def test_init_model_card_info_obj(self):
@Model.register("fake-model-3")
class FakeModel(Model):
"""
This is a fake model with a docstring.
# Parameters
fake_param1: str
fake_param2: int
"""
def forward(self, **kwargs):
return {}
intended_use = IntendedUse("Use 1", "User 1")
model_card = ModelCard(
**{
"id": "this-fake-model",
"registered_model_name": "fake-model-3",
"intended_use": intended_use,
})
model_card_dict = model_card.to_dict()
assert model_card.display_name == "FakeModel"
for key, val in intended_use.__dict__.items():
if val:
assert key in model_card_dict
else:
assert key not in model_card_dict
def test_init_registered_model_override(self):
@Model.register("fake-model-2")
class FakeModel(Model):
"""
This is a fake model with a docstring.
# Parameters
fake_param1: str
fake_param2: int
"""
def forward(self, **kwargs):
return {}
model_card = ModelCard(
**{
"id": "this-fake-model",
"registered_model_name": "fake-model-2",
"model_details":
"This is the fake model trained on a dataset.",
"model_class": FakeModel,
})
assert (model_card.model_details.description ==
"This is the fake model trained on a dataset.")
def test_init(self):
model_card = ModelCard(
id="fake_name",
display_name="Fake Name",
model_details="Model's description",
archive_file="fake.tar.gz",
overrides={},
)
assert model_card.id == "fake_name"
assert model_card.display_name == "Fake Name"
assert model_card.archive_file == ModelCard._storage_location + "fake.tar.gz"
assert model_card.model_details.description == "Model's description"
def test_init(self):
model_card = ModelCard(
id="fake_name",
display_name="Fake Name",
model_details="Model's description",
model_usage=ModelUsage(**{
"archive_file": "fake.tar.gz",
"overrides": {}
}),
)
assert model_card.id == "fake_name"
assert model_card.display_name == "Fake Name"
assert model_card.model_usage.archive_file == ModelUsage._storage_location + "fake.tar.gz"
assert model_card.model_details.description == "Model's description"
def get_pretrained_models() -> Dict[str, ModelCard]:
"""
Returns a mapping of [`ModelCard`](/models/common/model_card#modelcard)s for all
available pretrained models.
"""
pretrained_models = {}
model_card_paths = os.path.join(
os.path.dirname(os.path.realpath(__file__)), "modelcards", "*.json")
for model_card_path in glob.glob(model_card_paths):
if "template" not in model_card_path:
model_card = ModelCard.from_params(
params=Params.from_file(model_card_path))
pretrained_models[model_card.id] = model_card
return pretrained_models
def test_init_dict_model(self):
class FakeModel(Model):
"""
This is a fake model with a docstring.
# Parameters
fake_param1: str
fake_param2: int
"""
def forward(self, **kwargs):
return {}
model_card = ModelCard(**{
"id": "this-fake-model",
"model_class": FakeModel
})
assert model_card.display_name == "FakeModel"
assert model_card.model_details.description == "This is a fake model with a docstring."
def test_nested_json(self):
@Model.register("fake-model-4")
class FakeModel(Model):
"""
This is a fake model with a docstring.
# Parameters
fake_param1: str
fake_param2: int
"""
def forward(self, **kwargs):
return {}
model_card = ModelCard.from_params(
Params({
"id": "this-fake-model",
"registered_model_name": "fake-model-4",
"model_details": {
"description":
"This is the fake model trained on a dataset.",
"paper": {
"title": "paper name",
"url": "paper link",
"citation": "test citation",
},
},
"training_data": {
"dataset": {
"name": "dataset 1",
"url": "dataset url"
}
},
}))
assert isinstance(model_card.model_details.paper, Paper)
assert model_card.model_details.paper.url == "paper link"
assert model_card.training_data.dataset.name == "dataset 1"