Intended to be a Torch-like autograd engine, inspired by micrograd
add-apt-repository ppa:snaipewastaken/ppa
apt-get update
apt-get install libcriterion-dev
apt-get install libcsptr-dev
apt-get install meson ninja-build#include "tensor.h"
#include "ops.h"
#include "log.h"
int main()
{
log_set_level(LOG_INFO);
tensor_t *a = tensor((float[]){2., 4., 6.}, (int[]){3}, 1, true);
tensor_t *b = tensor((float[]){1., 2., 0.}, (int[]){3}, 1, true);
// c = a + b
tensor_t *c = tensor_add(a, b);
// c = c - 1
c = tensor_sub_tf(c, 1.);
// d = c ** 3
tensor_t *d = tensor_pow_tf(c, 3.);
// e = relu(d)
tensor_t *e = tensor_relu(d);
// f = sum(e)
tensor_t *f = tensor_sum(e);
tensor_backward(f); // compute gradients
tensor_print(a, PRINT_ALL); // print tensors a.data and a.grad = d(f)/d(a)
tensor_print(b, PRINT_ALL); // print tensors b.data and b.grad = d(f)/d(b)
// recursively free all tensors in the graph
tensor_free(f, true);
return 0;
}mkdir build && cd build
meson setup ..
ninja && meson test
./mainmake && make test
./main- tensor with > 1 parent segfault when using recursive tensor_free -> use smalloc for tensor as well
- polymorphic iterator range_iterator >< array_iterator
- Reduce operator for specific axes
- Matmul operator as a combination of sum, add and reshape ideally
- Pooling operators
- Conv operator as a specific case of pool operator