mirror of
https://github.com/deepset-ai/haystack.git
synced 2025-08-26 01:16:20 +00:00
d114a994f1
* refractor the to_squad data class * fix the validation label * refractor the to_squad data class * fix the validation label * add the test for the to_label object function * fix the tests for to_label_objects * move all the test related to squad data to one file * remove unused imports * revert tiny_augmented.json Co-authored-by: ZanSara <sarazanzo94@gmail.com>
110 lines
4.1 KiB
Python
110 lines
4.1 KiB
Python
import pandas as pd
|
|
from haystack.utils.squad_data import SquadData
|
|
from haystack.utils.augment_squad import augment_squad
|
|
from ..conftest import SAMPLES_PATH
|
|
from haystack.schema import Document, Label, Answer
|
|
|
|
|
|
def test_squad_augmentation():
|
|
input_ = SAMPLES_PATH / "squad" / "tiny.json"
|
|
output = SAMPLES_PATH / "squad" / "tiny_augmented.json"
|
|
glove_path = SAMPLES_PATH / "glove" / "tiny.txt" # dummy glove file, will not even be use when augmenting tiny.json
|
|
multiplication_factor = 5
|
|
augment_squad(
|
|
model="distilbert-base-uncased",
|
|
tokenizer="distilbert-base-uncased",
|
|
squad_path=input_,
|
|
output_path=output,
|
|
glove_path=glove_path,
|
|
multiplication_factor=multiplication_factor,
|
|
)
|
|
original_squad = SquadData.from_file(input_)
|
|
augmented_squad = SquadData.from_file(output)
|
|
assert original_squad.count(unit="paragraph") == augmented_squad.count(unit="paragraph") * multiplication_factor
|
|
|
|
|
|
def test_squad_to_df():
|
|
df = pd.DataFrame(
|
|
[["title", "context", "question", "id", "answer", 1, False]],
|
|
columns=["title", "context", "question", "id", "answer_text", "answer_start", "is_impossible"],
|
|
)
|
|
expected_result = [
|
|
{
|
|
"title": "title",
|
|
"paragraphs": [
|
|
{
|
|
"context": "context",
|
|
"qas": [
|
|
{
|
|
"question": "question",
|
|
"id": "id",
|
|
"answers": [{"text": "answer", "answer_start": 1}],
|
|
"is_impossible": False,
|
|
}
|
|
],
|
|
}
|
|
],
|
|
}
|
|
]
|
|
|
|
result = SquadData.df_to_data(df)
|
|
|
|
assert result == expected_result
|
|
|
|
|
|
def test_to_label_object():
|
|
squad_data_list = [
|
|
{
|
|
"title": "title",
|
|
"paragraphs": [
|
|
{
|
|
"context": "context",
|
|
"qas": [
|
|
{
|
|
"question": "question",
|
|
"id": "id",
|
|
"answers": [{"text": "answer", "answer_start": 1}],
|
|
"is_impossible": False,
|
|
},
|
|
{
|
|
"question": "another question",
|
|
"id": "another_id",
|
|
"answers": [{"text": "this is the response", "answer_start": 1}],
|
|
"is_impossible": False,
|
|
},
|
|
],
|
|
},
|
|
{
|
|
"context": "the second paragraph context",
|
|
"qas": [
|
|
{
|
|
"question": "the third question",
|
|
"id": "id_3",
|
|
"answers": [{"text": "this is another response", "answer_start": 1}],
|
|
"is_impossible": False,
|
|
},
|
|
{
|
|
"question": "the forth question",
|
|
"id": "id_4",
|
|
"answers": [{"text": "this is the response", "answer_start": 1}],
|
|
"is_impossible": False,
|
|
},
|
|
],
|
|
},
|
|
],
|
|
}
|
|
]
|
|
squad_data = SquadData(squad_data=squad_data_list)
|
|
answer_type = "generative"
|
|
labels = squad_data.to_label_objs(answer_type=answer_type)
|
|
for label, expected_question in zip(labels, squad_data.df.iterrows()):
|
|
expected_question = expected_question[1]
|
|
assert isinstance(label, Label)
|
|
assert isinstance(label.document, Document)
|
|
assert isinstance(label.answer, Answer)
|
|
assert label.query == expected_question["question"]
|
|
assert label.document.content == expected_question.context
|
|
assert label.document.id == expected_question.document_id
|
|
assert label.id == expected_question.id
|
|
assert label.answer.answer == expected_question.answer_text
|