Hi @anshuman23!

Let's ping @versilov since he has recently worked on matrex (see discussion.

If @versilov is already working on a matrex library based on NIFs, maybe we can unify the efforts?

@versilov how would the two NIF libraries interoperate? Is matrex keeping the matrix as a binary? If so, could the NIF side of tensforlow simply rely on this binary format?

It seems we are all working together improving Elixir for data science, so we should probably be in touch. :)

Hello @josevalim, @anshuman23!

Yes, matrex definitely uses the same binary format. The difference is in size. Matrex uses 32bit values (ints and floats), while in tensorflex I see 64 bit values. (BTW, will unsigned, used for the dimensions of the matrix, be of the same size on all platforms? May be it would be better to be more specific there with uint64_t?)

I think 32 bit values will be sufficient for the most tasks. Anyway, I consider to add support for different value types and different shapes to the Matrex.

@anshuman23, please, give matrex a try in tensorflex and feel free to send feature requests to me — I'll try to implement them ASAP, cuz that's what matrex needs now to polish the API.

PS: I'am not familiar with TF, but is it OK to feed array of doubles into this function with TF_FLOAT flag?

TF_NewTensor(TF_FLOAT, dims, ndims, mx1.p->data, (size_alloc) * sizeof(double), tensor_deallocator, 0);

Hi @josevalim and @versilov!

Sorry for the delayed reply, I did not have internet connectivity as I was on vacation and have just returned.

Yes, matrex definitely uses the same binary format. The difference is in size. Matrex uses 32bit values (ints and floats), while in tensorflex I see 64 bit values. (BTW, will unsigned, used for the dimensions of the matrix, be of the same size on all platforms? May be it would be better to be more specific there with uint64_t?)

I completely agree, I will try and switch to uint64_t in the next PR.

@anshuman23, please, give matrex a try in tensorflex and feel free to send feature requests to me — I'll try to implement them ASAP, cuz that's what matrex needs now to polish the API.

I will play around with Matrex and try to integrate it into Tensorflex first thing. :)

PS: I'am not familiar with TF, but is it OK to feed array of doubles into this function with TF_FLOAT flag?

I did not understand your question. Right now mx1.p->data is actually an array of doubles itself. This is the internal Tensorflow function as seen in their C API code:

TF_CAPI_EXPORT extern TF_Tensor* TF_NewTensor(
    TF_DataType, const int64_t* dims, int num_dims, void* data, size_t len,
    void (*deallocator)(void* data, size_t len, void* arg),
    void* deallocator_arg);

@anshuman23, hi!

Right now mx1.p->data is actually an array of doubles itself.

Yes, and you give TF_FLOAT as the first argument to TF_NewTensor. May be you should use TF_DOUBLE there? Or switch to the array of floats:)

Yes that will be done!