guanjihuan/py.guanjihuan.com
1
1
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

0.1.55

Browse Source
This commit is contained in:
guanjihuan 2023-11-28 21:28:44 +08:00
parent f96bc0da4e
commit 5c1bad3589
3 changed files with 6 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
PyPI/setup.cfg
View File

@ -1,7 +1,7 @@
[metadata] [metadata]
# replace with your username: # replace with your username:
name = guan name = guan
version = 0.1.54 version = 0.1.55
author = guanjihuan author = guanjihuan
author_email = guanjihuan@163.com author_email = guanjihuan@163.com
description = An open source python package description = An open source python package

2
PyPI/src/guan.egg-info/PKG-INFO
View File

@ -1,6 +1,6 @@
Metadata-Version: 2.1 Metadata-Version: 2.1
Name: guan Name: guan
Version: 0.1.54 Version: 0.1.55
Summary: An open source python package Summary: An open source python package
Home-page: https://py.guanjihuan.com Home-page: https://py.guanjihuan.com
Author: guanjihuan Author: guanjihuan

4
PyPI/src/guan/machine_learning.py
View File

@ -1,10 +1,12 @@
# Module: machine_learning # Module: machine_learning
import guan import guan
model_class = None # 把类定义成全局的，防止保存完整模型时，无法访问函数中的类
# 全连接神经网络模型（包含一个隐藏层） # 全连接神经网络模型（包含一个隐藏层）
@guan.function_decorator @guan.function_decorator
def fully_connected_neural_network_with_one_hidden_layer(input_size=1, hidden_size=10, output_size=1, activation='relu'): def fully_connected_neural_network_with_one_hidden_layer(input_size=1, hidden_size=10, output_size=1, activation='relu'):
import torch import torch
global model_class
class model_class(torch.nn.Module): class model_class(torch.nn.Module):
def __init__(self): def __init__(self):
super().__init__() super().__init__()
@ -30,6 +32,7 @@ def fully_connected_neural_network_with_one_hidden_layer(input_size=1, hidden_si
@guan.function_decorator @guan.function_decorator
def fully_connected_neural_network_with_two_hidden_layers(input_size=1, hidden_size_1=10, hidden_size_2=10, output_size=1, activation_1='relu', activation_2='relu'): def fully_connected_neural_network_with_two_hidden_layers(input_size=1, hidden_size_1=10, hidden_size_2=10, output_size=1, activation_1='relu', activation_2='relu'):
import torch import torch
global model_class
class model_class(torch.nn.Module): class model_class(torch.nn.Module):
def __init__(self): def __init__(self):
super().__init__() super().__init__()
@ -68,6 +71,7 @@ def fully_connected_neural_network_with_two_hidden_layers(input_size=1, hidden_s
@guan.function_decorator @guan.function_decorator
def fully_connected_neural_network_with_three_hidden_layers(input_size=1, hidden_size_1=10, hidden_size_2=10, hidden_size_3=10, output_size=1, activation_1='relu', activation_2='relu', activation_3='relu'): def fully_connected_neural_network_with_three_hidden_layers(input_size=1, hidden_size_1=10, hidden_size_2=10, hidden_size_3=10, output_size=1, activation_1='relu', activation_2='relu', activation_3='relu'):
import torch import torch
global model_class
class model_class(torch.nn.Module): class model_class(torch.nn.Module):
def __init__(self): def __init__(self):
super().__init__() super().__init__()