| | 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")), |
| | } |
| | ) |
| |
|
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| | |
| |
|
| |
|
| | 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) |
| |
|
