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modelscope/tests/pipelines/test_multi_modal_embedding.py

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# Copyright (c) Alibaba, Inc. and its affiliates.
import unittest
import torch
from modelscope.models import Model
from modelscope.outputs import OutputKeys
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
from modelscope.utils.demo_utils import DemoCompatibilityCheck
from modelscope.utils.test_utils import test_level
class MultiModalEmbeddingTest(unittest.TestCase, DemoCompatibilityCheck):
def setUp(self) -> None:
self.task = Tasks.multi_modal_embedding
self.model_id = 'damo/multi-modal_clip-vit-base-patch16_zh'
test_input = {'text': '皮卡丘'}
model_version = 'dev'
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
def test_run(self):
pipeline_multi_modal_embedding = pipeline(
Tasks.multi_modal_embedding,
model=self.model_id,
model_revision=self.model_version)
text_embedding = pipeline_multi_modal_embedding(
self.test_input)[OutputKeys.TEXT_EMBEDDING]
print('l1-norm: {}'.format(
torch.norm(text_embedding, p=1, dim=-1).item()))
print('l2-norm: {}'.format(torch.norm(text_embedding,
dim=-1).item())) # should be 1.0
@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, revision=self.model_version)
pipeline_multi_modal_embedding = pipeline(
task=Tasks.multi_modal_embedding, model=model)
text_embedding = pipeline_multi_modal_embedding(
self.test_input)[OutputKeys.TEXT_EMBEDDING]
print('l1-norm: {}'.format(
torch.norm(text_embedding, p=1, dim=-1).item()))
print('l2-norm: {}'.format(torch.norm(text_embedding,
dim=-1).item())) # should be 1.0
@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
def test_run_with_default_model(self):
pipeline_multi_modal_embedding = pipeline(
task=Tasks.multi_modal_embedding,
model_revision=self.model_version)
text_embedding = pipeline_multi_modal_embedding(
self.test_input)[OutputKeys.TEXT_EMBEDDING]
print('l1-norm: {}'.format(
torch.norm(text_embedding, p=1, dim=-1).item()))
print('l2-norm: {}'.format(torch.norm(text_embedding,
dim=-1).item())) # should be 1.0
@unittest.skip('demo compatibility test is only enabled on a needed-basis')
def test_demo_compatibility(self):
self.compatibility_check()
if __name__ == '__main__':
unittest.main()