/* Copyright 2019 The Microsoft DeepSpeed Team */
#include <torch/extension.h>

// CUDA forward declaration
void fused_lamb_cuda(at::Tensor & p, at::Tensor & p_copy, at::Tensor & m, at::Tensor & v, at::Tensor & g,
                        float lr, float beta1, float beta2, float max_coeff, float min_coeff, float eps, float grad_scale, int step, int mode, int bias_correction, float decay,
                        at::Tensor & w_l2_i, at::Tensor & u_l2_i, at::Tensor & lamb_coeff_val );

#define CHECK_CUDA(x) AT_ASSERTM(x.type().is_cuda(), #x " must be a CUDA tensor")
#define CHECK_CONTIGUOUS(x) AT_ASSERTM(x.is_contiguous(), #x " must be contiguous")
#define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)

// C++ interface
at::Tensor lamb(at::Tensor & p, at::Tensor & p_copy, at::Tensor & m, at::Tensor & v, at::Tensor & g, float lr, float beta1, float beta2, float max_coeff, float min_coeff, float eps, float grad_scale, int step, int mode, int bias_correction, float decay) {
        CHECK_INPUT(p);
        if (p_copy.numel() > 0) CHECK_INPUT(p_copy);
        CHECK_INPUT(m);
        CHECK_INPUT(v);
        CHECK_INPUT(g);
        int64_t num_elem = p.numel();
        AT_ASSERTM(m.numel() == num_elem, "number of elements in m and p tensors should be equal");
        AT_ASSERTM(v.numel() == num_elem, "number of elements in v and p tensors should be equal");
        AT_ASSERTM(g.numel() == num_elem, "number of elements in g and p tensors should be equal");
        AT_ASSERTM(p_copy.numel() == num_elem || p_copy.numel() == 0, "number of elements in p_copy and p tensors should be equal, or p_copy should be empty");

        //intermediate for weight L2 reduction
        //make sure that the threads per block is at least 512 during the kernel launch otherwise the behavious is unexpected
        at::Tensor w_l2_i = at::empty({512}, p.options().dtype(p.type().scalarType()==at::ScalarType::Half ? at::ScalarType::Float : p.type().scalarType()));

        //intermediate for update L2 reduction
        //make sure that the threads per block is at least 512 during the kernel launch otherwise the behavious is unexpected
        at::Tensor u_l2_i = at::empty({512}, p.options().dtype(p.type().scalarType()==at::ScalarType::Half ? at::ScalarType::Float : p.type().scalarType()));

        at::Tensor lamb_coeff_val = at::empty({1}, p.options().dtype(p.type().scalarType()==at::ScalarType::Half ? at::ScalarType::Float : p.type().scalarType()));

        fused_lamb_cuda(p, p_copy, m, v, g, lr, beta1, beta2, max_coeff, min_coeff, eps, grad_scale, step, mode, bias_correction, decay, w_l2_i, u_l2_i, lamb_coeff_val);

        return lamb_coeff_val;
}

PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
        m.def("lamb", &lamb, "Adam optimized CUDA implementation with LAMB.");
}