mirror of
https://github.com/modelscope/modelscope.git
synced 2025-12-16 16:27:45 +01:00
Link: https://code.alibaba-inc.com/Ali-MaaS/MaaS-lib/codereview/9662182 * clean up test level
69 lines
3.0 KiB
Python
69 lines
3.0 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
|
|
|
|
import unittest
|
|
|
|
from modelscope.models import Model
|
|
from modelscope.pipelines import pipeline
|
|
from modelscope.utils.constant import Tasks
|
|
from modelscope.utils.test_utils import test_level
|
|
|
|
|
|
class GEMMMultiModalEmbeddingTest(unittest.TestCase):
|
|
model_id = 'damo/multi-modal_gemm-vit-large-patch14_generative-multi-modal-embedding'
|
|
test_input = {
|
|
'image': 'data/test/images/generative_multimodal.jpg',
|
|
'text':
|
|
'interior design of modern living room with fireplace in a new house',
|
|
'captioning': False
|
|
}
|
|
|
|
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
|
|
def test_run(self):
|
|
generative_multi_modal_embedding_pipeline = pipeline(
|
|
Tasks.generative_multi_modal_embedding, model=self.model_id)
|
|
output = generative_multi_modal_embedding_pipeline(self.test_input)
|
|
print(output)
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
def test_run_with_default_model(self):
|
|
generative_multi_modal_embedding_pipeline = pipeline(
|
|
task=Tasks.generative_multi_modal_embedding)
|
|
output = generative_multi_modal_embedding_pipeline(self.test_input)
|
|
print(output)
|
|
|
|
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
|
|
def test_run_with_model_from_modelhub(self):
|
|
model = Model.from_pretrained(self.model_id)
|
|
generative_multi_modal_embedding_pipeline = pipeline(
|
|
task=Tasks.generative_multi_modal_embedding, model=model)
|
|
output = generative_multi_modal_embedding_pipeline(self.test_input)
|
|
print(output)
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
def test_run_with_output_captioning(self):
|
|
generative_multi_modal_embedding_pipeline = pipeline(
|
|
task=Tasks.generative_multi_modal_embedding, model=self.model_id)
|
|
test_input = {'image': self.test_input['image'], 'captioning': True}
|
|
output = generative_multi_modal_embedding_pipeline(test_input)
|
|
print(output)
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
def test_run_with_output_only_image(self):
|
|
generative_multi_modal_embedding_pipeline = pipeline(
|
|
task=Tasks.generative_multi_modal_embedding, model=self.model_id)
|
|
test_input = {'image': self.test_input['image'], 'captioning': False}
|
|
output = generative_multi_modal_embedding_pipeline(test_input)
|
|
print(output)
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
def test_run_with_output_only_text(self):
|
|
generative_multi_modal_embedding_pipeline = pipeline(
|
|
task=Tasks.generative_multi_modal_embedding, model=self.model_id)
|
|
test_input = {'text': self.test_input['text']}
|
|
output = generative_multi_modal_embedding_pipeline(test_input)
|
|
print(output)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|