2022-06-27 11:57:22 +08:00
|
|
|
# Copyright (c) Alibaba, Inc. and its affiliates.
|
|
|
|
|
|
|
|
|
|
import unittest
|
|
|
|
|
|
|
|
|
|
import numpy as np
|
|
|
|
|
|
|
|
|
|
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 MultiModalEmbeddingTest(unittest.TestCase):
|
2022-08-09 17:31:30 +08:00
|
|
|
model_id = 'damo/multi-modal_clip-vit-large-patch14_zh'
|
2022-06-27 11:57:22 +08:00
|
|
|
test_text = {'text': '一张风景图'}
|
|
|
|
|
|
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
|
|
|
def test_run(self):
|
|
|
|
|
pipe_line_multi_modal_embedding = pipeline(
|
|
|
|
|
Tasks.multi_modal_embedding, model=self.model_id)
|
|
|
|
|
test_str_embedding = pipe_line_multi_modal_embedding(
|
|
|
|
|
self.test_text)['text_embedding']
|
|
|
|
|
print(np.sum(np.abs(test_str_embedding)))
|
|
|
|
|
|
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
|
|
|
def test_run_with_model_from_modelhub(self):
|
|
|
|
|
model = Model.from_pretrained(self.model_id)
|
|
|
|
|
pipe_line_multi_modal_embedding = pipeline(
|
|
|
|
|
task=Tasks.multi_modal_embedding, model=model)
|
|
|
|
|
test_str_embedding = pipe_line_multi_modal_embedding(
|
|
|
|
|
self.test_text)['text_embedding']
|
|
|
|
|
print(np.sum(np.abs(test_str_embedding)))
|
|
|
|
|
|
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
|
|
|
def test_run_with_model_name(self):
|
|
|
|
|
pipe_line_multi_modal_embedding = pipeline(
|
|
|
|
|
task=Tasks.multi_modal_embedding, model=self.model_id)
|
|
|
|
|
test_str_embedding = pipe_line_multi_modal_embedding(
|
|
|
|
|
self.test_text)['text_embedding']
|
|
|
|
|
print(np.sum(np.abs(test_str_embedding)))
|
|
|
|
|
|
|
|
|
|
@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
|
|
|
|
|
def test_run_with_default_model(self):
|
|
|
|
|
pipe_line_multi_modal_embedding = pipeline(
|
|
|
|
|
task=Tasks.multi_modal_embedding)
|
|
|
|
|
test_str_embedding = pipe_line_multi_modal_embedding(
|
|
|
|
|
self.test_text)['text_embedding']
|
|
|
|
|
print(np.sum(np.abs(test_str_embedding)))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
|
|
unittest.main()
|