API Perf: Replace pydantic per-element validation with C loop validation (#26355)
This commit is contained in:
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"""Microbenchmark: cost of validating `input_ids` during FastAPI body binding.
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Compares two validators on a single `input_ids` field:
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- GenerateReqInputPydanticValidator: default pydantic walk (per-element type check)
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- GenerateReqInputCustomValidator: C-loop validator (validate_optional_list_i64_1d_2d)
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Usage:
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python benchmark/io/bench_input_ids_validator.py
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"""
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import time
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from dataclasses import dataclass
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from typing import Annotated, List, Optional, Union
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from pydantic import PlainValidator, TypeAdapter
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from sglang.srt.utils.field_validators import validate_optional_list_i64_1d_2d
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@dataclass
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class GenerateReqInputPydanticValidator:
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"""Default pydantic — walks every element of input_ids to type-check."""
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input_ids: Optional[Union[List[List[int]], List[int]]] = None
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@dataclass
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class GenerateReqInputCustomValidator:
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"""C-loop validator via PlainValidator."""
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input_ids: Annotated[
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Optional[Union[List[List[int]], List[int]]],
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PlainValidator(validate_optional_list_i64_1d_2d),
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] = None
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_ta_pydantic = TypeAdapter(GenerateReqInputPydanticValidator)
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_ta_custom = TypeAdapter(GenerateReqInputCustomValidator)
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def _time(fn, n_iter=30):
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t0 = time.perf_counter()
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for _ in range(n_iter):
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fn()
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return (time.perf_counter() - t0) * 1000 / n_iter
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def main():
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print(
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f"{'n_tokens':>9s} | {'default pydantic (ms)':>22s} | "
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f"{'rigid i64 validator (ms)':>26s}"
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)
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print("-" * 65)
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for n in [1_000, 10_000, 100_000, 1_000_000]:
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d = {"input_ids": list(range(1, n + 1))}
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p1 = _time(lambda: _ta_pydantic.validate_python(d))
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p2 = _time(lambda: _ta_custom.validate_python(d))
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print(f"{n:>9d} | {p1:>22.3f} | {p2:>26.3f}")
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print("\nLegend: mean over 30 iters, in ms.")
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if __name__ == "__main__":
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main()
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@@ -25,9 +25,10 @@ from array import array
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from collections import Counter
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from collections import Counter
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from dataclasses import dataclass, field
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from dataclasses import dataclass, field
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from enum import Enum
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from enum import Enum
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from typing import TYPE_CHECKING, Any, Dict, List, Literal, Optional, Union
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from typing import TYPE_CHECKING, Annotated, Any, Dict, List, Literal, Optional, Union
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import torch
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import torch
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from pydantic import PlainValidator
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from sglang.srt.lora.lora_registry import LoRARef
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from sglang.srt.lora.lora_registry import LoRARef
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from sglang.srt.managers.embed_types import PositionalEmbeds
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from sglang.srt.managers.embed_types import PositionalEmbeds
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@@ -40,6 +41,7 @@ from sglang.srt.observability.req_time_stats import (
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)
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)
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from sglang.srt.sampling.sampling_params import SamplingParams
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from sglang.srt.sampling.sampling_params import SamplingParams
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from sglang.srt.utils import ImageData, VideoData
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from sglang.srt.utils import ImageData, VideoData
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from sglang.srt.utils.field_validators import validate_optional_list_i64_1d_2d
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# Handle serialization of Image for pydantic
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# Handle serialization of Image for pydantic
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if TYPE_CHECKING:
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if TYPE_CHECKING:
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@@ -136,8 +138,13 @@ MultimodalDataInputFormat = Union[
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class GenerateReqInput(BaseReq):
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class GenerateReqInput(BaseReq):
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# The input prompt. It can be a single prompt or a batch of prompts.
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# The input prompt. It can be a single prompt or a batch of prompts.
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text: Optional[Union[List[str], str]] = None
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text: Optional[Union[List[str], str]] = None
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# The token ids for text; one can specify either text or input_ids
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# The token ids for text.
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input_ids: Optional[Union[List[List[int]], List[int]]] = None
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#
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# Use C-loop validator to replace Pydantic per-element type check for efficiency.
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input_ids: Annotated[
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Optional[Union[List[List[int]], List[int]]],
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PlainValidator(validate_optional_list_i64_1d_2d),
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] = None
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# The embeddings for input_ids; one can specify either text or input_ids or input_embeds.
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# The embeddings for input_ids; one can specify either text or input_ids or input_embeds.
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input_embeds: Optional[Union[List[List[List[float]]], List[List[float]]]] = None
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input_embeds: Optional[Union[List[List[List[float]]], List[List[float]]]] = None
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# The image input. It can be an image instance, file name, URL, or base64 encoded string.
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# The image input. It can be an image instance, file name, URL, or base64 encoded string.
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@@ -0,0 +1,81 @@
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# Copyright 2023-2024 SGLang Team
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Lightweight, reusable validators for hot-path API fields.
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These are intended to be paired with ``pydantic.PlainValidator`` on
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dataclass fields whose JSON shape is large or homogeneously typed, where
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pydantic's default per-element walk has been measured to dominate
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request latency.
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Usage::
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from typing import Annotated, List, Optional, Union
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from pydantic import PlainValidator
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from sglang.srt.utils.field_validators import validate_optional_list_i64_1d_2d
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@dataclass
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class MyReq:
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input_ids: Annotated[
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Optional[Union[List[List[int]], List[int]]],
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PlainValidator(validate_optional_list_i64_1d_2d),
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] = None
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"""
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from __future__ import annotations
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from array import array
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from typing import Any
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def validate_list_i64_1d(v: Any) -> list[int]:
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"""Validates type: list[int]"""
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if v is None:
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raise ValueError("must not be None")
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if not isinstance(v, list):
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raise ValueError(f"must be list; got {type(v).__name__}")
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if not v:
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return v
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if not isinstance(v[0], int):
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raise ValueError(f"elements must be int; got {type(v[0]).__name__}")
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try:
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array("q", v)
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except (TypeError, OverflowError) as e:
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raise ValueError(f"contains non-int64 element: {e}") from None
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return v
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def validate_optional_list_i64_1d_2d(
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v: Any,
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) -> list[int] | list[list[int]] | None:
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"""Validates type: list[int] | list[list[int]] | None"""
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if v is None:
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# Accept None
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return v
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if not isinstance(v, list):
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raise ValueError(f"must be list or null; got {type(v).__name__}")
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if not v:
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# Accept empty list
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return v
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if isinstance(v[0], int):
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# Accept list[int]
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return validate_list_i64_1d(v)
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if isinstance(v[0], list):
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# Accept list[list[int]]
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for i, row in enumerate(v):
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try:
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validate_list_i64_1d(row)
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except ValueError as e:
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raise ValueError(f"row {i}: {e}") from None
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return v
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raise ValueError(f"elements must be int or list; got {type(v[0]).__name__}")
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import unittest
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from sglang.srt.utils.field_validators import (
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validate_list_i64_1d,
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validate_optional_list_i64_1d_2d,
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)
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from sglang.test.ci.ci_register import register_cpu_ci
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from sglang.test.test_utils import CustomTestCase
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register_cpu_ci(est_time=2, suite="base-a-test-cpu")
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class TestValidateListI64_1d(CustomTestCase):
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"""`validate_list_i64_1d` rejects anything that array('q', v) can't accept."""
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def test_accept_int_list(self):
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v = [1, 2, 3]
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self.assertIs(validate_list_i64_1d(v), v)
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def test_accept_empty_list(self):
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v = []
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self.assertIs(validate_list_i64_1d(v), v)
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def test_accept_int64_boundaries(self):
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for v in ([-(2**63)], [2**63 - 1], [0]):
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self.assertIs(validate_list_i64_1d(v), v)
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def test_reject_none(self):
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with self.assertRaisesRegex(ValueError, "must not be None"):
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validate_list_i64_1d(None)
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def test_reject_non_list(self):
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for v in ((1, 2, 3), "abc", {1: 2}, 42, 3.14):
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with self.subTest(v=v):
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with self.assertRaisesRegex(ValueError, "must be list"):
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validate_list_i64_1d(v)
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def test_reject_non_int_first_element(self):
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for v in ([1.5, 2, 3], ["a", "b"], [None, 1]):
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with self.subTest(v=v):
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with self.assertRaisesRegex(ValueError, "elements must be int"):
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validate_list_i64_1d(v)
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def test_reject_overflow_int64(self):
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# 2**63 overflows signed int64.
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with self.assertRaisesRegex(ValueError, "non-int64 element"):
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validate_list_i64_1d([0, 2**63])
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def test_reject_non_int_later_element(self):
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# First-element fast path passes but C loop rejects later float.
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with self.assertRaisesRegex(ValueError, "non-int64 element"):
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validate_list_i64_1d([1, 2, 3.5])
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class TestValidateOptionalListI64_1d_2d(CustomTestCase):
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"""`validate_optional_list_i64_1d_2d` accepts None | [] | list[int] | list[list[int]]."""
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def test_accept_none(self):
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self.assertIsNone(validate_optional_list_i64_1d_2d(None))
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def test_accept_empty_list(self):
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v = []
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self.assertIs(validate_optional_list_i64_1d_2d(v), v)
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def test_accept_1d_int_list(self):
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v = [1, 2, 3]
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self.assertIs(validate_optional_list_i64_1d_2d(v), v)
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def test_accept_2d_int_list(self):
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v = [[1, 2], [3, 4, 5]]
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self.assertIs(validate_optional_list_i64_1d_2d(v), v)
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def test_accept_2d_with_empty_row(self):
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v = [[], [1, 2]]
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self.assertIs(validate_optional_list_i64_1d_2d(v), v)
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def test_reject_non_list_top_level(self):
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for v in ((1, 2), "abc", 42, 3.14, {1: 2}):
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with self.subTest(v=v):
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with self.assertRaisesRegex(ValueError, "must be list or null"):
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validate_optional_list_i64_1d_2d(v)
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def test_reject_mixed_first_element_type(self):
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with self.assertRaisesRegex(ValueError, "elements must be int or list"):
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validate_optional_list_i64_1d_2d([1.5, 2.5])
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def test_reject_overflow_in_1d(self):
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with self.assertRaisesRegex(ValueError, "non-int64 element"):
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validate_optional_list_i64_1d_2d([0, 2**63])
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def test_reject_bad_row_in_2d_reports_index(self):
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with self.assertRaisesRegex(ValueError, "row 1:"):
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validate_optional_list_i64_1d_2d([[1, 2], [3, "x"]])
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def test_reject_overflow_in_2d_reports_index(self):
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with self.assertRaisesRegex(ValueError, "row 0:.*non-int64"):
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validate_optional_list_i64_1d_2d([[2**63], [1, 2]])
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if __name__ == "__main__":
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unittest.main()
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