PyAiNetwork is a lightweight library for creating and training small to medium-sized neural networks.
Project description
PyAiNetwork
PyAiNetork - this is a lightweight library to create small to medium-sized LM's.
Main functions
- Creating neural networks
- neural network training
- learning and counting through numpy tables
Installation
pip install PyAiNetwork
examples of use normal
from PyAiNetwork import Network
net = Network(
4, #input
1, #layers
1, #neorons on layer
4 #output
'gelu' #activition function
)
input = [0.2,0.4,0.6,0.8]
output = net.forward(input)
print(output)
for i in range(1000):
net.train(
input, #input
input, #output
0.01 #learing rate
)
output = net.forward(input)
print(output)
examples of use profi
from PyAiNetwork import ProfNetwork
layers_neorons = [1]
net = ProfNetwork(
4, #input
layers_neorons, #layers
4, #output
'gelu', #activition function
'matrix' # math type (or every)
)
input = [0.2,0.4,0.6,0.8]
output = net.forward(input)
print(output)
for i in range(1000):
net.train(
input, #input
input, #output
0.01 #learing rate
)
output = net.forward(input)
print(output)
net.save("save.json") #json file name
net2 = ProfNetwork(
4, #input
layers_neorons, #layers
4, #output
'gelu', #activition function
'matrix' # math type (or every)
)
net2.load("save.json") #json file name
output = net2.forward(input)
print(output)
GitHub
https://github.com/eyes-studio/PyAiNetwork
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyainetwork-0.3.8.tar.gz
(5.4 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file pyainetwork-0.3.8.tar.gz.
File metadata
- Download URL: pyainetwork-0.3.8.tar.gz
- Upload date:
- Size: 5.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
6170eca89affd98731d266aa7376d35d69a2987107144c565347589c324fcdeb
|
|
| MD5 |
89df611fa7ca2b11391c373b5260d3cd
|
|
| BLAKE2b-256 |
cbdf25b5b651df668b797e2f6bdcb0c9bc146bece056c15bd6c665d40645739e
|
File details
Details for the file pyainetwork-0.3.8-py3-none-any.whl.
File metadata
- Download URL: pyainetwork-0.3.8-py3-none-any.whl
- Upload date:
- Size: 5.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
35973255383171c2cdd111da0e5a3faf9cba012077013a174bc1d9eafd541eae
|
|
| MD5 |
9652840ac2fb965e1de3221c30564fbe
|
|
| BLAKE2b-256 |
c2acd8c2b8db1c24e2c2c59f0d52f1b44bf9e9e7b2f8564a72501c68417f290b
|