#include void multi_tensor_scale_cuda( int chunk_size, at::Tensor noop_flag, std::vector> tensor_lists, float scale); void multi_tensor_axpby_cuda( int chunk_size, at::Tensor noop_flag, std::vector> tensor_lists, float a, float b, int arg_to_check); std::tuple multi_tensor_l2norm_cuda( int chunk_size, at::Tensor noop_flag, std::vector> tensor_lists, at::optional per_tensor_python); void multi_tensor_lamb_stage1_cuda( int chunk_size, at::Tensor noop_flag, std::vector> tensor_lists, at::Tensor per_tensor_decay, const int step, const float beta1, const float beta2, const float epsilon, const float global_grad_norm, const float max_global_grad_norm); void multi_tensor_lamb_stage2_cuda( int chunk_size, at::Tensor noop_flag, std::vector> tensor_lists, at::Tensor per_tensor_param_norm, at::Tensor per_tensor_update_norm, const float step_size); PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { m.def("multi_tensor_scale", &multi_tensor_scale_cuda, "Fused overflow check + scale for a list of contiguous tensors"); m.def("multi_tensor_axpby", &multi_tensor_axpby_cuda, "out = a*x + b*y for a list of contiguous tensors"); m.def("multi_tensor_l2norm", &multi_tensor_l2norm_cuda, "Computes L2 norm for a list of contiguous tensors"); m.def("multi_tensor_lamb_stage1_cuda", &multi_tensor_lamb_stage1_cuda, "Computes update part of LAMB optimizer"); m.def("multi_tensor_lamb_stage2_cuda", &multi_tensor_lamb_stage2_cuda, "Completes application of gradient to parameters for LAMB optimizer"); }