From 0363b5fcf6655df5af4932df238023b649dc4337 Mon Sep 17 00:00:00 2001
From: guanjihuan <guanjihuan@163.com>
Date: Sun, 9 Jun 2024 05:26:20 +0800
Subject: [PATCH] 0.1.107

---
 PyPI/setup.cfg                    |  2 +-
 PyPI/src/guan.egg-info/PKG-INFO   |  2 +-
 PyPI/src/guan/machine_learning.py | 20 ++++++++++++++++++++
 3 files changed, 22 insertions(+), 2 deletions(-)

diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg
index 59f7c13..b3c0a85 100644
--- a/PyPI/setup.cfg
+++ b/PyPI/setup.cfg
@@ -1,7 +1,7 @@
 [metadata]
 # replace with your username:
 name = guan
-version = 0.1.106
+version = 0.1.107
 author = guanjihuan
 author_email = guanjihuan@163.com
 description = An open source python package
diff --git a/PyPI/src/guan.egg-info/PKG-INFO b/PyPI/src/guan.egg-info/PKG-INFO
index 79b2fed..39f5c1f 100644
--- a/PyPI/src/guan.egg-info/PKG-INFO
+++ b/PyPI/src/guan.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: guan
-Version: 0.1.106
+Version: 0.1.107
 Summary: An open source python package
 Home-page: https://py.guanjihuan.com
 Author: guanjihuan
diff --git a/PyPI/src/guan/machine_learning.py b/PyPI/src/guan/machine_learning.py
index d0c60f1..f47fd53 100644
--- a/PyPI/src/guan/machine_learning.py
+++ b/PyPI/src/guan/machine_learning.py
@@ -254,6 +254,14 @@ def save_model(model, filename='./model.pth'):
     import torch
     torch.save(model, filename)
 
+# 以字典的形式保存模型的所有信息到文件（保存时需要模型的类可访问）
+def save_model_with_all_information(model, model_class, note='', filename='./model_with_all_information.pth'):
+    import torch
+    checkpoint = {'model_state_dict': model.state_dict(),
+                  'model_class': model_class,
+                  'note': note,}
+    torch.save(checkpoint, filename)
+
 # 加载模型参数（需要输入模型，加载后，原输入的模型参数也会改变）
 def load_model_parameters(model, filename='./model_parameters.pth'):
     import torch
@@ -266,6 +274,18 @@ def load_model(filename='./model.pth'):
     model = torch.load(filename)
     return model
 
+# 加载包含所有信息的模型（包含了模型的类，返回的是对象）
+def load_model_with_all_information(filename='./model_with_all_information.pth', note_print=0):
+    import torch
+    checkpoint = torch.load(filename)
+    model_class = checkpoint['model_class']
+    model = model_class()
+    model.load_state_dict(checkpoint['model_state_dict'])
+    if note_print==1:
+        note = checkpoint['note']
+        print(note)
+    return model
+
 # 加载训练数据，用于批量加载训练
 def load_train_data(x_train, y_train, batch_size=32):
     from torch.utils.data import DataLoader, TensorDataset