Angel

@angelcrypto

83 Following

19 Followers

Angel pfp

Been a while since I've been on here. A lot going on, but now I'm ready to start a new series, and I will finish it this time! The new series will be about Cuda C/C++ programming! I've always wanted to learn this, so why not share my learning journey in here. Will start soon!

0 reply

0 recast

0 reaction

Angel pfp

### Automatic Differentiation in C++ ### Day 9: Adding more arithmetic operations I've been busy last week but I'm back now. I've added some basic arithmetic operations to allow interactions between tensors and primitive C++ numbers (float, double, int...)., e.g. doing somthing like `tensor + 3`

2 replies

0 recast

0 reaction

Angel pfp

### Automatic differentiation in C++ ### Day 8: Forward mode implementation part 2 Done with the inital implementation of FM. It's a basic one with no real optimizations. I'm working on making it faster. You can find it on github. I'll share an explanation later today!

4 replies

0 recast

1 reaction

Angel pfp

### Automatic differentiation in C++ ### Day 8: Forward mode implementation part 1 I've figured out how to implement the forward mode for the simple cases: Case 1: input x is a vector and output y is a real number. The second case is just a generalization of the output (y is also a vector).

7 replies

0 recast

0 reaction

Angel pfp

### Automatic DIfferentiation in C++ ### Day 7: Testing basic operations, refreshing some math and learning vim motions Tested my basic tensor operations (works 😁 ). Also, tried to apply simple chain rule on some functions just to make sure I remember how to do it😅

5 replies

0 recast

0 reaction

Angel pfp

### Automatic Differentiation in C++ ### Here's the github repo (empty now), I'll add my current code there tonight! https://github.com/angel-cr/AutoGrad

0 reply

0 recast

0 reaction

Angel pfp

Just had a day off from doing coding today, so no new things done for the project. I'll be back tomorrow!

5 replies

0 recast

0 reaction

Angel pfp

### Automatic Differentiation in C++ ### DAY 5: Simple Tensor class implementation: Part 1 Started the Tensor implementation. As mentioned before, this will be 1d vector base implementation of a Tensor for now for training purposes. Finished the basic operations and some math ones (exp, tang, sin, cos).

3 replies

0 recast

0 reaction

Angel pfp

### Automatic differentiation in C++ ### Day 4: Today I started working on my Tensor class (rip 🤕) .I thought a little bit about what do I want it to have at first and I figured that since I'm still (re)starting with C++, I'll make it simple: it will support 1d vectors for now and some basic operations.

1 reply

0 recast

0 reaction

Angel pfp

### Automatic differentiation in C++ ### Day 3: Today I focused on reading more about forward mode and refreshing some theory about chain rule and some gradients refresher (been a while since I've done those calculations by hand). I think I'll start with implementing forward mode first at this time.

1 reply

0 recast

0 reaction

Angel pfp

### Automatic differentiation in C++ ### Day 2: Reading about the theory of Automatic differentiation Today I didn't do much unfortunatly as I was busy with other stuff. I read a bit about the two types of automatic differentiation: forward and backward. I got the gist of it and understood when to use each one.

3 replies

0 recast

0 reaction

Angel pfp

### Automatic differentiation in C++ ### DAY 1: Learning some modern C++ I've been 100% programming in Python these past years doing some data science and ML/DL stuff and the last time I used C++ was when I was doing competitive programming in college, and that was C++03 😢

2 replies

0 recast

1 reaction

Angel pfp

So I've just started working on implementing automatic differentiation in C++. While doing this, I'll be trying to learn modern C++ and cuda (for gpu calculations of all operations). I'll be sharing my progress everyday in here with all the code and references/tutorials/links I'll be using.

8 replies

0 recast

1 reaction

Angel pfp

This degen locking system is interesting. Let's see how this goes!

1 reply

0 recast

0 reaction

Angel pfp

First cast in here! Glad to be un this community!

0 reply

0 recast

1 reaction