mirror of
https://github.com/lancedb/lancedb.git
synced 2026-09-03 12:08:52 +00:00
feat(functions): support GPU resource requirements (#4085)
Functions can describe their Python environment today, but cannot declare accelerator requirements. That prevents Sophon from scheduling computed-column UDF refreshes onto GPU workers from the immutable Function definition. Add `num_gpus` to Python `@udf` through a typed `FunctionResourceRequirements` value and represent resource-aware definitions with the `python_v2` runtime discriminator. CPU Functions retain their existing `python` encoding and canonical identity. The new discriminator is intentional for mixed-version safety: deployments that do not understand execution resources reject the runtime instead of accepting a new field and silently running the Function on CPU. Required resources are part of Function version identity; priority, concurrency, and retry policy remain Job concerns. The actual resource scheduling remains owned by Sophon.
This commit is contained in:
@@ -54,6 +54,18 @@ _UInt32 = conint(strict=True, ge=0, le=2**32 - 1)
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_UInt64 = conint(strict=True, ge=0, le=2**64 - 1)
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def _validate_gpu_wire_marker(value: Any) -> bool:
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if value is not True:
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raise ValueError("runtime.gpu must be true")
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return True
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def _normalize_gpu_marker(value: bool) -> Optional[bool]:
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if not isinstance(value, bool):
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raise ValueError("gpu must be a boolean")
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return True if value else None
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class _FrozenDict(dict):
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def _immutable(self, *args, **kwargs):
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raise TypeError("remote canonical values are immutable")
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@@ -239,6 +251,23 @@ class PythonRuntimeSpec(_RemoteValue):
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python_version: Optional[str] = None
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environment: Optional[PythonEnvironmentSpec] = None
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env: Optional[Mapping[str, str]] = None
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gpu: Optional[bool] = None
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@model_validator(mode="before")
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@classmethod
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def _discard_unknown_runtime_payload(cls, value):
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if isinstance(value, Mapping):
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kind = value.get("kind")
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if isinstance(kind, str) and kind not in {"python", "python_v2"}:
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return {"kind": kind}
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return value
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@field_validator("gpu", mode="before")
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@classmethod
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def _validate_gpu_marker(cls, value):
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if value is None:
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return None
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return _validate_gpu_wire_marker(value)
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@model_validator(mode="after")
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def _validate_runtime_kind(self):
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@@ -247,18 +276,28 @@ class PythonRuntimeSpec(_RemoteValue):
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raise ValueError("python runtime requires python_version")
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if self.environment is None:
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raise ValueError("python runtime requires environment")
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if self.gpu is not None:
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raise ValueError("python runtime with gpu requires kind='python_v2'")
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elif self.kind == "python_v2":
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if self.python_version is None:
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raise ValueError("python_v2 runtime requires python_version")
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if self.environment is None:
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raise ValueError("python_v2 runtime requires environment")
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if self.gpu is None:
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raise ValueError("python_v2 runtime requires gpu")
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else:
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object.__setattr__(self, "python_version", None)
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object.__setattr__(self, "environment", None)
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object.__setattr__(self, "env", None)
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object.__setattr__(self, "gpu", None)
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return self
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class FunctionVersion(_RemoteValue):
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"""An exact immutable Function version returned by Enterprise.
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Scheduling resources, priority, concurrency, and retry policy belong to
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the submitting Job and are not part of this identity.
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The GPU execution requirement is part of this identity. CPU and memory sizing,
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priority, concurrency, and retry policy belong to the execution platform.
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"""
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name: str
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@@ -996,6 +1035,7 @@ class UdfDefinition:
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pip: tuple[str, ...],
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env: Mapping[str, str],
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python_version: Optional[str],
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gpu: bool = False,
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conda: tuple[str, ...] = (),
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conda_channels: tuple[str, ...] = (),
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):
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@@ -1024,12 +1064,14 @@ class UdfDefinition:
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signature = _infer_signature(function, input_schema, output_schema)
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source = _package_source(function)
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digest = f"sha256:{hashlib.sha256(source).hexdigest()}"
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gpu_marker = _normalize_gpu_marker(gpu)
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runtime = PythonRuntimeSpec(
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kind="python",
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kind="python_v2" if gpu_marker is not None else "python",
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python_version=python_version
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or f"{sys.version_info.major}.{sys.version_info.minor}",
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environment=environment_spec,
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env=environment,
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gpu=gpu_marker,
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)
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self._function = function
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self._request = FunctionRegistrationRequest(
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@@ -1075,6 +1117,7 @@ def udf(
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pip: tuple[str, ...] | list[str] = (),
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env: Optional[Mapping[str, str]] = None,
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python_version: Optional[str] = None,
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gpu: bool = False,
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conda: tuple[str, ...] | list[str] = (),
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conda_channels: tuple[str, ...] | list[str] = (),
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) -> Callable[[Callable[..., Any]], UdfDefinition]: ...
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@@ -1089,6 +1132,7 @@ def udf(
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pip: tuple[str, ...] | list[str] = (),
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env: Optional[Mapping[str, str]] = None,
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python_version: Optional[str] = None,
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gpu: bool = False,
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conda: tuple[str, ...] | list[str] = (),
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conda_channels: tuple[str, ...] | list[str] = (),
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):
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@@ -1121,6 +1165,10 @@ def udf(
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Environment variables included in the Function definition.
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python_version : str, optional
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Remote Python major/minor version. Defaults to the client version.
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gpu : bool, default False
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Whether every remote execution requires a GPU. The execution platform
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selects one compatible GPU for each worker. The requirement is part of
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the immutable Function version.
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The packaged artifact is a snapshot: the function source plus exactly
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the module-level names it references (modules as imports, importable
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@@ -1145,6 +1193,11 @@ def udf(
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... return value * 2
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>>> score(1.5)
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3.0
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>>> @udf(pip=["cupy-cuda12x"], gpu=True)
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... def gpu_score(value: int) -> int:
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... return value * 2
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>>> gpu_score.registration_request.runtime.gpu
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True
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"""
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def decorate(target: Callable[..., Any]) -> UdfDefinition:
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@@ -1156,6 +1209,7 @@ def udf(
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pip=tuple(pip),
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env={} if env is None else env,
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python_version=python_version,
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gpu=gpu,
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conda=tuple(conda),
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conda_channels=tuple(conda_channels),
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)
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@@ -19,7 +19,7 @@ import pyarrow as pa
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import pytest
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import lancedb
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from lancedb.functions import UdfDefinition, udf
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from lancedb.functions import PythonRuntimeSpec, UdfDefinition, udf
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THRESHOLD = 20
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_CACHE = None
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@@ -89,6 +89,58 @@ def test_udf_conda_environment():
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udf(name="channels", conda_channels=["conda-forge"])(lambda value: value)
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def test_udf_gpu_marker_uses_gpu_runtime():
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@udf(pip=["cupy-cuda12x"], gpu=True)
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def double_on_gpu(value: int) -> int:
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return value * 2
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request = json.loads(double_on_gpu.registration_request.to_canonical_json())
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assert request["runtime"]["kind"] == "python_v2"
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assert request["runtime"]["gpu"] is True
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@udf(pip=["pyarrow"])
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def cpu_function(value: int) -> int:
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return value
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cpu_runtime = json.loads(cpu_function.registration_request.to_canonical_json())[
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"runtime"
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]
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assert cpu_runtime["kind"] == "python"
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assert "gpu" not in cpu_runtime
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def identity(value: int) -> int:
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return value
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for invalid in [None, 0, 1, -1, 1.5, "", "true", "1", "H100"]:
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with pytest.raises(ValueError, match="gpu must be a boolean"):
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udf(name="invalid_gpu", gpu=invalid)(identity)
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base_runtime = {
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"kind": "python_v2",
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"python_version": "3.12",
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"environment": {"kind": "pip"},
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}
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runtime = PythonRuntimeSpec.model_validate({**base_runtime, "gpu": True})
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assert runtime.gpu is True
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for invalid in [False, 1, 0, "", "true", "1", "H100"]:
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with pytest.raises(ValueError, match="runtime.gpu must be true"):
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PythonRuntimeSpec.model_validate({**base_runtime, "gpu": invalid})
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def test_unknown_runtime_discards_payload_before_known_field_validation():
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for payload in [
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{"kind": "python_v3", "gpu": {"model": "H100"}},
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{"kind": "python_v3", "resources": []},
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{
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"kind": "python_v3",
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"environment": {"kind": []},
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"python_version": 3.15,
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},
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]:
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runtime = PythonRuntimeSpec.model_validate(payload)
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assert runtime.to_canonical_json() == '{"kind":"python_v3"}'
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def test_udf_packages_attribute_access_and_body_imports():
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@udf
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def word_norm(body: str) -> float:
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+150
-27
@@ -207,6 +207,33 @@ pub enum PythonRuntimeSpec {
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environment: PythonEnvironmentSpec,
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env: BTreeMap<String, String>,
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},
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/// The GPU-enabled Sophon-managed Python runtime.
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///
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/// # Examples
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///
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/// ```
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/// use std::collections::BTreeMap;
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/// use lancedb::function::{PythonEnvironmentSpec, PythonRuntimeSpec};
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///
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/// let runtime = PythonRuntimeSpec::PythonV2 {
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/// python_version: "3.12".to_string(),
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/// environment: PythonEnvironmentSpec {
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/// kind: "pip".to_string(),
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/// packages: vec!["cupy-cuda12x".to_string()],
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/// channels: Vec::new(),
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/// path: None,
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/// modules: Vec::new(),
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/// image: None,
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/// },
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/// env: BTreeMap::new(),
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/// };
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/// assert!(runtime.requires_gpu());
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/// ```
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PythonV2 {
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python_version: String,
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environment: PythonEnvironmentSpec,
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env: BTreeMap<String, String>,
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},
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/// A runtime kind introduced by a newer server.
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///
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/// Unknown payload fields are intentionally not retained because the
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@@ -219,22 +246,27 @@ impl PythonRuntimeSpec {
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pub fn kind(&self) -> &str {
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match self {
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Self::Python { .. } => "python",
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Self::PythonV2 { .. } => "python_v2",
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Self::Unrecognized { kind } => kind,
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}
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}
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/// The Python version for the V1 runtime, or `None` for an unknown kind.
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/// The Python version for a known Python runtime, or `None` for an unknown kind.
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pub fn python_version(&self) -> Option<&str> {
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match self {
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Self::Python { python_version, .. } => Some(python_version),
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Self::Python { python_version, .. } | Self::PythonV2 { python_version, .. } => {
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Some(python_version)
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}
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Self::Unrecognized { .. } => None,
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}
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}
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/// The Python environment for the V1 runtime, or `None` for an unknown kind.
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/// The Python environment for a known Python runtime, or `None` for an unknown kind.
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pub fn environment(&self) -> Option<&PythonEnvironmentSpec> {
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match self {
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Self::Python { environment, .. } => Some(environment),
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Self::Python { environment, .. } | Self::PythonV2 { environment, .. } => {
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Some(environment)
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}
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Self::Unrecognized { .. } => None,
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}
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}
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@@ -242,38 +274,73 @@ impl PythonRuntimeSpec {
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/// Environment variables, or `None` for an unknown kind.
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pub fn env(&self) -> Option<&BTreeMap<String, String>> {
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match self {
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Self::Python { env, .. } => Some(env),
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Self::Python { env, .. } | Self::PythonV2 { env, .. } => Some(env),
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Self::Unrecognized { .. } => None,
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}
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}
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/// Whether the runtime requires a GPU selected by the execution platform.
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pub fn requires_gpu(&self) -> bool {
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matches!(self, Self::PythonV2 { .. })
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}
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}
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#[derive(Deserialize)]
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struct PythonRuntimeWire {
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kind: String,
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#[serde(default)]
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python_version: Option<String>,
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#[serde(default)]
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environment: Option<PythonEnvironmentSpec>,
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struct PythonRuntimeV1Wire {
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python_version: String,
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environment: PythonEnvironmentSpec,
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#[serde(default)]
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env: BTreeMap<String, String>,
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#[serde(default)]
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gpu: Option<Value>,
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}
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#[derive(Deserialize)]
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struct PythonRuntimeV2Wire {
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python_version: String,
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environment: PythonEnvironmentSpec,
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#[serde(default)]
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env: BTreeMap<String, String>,
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gpu: bool,
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}
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impl<'de> Deserialize<'de> for PythonRuntimeSpec {
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fn deserialize<D: Deserializer<'de>>(deserializer: D) -> std::result::Result<Self, D::Error> {
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let wire = PythonRuntimeWire::deserialize(deserializer)?;
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if wire.kind == "python" {
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Ok(Self::Python {
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python_version: wire
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.python_version
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.ok_or_else(|| de::Error::missing_field("python_version"))?,
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environment: wire
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.environment
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.ok_or_else(|| de::Error::missing_field("environment"))?,
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env: wire.env,
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})
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} else {
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Ok(Self::Unrecognized { kind: wire.kind })
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let value = Value::deserialize(deserializer)?;
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let kind = value
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.get("kind")
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.ok_or_else(|| de::Error::missing_field("kind"))?
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.as_str()
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.ok_or_else(|| de::Error::custom("runtime.kind must be a string"))?
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.to_string();
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match kind.as_str() {
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"python" => {
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let wire: PythonRuntimeV1Wire =
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serde_json::from_value(value).map_err(de::Error::custom)?;
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if wire.gpu.is_some() {
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return Err(de::Error::custom(
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"python runtime with gpu requires kind='python_v2'",
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));
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}
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Ok(Self::Python {
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python_version: wire.python_version,
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environment: wire.environment,
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env: wire.env,
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})
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}
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"python_v2" => {
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let wire: PythonRuntimeV2Wire =
|
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serde_json::from_value(value).map_err(de::Error::custom)?;
|
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if !wire.gpu {
|
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return Err(de::Error::custom("runtime.gpu must be true"));
|
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}
|
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Ok(Self::PythonV2 {
|
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python_version: wire.python_version,
|
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environment: wire.environment,
|
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env: wire.env,
|
||||
})
|
||||
}
|
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_ => Ok(Self::Unrecognized { kind }),
|
||||
}
|
||||
}
|
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}
|
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@@ -287,6 +354,8 @@ impl Serialize for PythonRuntimeSpec {
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environment: &'a PythonEnvironmentSpec,
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#[serde(skip_serializing_if = "BTreeMap::is_empty")]
|
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env: &'a BTreeMap<String, String>,
|
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#[serde(skip_serializing_if = "Option::is_none")]
|
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gpu: Option<bool>,
|
||||
}
|
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|
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#[derive(Serialize)]
|
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@@ -304,6 +373,19 @@ impl Serialize for PythonRuntimeSpec {
|
||||
python_version,
|
||||
environment,
|
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env,
|
||||
gpu: None,
|
||||
}
|
||||
.serialize(serializer),
|
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Self::PythonV2 {
|
||||
python_version,
|
||||
environment,
|
||||
env,
|
||||
} => PythonRuntimeRef {
|
||||
kind: "python_v2",
|
||||
python_version,
|
||||
environment,
|
||||
env,
|
||||
gpu: Some(true),
|
||||
}
|
||||
.serialize(serializer),
|
||||
Self::Unrecognized { kind } => UnrecognizedRuntimeRef { kind }.serialize(serializer),
|
||||
@@ -313,8 +395,8 @@ impl Serialize for PythonRuntimeSpec {
|
||||
|
||||
/// Immutable Function version returned by the Enterprise catalog.
|
||||
///
|
||||
/// Scheduling resources, priority, concurrency, and retry policy belong to
|
||||
/// the submitting Job and are not part of this identity.
|
||||
/// The GPU execution requirement is part of this identity. CPU and memory sizing,
|
||||
/// priority, concurrency, and retry policy belong to the execution platform.
|
||||
#[derive(Debug, Clone, PartialEq, Eq, Serialize, Deserialize)]
|
||||
pub struct FunctionVersion {
|
||||
name: String,
|
||||
@@ -589,7 +671,7 @@ impl_json!(RefreshColumnResult);
|
||||
|
||||
#[cfg(test)]
|
||||
mod conda_environment_tests {
|
||||
use super::PythonEnvironmentSpec;
|
||||
use super::{PythonEnvironmentSpec, PythonRuntimeSpec};
|
||||
|
||||
#[test]
|
||||
fn conda_channels_round_trip_and_pip_stays_bare() {
|
||||
@@ -608,4 +690,45 @@ mod conda_environment_tests {
|
||||
serde_json::from_str(r#"{"kind":"pip","packages":["numpy"]}"#).unwrap();
|
||||
assert!(!serde_json::to_string(&pip).unwrap().contains("channels"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn gpu_python_runtime_marker_round_trips_and_validates() {
|
||||
let runtime: PythonRuntimeSpec = serde_json::from_str(
|
||||
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":true}"#,
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(runtime.kind(), "python_v2");
|
||||
assert!(runtime.requires_gpu());
|
||||
assert_eq!(
|
||||
super::canonical_json(&runtime).unwrap(),
|
||||
r#"{"environment":{"kind":"pip"},"gpu":true,"kind":"python_v2","python_version":"3.12"}"#
|
||||
);
|
||||
|
||||
for invalid in [
|
||||
r#"{"kind":"python","python_version":"3.12","environment":{"kind":"pip"},"gpu":true}"#,
|
||||
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"}}"#,
|
||||
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":1}"#,
|
||||
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":false}"#,
|
||||
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":"true"}"#,
|
||||
r#"{"kind":"python_v2","python_version":"3.12","environment":{"kind":"pip"},"gpu":"H100"}"#,
|
||||
] {
|
||||
assert!(serde_json::from_str::<PythonRuntimeSpec>(invalid).is_err());
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn unknown_runtime_discards_payload_before_known_field_validation() {
|
||||
for encoded in [
|
||||
r#"{"kind":"python_v3","gpu":{"model":"H100"}}"#,
|
||||
r#"{"kind":"python_v3","resources":[]}"#,
|
||||
r#"{"kind":"python_v3","python_version":3.15,"environment":{"kind":[]}}"#,
|
||||
] {
|
||||
let runtime: PythonRuntimeSpec = serde_json::from_str(encoded).unwrap();
|
||||
assert_eq!(runtime.kind(), "python_v3");
|
||||
assert_eq!(
|
||||
super::canonical_json(&runtime).unwrap(),
|
||||
r#"{"kind":"python_v3"}"#
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user