''' Copyright (c) 2024 Beijing Volcano Engine Technology Ltd. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. ''' import base64 import os import tempfile import unittest from copy import deepcopy from unittest import TestCase import numpy as np import torch import veturboio import veturboio.ops.sfcs_utils as sfcs_utils def init_sfcs_env(): sfcs_conf = os.getcwd() + '/libcfs.xml' if os.path.exists(sfcs_conf): os.remove(sfcs_conf) os.environ['SFCS_FSNAME'] = 'byted-cpu-sfcs' os.environ['SFCS_REGION'] = 'cn-beijing' os.environ['SFCS_ACCESS_KEY'] = os.environ['CI_SFCS_AK'] os.environ['SFCS_SECRET_KEY'] = os.environ['CI_SFCS_SK'] os.environ['SFCS_AUTHENTICATION_SERVICE_NAME'] = 'cfs' os.environ['SFCS_NS_ID'] = '18014398509481988' os.environ['SFCS_UFS_PATH'] = 'tos://yinzq-bucket/' os.environ['SFCS_MULTI_NIC_WHITELIST'] = 'eth0' os.environ['SFCS_NETWORK_SEGMENT'] = '172.31.128.0/17' os.environ['SFCS_NAMENODE_ENDPOINT_ADDRESS'] = '100.67.19.231' os.environ['SFCS_LOG_SEVERITY'] = 'ERROR' sfcs_utils.init_sfcs_conf() class TestSFCS(TestCase): @classmethod def setUpClass(cls): init_sfcs_env() def _run_pipeline(self): filepath = "/data.bin" filesize = 1024 * 1024 sfcs_utils.sfcs_delete_file(filepath) arr_0 = np.empty([filesize], dtype=np.byte) length = sfcs_utils.sfcs_write_file(filepath, arr_0, filesize) self.assertEqual(length, filesize) size = sfcs_utils.sfcs_get_file_size(filepath) self.assertEqual(size, filesize) arr_1 = np.empty([filesize], dtype=np.byte) length = sfcs_utils.sfcs_read_file(filepath, arr_1, filesize, 0) self.assertEqual(length, filesize) self.assertTrue((arr_0 == arr_1).all()) sfcs_utils.sfcs_delete_file(filepath) def test_pipeline(self): self._run_pipeline() class TestSFCSLoad(TestCase): @classmethod def setUpClass(cls): init_sfcs_env() # key / iv os.environ['VETURBOIO_KEY'] = base64.b64encode(b'abcdefgh12345678').decode('ascii') os.environ['VETURBOIO_IV'] = base64.b64encode(b'1234567887654321').decode('ascii') # kms info ENV_KMS_HOST = 'VETURBOIO_KMS_HOST' ENV_KMS_REGION = 'VETURBOIO_KMS_REGION' ENV_KMS_AK = 'VETURBOIO_KMS_ACCESS_KEY' ENV_KMS_SK = 'VETURBOIO_KMS_SECRET_KEY' ENV_KMS_KEYRING = 'VETURBOIO_KMS_KEYRING_NAME' ENV_KMS_KEY = 'VETURBOIO_KMS_KEY_NAME' os.environ[ENV_KMS_HOST] = 'open.volcengineapi.com' os.environ[ENV_KMS_REGION] = 'cn-beijing' os.environ[ENV_KMS_AK] = os.environ['CI_VENDOR_AK'] os.environ[ENV_KMS_SK] = os.environ['CI_VENDOR_SK'] os.environ[ENV_KMS_KEYRING] = 'datapipe_keyring' os.environ[ENV_KMS_KEY] = 'datapipe_key_ml_maas' cls.filepath_0 = "sfcs://model.safetensors" cls.filepath_1 = "sfcs://model.pt" # mock /tmp as efs mount path cls.filepath_2 = "/model.safetensors" cls.tensors_0 = { "weight1": torch.ones(500, 50), "weight2": torch.zeros(500, 50), } class MockModel(torch.nn.Module): def __init__(self) -> None: super().__init__() self.linear1 = torch.nn.Linear(500, 50) self.linear2 = torch.nn.Linear(500, 50) cls.model = MockModel() if torch.cuda.is_available(): cls.cuda_tensors_0 = deepcopy(cls.tensors_0) for key in cls.cuda_tensors_0.keys(): cls.cuda_tensors_0[key] = cls.cuda_tensors_0[key].cuda() cls.cuda_model = MockModel().cuda() @classmethod def tearDownClass(cls): sfcs_utils.sfcs_delete_file(cls.filepath_0[6:]) sfcs_utils.sfcs_delete_file(cls.filepath_1[6:]) def _run_pipeline(self, tensors, model, map_location, use_cipher): veturboio.save_file(tensors, self.filepath_0, use_cipher=use_cipher) loaded_tensors = veturboio.load(self.filepath_0, map_location=map_location, use_cipher=use_cipher) for key in tensors.keys(): self.assertTrue(torch.allclose(tensors[key], loaded_tensors[key])) veturboio.save_model(model, self.filepath_0, use_cipher=use_cipher) loaded_tensors = veturboio.load(self.filepath_0, map_location=map_location, use_cipher=use_cipher) state_dict = model.state_dict() for key in state_dict.keys(): self.assertTrue(torch.allclose(state_dict[key], loaded_tensors[key])) veturboio.save_pt(state_dict, self.filepath_1, use_cipher=use_cipher) loaded_tensors = veturboio.load(self.filepath_1, map_location=map_location, use_cipher=use_cipher) for key in state_dict.keys(): self.assertTrue(torch.allclose(state_dict[key], loaded_tensors[key])) os.environ['VETURBOIO_USE_SFCS_SDK'] = '1' loaded_tensors = veturboio.load(self.filepath_2, map_location=map_location, use_cipher=use_cipher) del os.environ['VETURBOIO_USE_SFCS_SDK'] state_dict = model.state_dict() for key in state_dict.keys(): self.assertTrue(torch.allclose(state_dict[key], loaded_tensors[key])) def test_pipeline_cpu(self): self._run_pipeline(self.tensors_0, self.model, "cpu", use_cipher=False) self._run_pipeline(self.tensors_0, self.model, "cpu", use_cipher=True) @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available") def test_pipeline_cuda(self): self._run_pipeline(self.cuda_tensors_0, self.cuda_model, "cuda:0", use_cipher=False) self._run_pipeline(self.cuda_tensors_0, self.cuda_model, "cuda:0", use_cipher=True) def test_pipeline_cipher_header_cpu(self): os.environ["VETURBOIO_CIPHER_HEADER"] = "1" self._run_pipeline(self.tensors_0, self.model, "cpu", use_cipher=True) del os.environ["VETURBOIO_CIPHER_HEADER"] @unittest.skipIf(not torch.cuda.is_available(), "CUDA not available") def test_pipeline_cipher_header_cuda(self): os.environ["VETURBOIO_CIPHER_HEADER"] = "1" self._run_pipeline(self.cuda_tensors_0, self.cuda_model, "cuda:0", use_cipher=True) del os.environ["VETURBOIO_CIPHER_HEADER"]