| import json |
| from dataclasses import field |
| from typing import Any, Dict, List, Optional |
|
|
| from datasets import Features, Sequence, Value |
|
|
| from .operator import InstanceOperatorValidator |
|
|
| UNITXT_DATASET_SCHEMA = Features( |
| { |
| "source": Value("string"), |
| "target": Value("string"), |
| "references": Sequence(Value("string")), |
| "metrics": Sequence(Value("string")), |
| "group": Value("string"), |
| "postprocessors": Sequence(Value("string")), |
| "task_data": Value(dtype="string"), |
| "data_classification_policy": Sequence(Value("string")), |
| } |
| ) |
|
|
|
|
| class ToUnitxtGroup(InstanceOperatorValidator): |
| group: str |
| metrics: List[str] = None |
| postprocessors: List[str] = field(default_factory=lambda: ["to_string_stripped"]) |
| remove_unnecessary_fields: bool = True |
|
|
| @staticmethod |
| def artifact_to_jsonable(artifact): |
| if artifact.__id__ is None: |
| return artifact.to_dict() |
| return artifact.__id__ |
|
|
| def process( |
| self, instance: Dict[str, Any], stream_name: Optional[str] = None |
| ) -> Dict[str, Any]: |
| task_data = { |
| **instance["inputs"], |
| **instance["outputs"], |
| "metadata": { |
| "template": self.artifact_to_jsonable( |
| instance["recipe_metadata"]["template"] |
| ) |
| }, |
| } |
| instance["task_data"] = json.dumps(task_data) |
|
|
| if self.remove_unnecessary_fields: |
| keys_to_delete = [] |
|
|
| for key in instance.keys(): |
| if key not in UNITXT_DATASET_SCHEMA: |
| keys_to_delete.append(key) |
|
|
| for key in keys_to_delete: |
| del instance[key] |
| instance["group"] = self.group |
| if self.metrics is not None: |
| instance["metrics"] = self.metrics |
| if self.postprocessors is not None: |
| instance["postprocessors"] = self.postprocessors |
| return instance |
|
|
| def validate(self, instance: Dict[str, Any], stream_name: Optional[str] = None): |
| |
| assert instance is not None, "Instance is None" |
| assert isinstance( |
| instance, dict |
| ), f"Instance should be a dict, got {type(instance)}" |
| assert all( |
| key in instance for key in UNITXT_DATASET_SCHEMA |
| ), f"Instance should have the following keys: {UNITXT_DATASET_SCHEMA}. Instance is: {instance}" |
| UNITXT_DATASET_SCHEMA.encode_example(instance) |
|
|