| from dataclasses import field |
| from typing import Any, Dict, List |
|
|
| from datasets import Features, Sequence, Value |
|
|
| from .operator import StreamInstanceOperatorValidator |
|
|
| 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")), |
| } |
| ) |
|
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| |
| |
| |
| |
| |
| |
| |
| |
|
|
|
|
| class ToUnitxtGroup(StreamInstanceOperatorValidator): |
| group: str |
| metrics: List[str] = None |
| postprocessors: List[str] = field(default_factory=lambda: ["to_string"]) |
| remove_unnecessary_fields: bool = True |
|
|
| def process(self, instance: Dict[str, Any], stream_name: str = None) -> Dict[str, Any]: |
| if self.remove_unnecessary_fields: |
| for key in instance.keys(): |
| if key not in UNITXT_DATASET_SCHEMA: |
| 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: str = None): |
| |
| assert instance is not None, f"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}" |
| UNITXT_DATASET_SCHEMA.encode_example(instance) |
|
|
