From a97aacc3c300c96c964f7a0001f1f17c1001dd57 Mon Sep 17 00:00:00 2001 From: manu12121999 Date: Tue, 10 Dec 2024 00:16:48 +0100 Subject: [PATCH] add information header --- README.md | 32 +++++++++++++++++--------------- ctrl_c_nn.py | 7 ++++++- 2 files changed, 23 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index b5c35f3..1b8c307 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,7 @@ # Ctrl_C_NN -Dependency-free neural network inference framework in a single file +Dependency-free neural network inference framework in a single file. + +CURRENTLY IN DEVELOPMENT: NOT IN A USABLE STATE YET ## What is it for Inference with simple neural networks where installing dependencies is not possible. This project is and will be dependency-free and has the most open open-source license. Whatever you need it for, just copy the single .py file into your project, and you can run an already-trained neural network. @@ -8,20 +10,20 @@ Inference with simple neural networks where installing dependencies is not possi Since it is written 100% in Python, its performance is terrible compared to PyTorch or numpy-based frameworks. It's not designed for the training of neural networks but to load and run simple Pytorch neural networks. ## WIP -| Description | Status | -|------------------------------------------|------------------------| -| Base Tensor class | :white_check_mark: | -| Tensor operations (+, *, @) | :white_check_mark: | -| Tensor Broadcasting | :white_check_mark: | -| Tensor Shape Manipulation (e.g. reshape) | :white_check_mark: | -| Simple Layers and Non-linearities | :white_check_mark: | -| Forward pass of simple NN | :large_orange_diamond: | -| Backward pass of simple NN | :large_orange_diamond: | -| Convolutional Layers | :x: | -| Reading pth files | :x: | -| Basic Image I/O | :x: | -| ... | :x: | -| ... | :x: | +| Description | Status | +|------------------------------------------|----------------------------| +| Base Tensor class | :white_check_mark: | +| Tensor operations (+, *, @) | :white_check_mark: | +| Tensor Broadcasting | :white_check_mark: | +| Tensor Shape Manipulation (e.g. reshape) | :white_check_mark: | +| Simple Layers and Non-linearities | :white_check_mark: | +| Forward pass of simple NN | :large_orange_diamond: WIP | +| Backward pass of simple NN | :large_orange_diamond: WIP | +| Convolutional Layers | :x: | +| Reading pth files | :x: | +| Basic Image I/O | :x: | +| ... | :x: | +| ... | :x: | ## Sample Usage Tensor diff --git a/ctrl_c_nn.py b/ctrl_c_nn.py index 4af04ea..f8042d4 100644 --- a/ctrl_c_nn.py +++ b/ctrl_c_nn.py @@ -1,9 +1,14 @@ +__author__ = "Manuel Vogel" +__version__ = "0.0.1" +__website__ = "https://github.com/manu12121999/ctrl_c_nn" +__original_source__ = "https://github.com/manu12121999/ctrl_c_nn/blob/main/ctrl_c_nn.py" +__email__ = "manu12121999@gmail.com" + import random import sys import math import operator from multiprocessing import Pool -import itertools sumprod = math.sumprod if sys.version_info >= (3, 12) else lambda p, q: sum([p_i*q_i for p_i, q_i in zip(p, q)])