero_width_assertions_ignored(self):
"""Test that anchors ^ and $ in '^abc$' add 0, giving max length 3."""
self.assertEqual(get_max_seq_length("^abc$"), 3)
def test_complex_pattern(self):
"""Test combined pattern '(foo|bar)\\d{2}': branch(3) + repeat(2) = 5."""
self.assertEqual(get_max_seq_length(r"(foo|bar)\d{2}"), 5)
def test_nested_groups(self):
"""Test that nested groups '((ab))' correctly recurse to give max length 2."""
self.assertEqual(get_max_seq_length("((ab))"), 2)
def test_question_mark_optional(self):
"""Test that optional 'a?' (equivalent to a{0,1}) gives max length 1."""
self.assertEqual(get_max_seq_length("a?"), 1)
def test_mixed_unbounded_and_bounded(self):
"""Test that 'ab+c{3}' gives >= MAX_LEN because b+ is unbounded."""
result = get_max_seq_length("ab+c{3}")
self.assertGreaterEqual(result, MAX_LEN)
def test_empty_regex(self):
"""Test that empty regex gives max length 0 (no tokens to match)."""
self.assertEqual(get_max_seq_length(""), 0)
def test_lookahead_triggers_unhandled_token(self):
"""Test that lookahead (?=a) hits the unhandled-token fallback (MAX_LEN)."""
result = get_max_seq_length("(?=a)b")
self.assertGreaterEqual(result, MAX_LEN)
def test_lookbehind_triggers_unhandled_token(self):
"""Test that lookbehind (?<=x) hits the unhandled-token fallback (MAX_LEN)."""
result = get_max_seq_length("(?<=x)y")
self.assertGreaterEqual(result, MAX_LEN)
if __name__ == "__main__":
unittest.main()