Datasets:

willychan21
/

ParallelKernelBench_Problems

import torch
import torch.distributed as dist


@torch.no_grad()
def solution(A_local: torch.Tensor, B: torch.Tensor) -> torch.Tensor:
    world_size = dist.get_world_size()
    A_gathered = [torch.empty_like(A_local) for _ in range(world_size)]
    dist.all_gather(A_gathered, A_local)
    A_global = torch.cat(A_gathered, dim=1)
    return torch.matmul(A_global, B)

	import torch
	import torch.distributed as dist


	@torch.no_grad()
	def solution(A_local: torch.Tensor, B: torch.Tensor) -> torch.Tensor:
	world_size = dist.get_world_size()
	A_gathered = [torch.empty_like(A_local) for _ in range(world_size)]
	dist.all_gather(A_gathered, A_local)
	A_global = torch.cat(A_gathered, dim=1)
	return torch.matmul(A_global, B)