def test_nccl_sparse_pull_single_remainder(): nccl_id = nccl.UniqueId() comm = nccl.Communicator(1, 0, nccl_id) req_index = F.randint([10000], F.int64, F.ctx(), 0, 100000) value = F.uniform([100000, 100], F.float32, F.ctx(), -1.0, 1.0) part = NDArrayPartition(100000, 1, 'remainder') rv = comm.sparse_all_to_all_pull(req_index, value, part) exp_rv = F.gather_row(value, req_index) assert F.array_equal(rv, exp_rv)
def test_nccl_sparse_push_single_remainder(): nccl_id = nccl.UniqueId() comm = nccl.Communicator(1, 0, nccl_id) index = F.randint([10000], F.int32, F.ctx(), 0, 10000) value = F.uniform([10000, 100], F.float32, F.ctx(), -1.0, 1.0) part = NDArrayPartition(10000, 1, 'remainder') ri, rv = comm.sparse_all_to_all_push(index, value, part) assert F.array_equal(ri, index) assert F.array_equal(rv, value)
def test_nccl_sparse_pull_single_range(): nccl_id = nccl.UniqueId() comm = nccl.Communicator(1, 0, nccl_id) req_index = F.randint([10000], F.int64, F.ctx(), 0, 100000) value = F.uniform([100000, 100], F.float32, F.ctx(), -1.0, 1.0) part_ranges = F.copy_to(F.tensor([0, value.shape[0]], dtype=F.int64), F.ctx()) part = NDArrayPartition(100000, 1, 'range', part_ranges=part_ranges) rv = comm.sparse_all_to_all_pull(req_index, value, part) exp_rv = F.gather_row(value, req_index) assert F.array_equal(rv, exp_rv)