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import pytest
import markdown
from bs4 import BeautifulSoup
from compliance_checks.intended_purpose import (
IntendedPurposeCheck, IntendedPurposeResult,
)
model_card_template = """\
## Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
### Direct Use
Here is some info about direct uses...
### Downstream Use [optional]
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
[More Information Needed]
### Out-of-Scope Use
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
Here is some info about out-of-scope uses...
"""
albert_base_v2 = """\
# ALBERT Base v2
## Intended uses & limitations
Here is some info about direct uses...
"""
distilbert_base_cased_distilled_squad = """\
# DistilBERT base cased distilled SQuAD
## Uses
This model can be used for question answering.
"""
distilroberta_base = """\
# Model Card for DistilRoBERTa base
# Uses
You can use the raw model for masked language modeling, but it's mostly intended to be fine-tuned on a downstream task.
"""
openai_clip_vit_base_patch = """\
# Model Card: CLIP
## Model Use
Stuff.
### Intended Use
Stuff.
#### Primary intended uses
Stuff.
### Out-of-Scope Use Cases
Stuff.
"""
sentence_transformers = """\
# all-MiniLM-L6-v2
## Intended uses
Our model is intented to be used as a sentence and short paragraph encoder.
"""
success_result = IntendedPurposeResult(
status=True
)
@pytest.mark.parametrize("card", [
model_card_template,
albert_base_v2,
distilbert_base_cased_distilled_squad,
distilroberta_base,
openai_clip_vit_base_patch,
sentence_transformers,
])
def test_run_checks(card):
model_card_html = markdown.markdown(card)
card_soup = BeautifulSoup(model_card_html, features="html.parser")
results = IntendedPurposeCheck().run_check(card_soup)
assert results == success_result
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