Gene
2 years ago
2 changed files with 0 additions and 108 deletions
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tests/test_learnware_client/test_docker.py
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| import os | |||
| import zipfile | |||
| import numpy as np | |||
| import learnware | |||
| from learnware.client import LearnwareClient | |||
| from learnware.client.container import LearnwaresContainer | |||
| from learnware.learnware.reuse import AveragingReuser | |||
| if __name__ == "__main__": | |||
| email = "liujd@lamda.nju.edu.cn" | |||
| token = "f7e647146a314c6e8b4e2e1079c4bca4" | |||
| client = LearnwareClient() | |||
| client.login(email, token) | |||
| root = os.path.dirname(__file__) | |||
| learnware_ids = ["00000084", "00000154", "00000155"] | |||
| zip_paths = [os.path.join(root, x) for x in ["1.zip", "2.zip", "3.zip"]] | |||
| for learnware_id, zip_path in zip(learnware_ids, zip_paths): | |||
| client.download_learnware(learnware_id, zip_path) | |||
| learnware_list = [client.load_learnware(learnware_path=zippath) for zippath in zip_paths] | |||
| with LearnwaresContainer(learnware_list, zip_paths, mode="docker") as env_container: | |||
| learnware_list = env_container.get_learnwares_with_container() | |||
| reuser = AveragingReuser(learnware_list, mode="vote_by_label") | |||
| input_array = np.random.random(size=(20, 13)) | |||
| print(reuser.predict(input_array)) | |||
| for learnware in learnware_list: | |||
| print(learnware.id, learnware.predict(input_array)) | |||
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tests/test_learnware_client/test_load.py
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| import os | |||
| import unittest | |||
| import zipfile | |||
| import numpy as np | |||
| import learnware | |||
| from learnware.learnware import get_learnware_from_dirpath | |||
| from learnware.client import LearnwareClient | |||
| from learnware.client.container import ModelCondaContainer, LearnwaresContainer | |||
| from learnware.learnware.reuse import AveragingReuser | |||
| class TestLearnwareLoad(unittest.TestCase): | |||
| def setUp(self): | |||
| unittest.TestCase.setUpClass() | |||
| email = "liujd@lamda.nju.edu.cn" | |||
| token = "f7e647146a314c6e8b4e2e1079c4bca4" | |||
| self.client = LearnwareClient() | |||
| self.client.login(email, token) | |||
| root = os.path.dirname(__file__) | |||
| self.learnware_ids = ["00000084", "00000154", "00000155"] | |||
| self.zip_paths = [os.path.join(root, x) for x in ["1.zip", "2.zip", "3.zip"]] | |||
| def test_load_single_learnware_by_zippath(self): | |||
| for learnware_id, zip_path in zip(self.learnware_ids, self.zip_paths): | |||
| self.client.download_learnware(learnware_id, zip_path) | |||
| learnware_list = [ | |||
| self.client.load_learnware(learnware_path=zippath, runnable_option="conda_env") | |||
| for zippath in self.zip_paths | |||
| ] | |||
| reuser = AveragingReuser(learnware_list, mode="vote_by_label") | |||
| input_array = np.random.random(size=(20, 13)) | |||
| print(reuser.predict(input_array)) | |||
| for learnware in learnware_list: | |||
| print(learnware.id, learnware.predict(input_array)) | |||
| def test_load_multi_learnware_by_zippath(self): | |||
| for learnware_id, zip_path in zip(self.learnware_ids, self.zip_paths): | |||
| self.client.download_learnware(learnware_id, zip_path) | |||
| learnware_list = self.client.load_learnware(learnware_path=self.zip_paths, runnable_option="conda_env") | |||
| reuser = AveragingReuser(learnware_list, mode="vote_by_label") | |||
| input_array = np.random.random(size=(20, 13)) | |||
| print(reuser.predict(input_array)) | |||
| for learnware in learnware_list: | |||
| print(learnware.id, learnware.predict(input_array)) | |||
| def test_load_single_learnware_by_id(self): | |||
| learnware_list = [ | |||
| self.client.load_learnware(learnware_id=idx, runnable_option="conda_env") for idx in self.learnware_ids | |||
| ] | |||
| reuser = AveragingReuser(learnware_list, mode="vote_by_label") | |||
| input_array = np.random.random(size=(20, 13)) | |||
| print(reuser.predict(input_array)) | |||
| for learnware in learnware_list: | |||
| print(learnware.id, learnware.predict(input_array)) | |||
| def test_load_multi_learnware_by_id(self): | |||
| learnware_list = self.client.load_learnware(learnware_id=self.learnware_ids, runnable_option="conda_env") | |||
| reuser = AveragingReuser(learnware_list, mode="vote_by_label") | |||
| input_array = np.random.random(size=(20, 13)) | |||
| print(reuser.predict(input_array)) | |||
| for learnware in learnware_list: | |||
| print(learnware.id, learnware.predict(input_array)) | |||
| if __name__ == "__main__": | |||
| unittest.main() | |||