def test_can_batch_launch_custom_model(self):
class TestExtractor(Extractor):
def __iter__(self):
for i in range(5):
yield DatasetItem(id=i,
subset='train',
image=np.array([i]))
class TestLauncher(Launcher):
def launch(self, inputs):
for i, inp in enumerate(inputs):
yield [Label(attributes={'idx': i, 'data': inp.item()})]
model_name = 'model'
launcher_name = 'custom_launcher'
project = Project()
project.env.launchers.register(launcher_name, TestLauncher)
project.add_model(model_name, {'launcher': launcher_name})
model = project.make_executable_model(model_name)
extractor = TestExtractor()
batch_size = 3
executor = InferenceWrapper(extractor, model, batch_size=batch_size)
for item in executor:
self.assertEqual(1, len(item.annotations))
self.assertEqual(
int(item.id) % batch_size,
item.annotations[0].attributes['idx'])
self.assertEqual(int(item.id),
item.annotations[0].attributes['data'])
def test_can_batch_launch_custom_model(self):
dataset = Dataset.from_iterable([
DatasetItem(id=i, subset='train', image=np.array([i]))
for i in range(5)
],
categories=['label'])
class TestLauncher(Launcher):
def launch(self, inputs):
for i, inp in enumerate(inputs):
yield [Label(0, attributes={'idx': i, 'data': inp.item()})]
model_name = 'model'
launcher_name = 'custom_launcher'
project = Project()
project.env.launchers.register(launcher_name, TestLauncher)
project.add_model(model_name, {'launcher': launcher_name})
model = project.make_executable_model(model_name)
batch_size = 3
executor = ModelTransform(dataset, model, batch_size=batch_size)
for item in executor:
self.assertEqual(1, len(item.annotations))
self.assertEqual(
int(item.id) % batch_size,
item.annotations[0].attributes['idx'])
self.assertEqual(int(item.id),
item.annotations[0].attributes['data'])
def test_can_batch_launch_custom_model(self):
class TestExtractor(Extractor):
def __init__(self, url, n=0):
super().__init__(length=n)
self.n = n
def __iter__(self):
for i in range(self.n):
yield DatasetItem(id=i, subset='train', image=i)
def subsets(self):
return ['train']
class TestLauncher(Launcher):
def __init__(self, **kwargs):
pass
def launch(self, inputs):
for i, inp in enumerate(inputs):
yield [LabelObject(attributes={'idx': i, 'data': inp})]
model_name = 'model'
launcher_name = 'custom_launcher'
project = Project()
project.env.launchers.register(launcher_name, TestLauncher)
project.add_model(model_name, {'launcher': launcher_name})
model = project.make_executable_model(model_name)
extractor = TestExtractor('', n=5)
batch_size = 3
executor = InferenceWrapper(extractor, model, batch_size=batch_size)
for item in executor:
self.assertEqual(1, len(item.annotations))
self.assertEqual(
int(item.id) % batch_size,
item.annotations[0].attributes['idx'])
self.assertEqual(int(item.id),
item.annotations[0].attributes['data'])
