File size: 3,434 Bytes
ebeed67 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 | """The shape of ``result.json`` (``camstack.training-result/v1``), as pydantic.
``manifest.py`` builds the document as plain dicts; this model is the contract
it is checked against (in the tests, and by ``tools/gen_schemas.py`` into
``schemas/result.schema.json``, which the hub mirrors in zod). The harness's
per-class reports stay open (``dict``): their shape is the harness's own.
"""
from __future__ import annotations
from typing import Any, Literal, Optional
from pydantic import BaseModel, ConfigDict, Field
class _Open(BaseModel):
model_config = ConfigDict(extra="forbid", protected_namespaces=())
class ErrorBlock(_Open):
stage: str
code: str
message: str
class TrainerBlock(_Open):
version: str
revision: str
class Frames(_Open):
train: int
val: int
holdout: int
class DatasetBlock(_Open):
versionId: str
annotationHash: str
sha256: str
frames: Frames
holdoutCameras: list[int]
replayImages: int
class TrainingBlock(_Open):
epochsRun: int
bestEpoch: int
bestMap50: float
bestMap50_95: float
seconds: float
class EvaluationBlock(_Open):
holdoutFrames: int
baseline: Optional[dict[str, Any]]
candidate: Optional[dict[str, Any]]
candidateInt8: Optional[dict[str, Any]]
recallDeltaByCamera: Optional[dict[str, dict[str, float]]]
map50: dict[str, Optional[float]]
class FloorsBlock(_Open):
baseline: dict[str, float]
candidate: dict[str, float]
candidateInt8: Optional[dict[str, float]]
notes: list[str]
class Int8Block(_Open):
kept: bool
map50Fp16: Optional[float]
map50Int8: Optional[float]
reason: Optional[str]
class Dropped(_Open):
export: str
reason: str
class FileRow(_Open):
path: str
bytes: int
sha256: str = Field(pattern=r"^[0-9a-f]{64}$")
format: Literal["onnx", "openvino", "coreml", "pt"]
variant: Literal["base", "int8"]
class Bundle(_Open):
path: Literal["bundle.tar"]
bytes: int
sha256: str = Field(pattern=r"^[0-9a-f]{64}$")
class FormatEntry(_Open):
url: str
sizeMB: float
revision: str
files: Optional[list[str]] = None
runtimes: Optional[list[Literal["python"]]] = None
isDirectory: Optional[bool] = None
class CatalogEntryDraft(_Open):
id: str
name: str
description: str
inputSize: dict[Literal["width", "height"], int]
labels: list[Any]
preprocessMode: Literal["letterbox"]
defaultClassFloors: dict[str, float]
formats: dict[Literal["onnx", "openvino", "coreml"], FormatEntry]
class CatalogDraft(_Open):
base: CatalogEntryDraft
int8: Optional[CatalogEntryDraft]
class TrainingResult(_Open):
"""A succeeded result carries every block; a failed one the error and whatever was known."""
schema_: Literal["camstack.training-result/v1"] = Field(alias="schema")
jobKey: str
status: Literal["succeeded", "failed"]
error: Optional[ErrorBlock]
trainer: TrainerBlock
toolchain: dict[str, Optional[str]]
dataset: Optional[DatasetBlock] = None
training: Optional[TrainingBlock] = None
evaluation: Optional[EvaluationBlock] = None
floors: Optional[FloorsBlock] = None
int8: Optional[Int8Block] = None
exportsDropped: Optional[list[Dropped]] = None
files: Optional[list[FileRow]] = None
bundle: Optional[Bundle] = None
catalogDraft: Optional[CatalogDraft] = None
licence: str
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