tns

tns is a small and lightweight C library designed to implement tensors for neural networks. It only supports 1 and 2 dimensional tensors, but includes support for quantized representation (float32 and int8).

Features

• Support for 1D and 2D tensors.
• Quantized representation (float32, int8) support.
• Clean polymorphic API

Installation

Clone the repository to your local machine.

git clone https://github.com/yourusername/tns.git

Navigate to the project directory and compile the source code.

cd tns
make

you will get two files: tns.c and tns.h to include in your project.

Include the tns.h header file in your C program.

#include "tns.h"

Compile tns.c

gcc -O3 -fopenmp -c tns.c

If your architecture does not support OpenMP, just remove the flag.

Link tns.o with your other objects to create the executable.

To run all the tests, go in the test directory and type:

make runtest

Only tests that failed are shown, if no test fails, nothing is printed.

Creating a Tensor

Currently only floating point fp32 and quantized int8 tensors are supported.

// Create a 2D float32 tensor
tns_fp32_t t1 = NULL;
tns_new(t1, 2, 5); // 2 rows, 5 columns

// Create a 1D column tensor
tns_fp32_t t2 = NULL;
tns_new(t2, 16); // 16 rows, 1 column

// Create a 1D column quantized tensor
tns_in8_t t3 = NULL;
tns_new(t3, 16, 1, 4); // 16 rows, 1 column, group size = 4

To free a tensor, use tns_free().

tns_free(t1); // will set t1 to NULL
tns_free(t2); // will set t1 to NULL
tns_free(t3); // will set t1 to NULL

To get the tension dimensions:

tns_nrows(t1); // returns the number of rows
tns_ncols(t1); // returns the number of columns

Multiplication

The tns_matmul(r,A,x) implments the operation r = A * x where r and x are vectors and A is a matrix of compatible dimensions.

The result vector r must be of type fp32 while A and x can be quantized.

Setting and Getting Tensor Values

You can initialize a tensor by copying values into it:

tns_fp32_t ft  = NULL;
tns_new(ft,4);

float v = {0.1, 1.2, 3.4, 5.6};
tns_cpy(ft,v);

You can also use tns_cpy() to copy values between tensors:

tns_int8_t qt  = NULL; // A quantized tensor
tns_new(qt,4,1,2); // group size of 2

tns_cpy(qt,ft); // copy and quantize 

To set or get a value (that will always be a float) you can use tns_set() and tns_get().

float x;
x = tns_get(qt,2); // will de-quantize and return the third element in the vector `qt`

tns_set(ft,x,2); // put it in the `ft` tensor

Contributing

Please note that this is just an initial version, many things need to be properly implemented and tested.

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

License

MIT