将 TensorFlow 模型保存到 Google Drive 可以通过以下步骤完成:
步骤 1:创建 Google Drive API 凭据
步骤 2:连接到 Google Drive API
import os
from pydrive.auth import GoogleAuth
from pydrive.drive import GoogleDrive
gauth = GoogleAuth()
gauth.credentials = GoogleCredentials.from_json("path/to/client_secrets.json")
drive = GoogleDrive(gauth)
步骤 3:保存 TensorFlow 模型到 Google Drive 假设你已经有一个 TensorFlow 模型(例如,saved_model.pb 文件和 variables 目录)。
model_folder = drive.CreateFile({'title': 'My TensorFlow Model', 'mimeType': 'application/vnd.google-apps.folder'})
model_folder.Upload()
model_file = drive.CreateFile({'title': 'saved_model.pb', 'parents': [{'id': model_folder['id']}]})
model_file.SetContentFile('path/to/saved_model.pb')
model_file.Upload()
variables_folder = drive.CreateFile({'title': 'variables', 'mimeType': 'application/vnd.google-apps.folder', 'parents': [{'id': model_folder['id']}]})
variables_folder.Upload()
for file in os.listdir('path/to/variables'):
variable_file = drive.CreateFile({'title': file, 'parents': [{'id': variables_folder['id']}]})
variable_file.SetContentFile('path/to/variables/' + file)
variable_file.Upload()
步骤 4:获取 Google Drive 上的 TensorFlow 模型 使用以下代码从 Google Drive 上获取保存的模型:
model_folder = drive.ListFile({'q': "'root' in parents and trashed=false"}).GetList()[0]
model_files = drive.ListFile({'q': f"'{model_folder['id']}' in parents and trashed=false"}).GetList()
saved_model_pb = next((file for file in model_files if file['title'] == 'saved_model.pb'), None)
variables_folder = next((file for file in model_files if file['title'] == 'variables' and file['mimeType'] == 'application/vnd.google-apps.folder'), None)
variable_files = drive.ListFile({'q': f"'{variables_folder['id']}' in parents and trashed=false"}).GetList()
for file in model_files:
file.GetContentFile('path/to/save/' + file['title'])
for file in variable_files:
file.GetContentFile('path/to/save/' + file['title'])
请注意,这里使用了 PyDrive 库来连接到 Google Drive API,并上传/下载模型文件。在代码中,你需要将路径(path/to/client_secrets.json、path/to/saved_model.pb、path/to/variables)替换为适当的文件路径。
参考文档:
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