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Adding Acceptability judgment and SentEval tasks #1271
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,107 @@ | ||
| import numpy as np | ||
| import torch | ||
| from dataclasses import dataclass | ||
| from typing import List | ||
|
|
||
| from jiant.tasks.core import ( | ||
| BaseExample, | ||
| BaseTokenizedExample, | ||
| BaseDataRow, | ||
| BatchMixin, | ||
| Task, | ||
| TaskTypes, | ||
| ) | ||
| from jiant.tasks.lib.templates.shared import single_sentence_featurize, labels_to_bimap | ||
| from jiant.utils.python.io import read_json | ||
|
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|
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| @dataclass | ||
| class Example(BaseExample): | ||
| guid: str | ||
| text: str | ||
| label: str | ||
|
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| def tokenize(self, tokenizer): | ||
| return TokenizedExample( | ||
| guid=self.guid, | ||
| text=tokenizer.tokenize(self.text), | ||
| label_id=BaseAcceptabilityTask.LABEL_TO_ID[self.label], | ||
| ) | ||
|
|
||
|
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| @dataclass | ||
| class TokenizedExample(BaseTokenizedExample): | ||
| guid: str | ||
| text: List | ||
| label_id: int | ||
|
|
||
| def featurize(self, tokenizer, feat_spec): | ||
| return single_sentence_featurize( | ||
| guid=self.guid, | ||
| input_tokens=self.text, | ||
| label_id=self.label_id, | ||
| tokenizer=tokenizer, | ||
| feat_spec=feat_spec, | ||
| data_row_class=DataRow, | ||
| ) | ||
|
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||
|
|
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| @dataclass | ||
| class DataRow(BaseDataRow): | ||
| guid: str | ||
| input_ids: np.ndarray | ||
| input_mask: np.ndarray | ||
| segment_ids: np.ndarray | ||
| label_id: int | ||
| tokens: list | ||
|
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||
|
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| @dataclass | ||
| class Batch(BatchMixin): | ||
| input_ids: torch.LongTensor | ||
| input_mask: torch.LongTensor | ||
| segment_ids: torch.LongTensor | ||
| label_id: torch.LongTensor | ||
| tokens: list | ||
|
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||
|
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| class BaseAcceptabilityTask(Task): | ||
| Example = Example | ||
| TokenizedExample = TokenizedExample | ||
| DataRow = DataRow | ||
| Batch = Batch | ||
|
|
||
| TASK_TYPE = TaskTypes.CLASSIFICATION | ||
| LABELS = ["acceptable", "unacceptable"] | ||
| LABEL_TO_ID, ID_TO_LABEL = labels_to_bimap(LABELS) | ||
| DATA_PHASE_MAP = {"train": "train", "dev": "val", "test": "test"} | ||
|
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||
| def __init__(self, name, path_dict, fold: str): | ||
| # Fold should be a string like "fold1" | ||
| super().__init__(name=name, path_dict=path_dict) | ||
| self.fold = fold | ||
|
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||
| def get_train_examples(self): | ||
| return self._create_examples(set_type="train") | ||
|
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| def get_val_examples(self): | ||
| return self._create_examples(set_type="val") | ||
|
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| def get_test_examples(self): | ||
| return self._create_examples(set_type="test") | ||
|
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| def _create_examples(self, set_type): | ||
| data = read_json(self.path_dict["data"]) | ||
| metadata = read_json(self.path_dict["metadata"]) | ||
| assert len(data) == len(metadata) | ||
| examples = [] | ||
| for data_row, metadata_row in zip(data, metadata): | ||
| row_phase = self.DATA_PHASE_MAP[metadata_row["misc"][self.fold]] | ||
| if row_phase != set_type: | ||
| continue | ||
| examples.append( | ||
| Example( | ||
| guid=data_row["pair-id"], text=data_row["context"], label=data_row["label"], | ||
| ) | ||
| ) | ||
| return examples |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| from dataclasses import dataclass | ||
| import jiant.tasks.lib.acceptability_judgement.base as base | ||
|
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|
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| @dataclass | ||
| class Example(base.Example): | ||
| pass | ||
|
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|
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| @dataclass | ||
| class TokenizedExample(base.TokenizedExample): | ||
| pass | ||
|
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|
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| @dataclass | ||
| class DataRow(base.DataRow): | ||
| pass | ||
|
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| @dataclass | ||
| class Batch(base.Batch): | ||
| pass | ||
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| class AcceptabilityCoordTask(base.BaseAcceptabilityTask): | ||
| pass |
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