Datasets:

chibifire
/

taskweft-fbd-react-train

license: mit
task_categories:
  - text-generation
tags:
  - iec-61131-3
  - function-block-diagram
  - plcopen
  - taskweft
  - editscore
configs:
  - config_name: react
    default: true
    data_files:
      - split: train
        path: data/react/*.parquet
      - split: test
        path: test/data/react/*.parquet
      - split: evaluation
        path: evaluation/data/react/*.parquet
  - config_name: react_root
    data_files:
      - split: train
        path: data/react_root/*.parquet
      - split: test
        path: test/data/react_root/*.parquet
      - split: evaluation
        path: evaluation/data/react_root/*.parquet
  - config_name: react_candidates
    data_files:
      - split: train
        path: data/react_candidates/*.parquet
      - split: test
        path: test/data/react_candidates/*.parquet
      - split: evaluation
        path: evaluation/data/react_candidates/*.parquet
  - config_name: react_scores
    data_files:
      - split: train
        path: data/react_scores/*.parquet
      - split: test
        path: test/data/react_scores/*.parquet
      - split: evaluation
        path: evaluation/data/react_scores/*.parquet

taskweft-fbd-react-train

Intents paired with IEC 61131-3 Function Block Diagrams that carry them out, as an EditScore-shaped corpus.

What it is for

Each intent has a root row, three ranked candidate diagrams and a score row per candidate. Rank1 is the reference diagram. Rank3 compiles and does the wrong thing. Rank5 is a diagram the compiler refuses. The scores come from the compiler's reference scan on constructed input traces. Every row is built from a template and a seed, so the labels are true by construction and the corpus regenerates from the seeds. The train split trains. The test split holds out every tenth seed of the same distribution and gates the trained model. The evaluation split holds out the button_sequence_then_idle family, and is never trained or tuned on.

The react_root config holds the intent, template, seed, frame, the block kinds and signatures the reference uses, and the input traces. The react_candidates config holds each candidate's compiler text form, PLCopen XML, plan and runner result, with a sha256 of its source text. The react_scores config holds parse, compile, run and effect-match flags, step and wall-time measures, and the refusal. The default react config joins the three. Every artifact is in the parquet. An artifact a family does not produce is an empty string, never a null. A manifest.json sits at the repo root.

Provenance

Generator: v-sekai-fabric/taskweft-fbd-teacher.
Compiler: taskweft-fbd-compiler at commit d3279ec.

Use

from datasets import load_dataset
ds = load_dataset("chibifire/taskweft-fbd-react-train", "react", split="train")

Or fetch the files with hf download chibifire/taskweft-fbd-react-train --repo-type dataset.

Licence

MIT. See the MIT License.