def _replicate_edgelist(self): client = mg_utils.get_client() comms = Comms.get_comms() # FIXME: There might be a better way to control it if client is None: return work_futures = replication.replicate_cudf_dataframe( self.edgelist.edgelist_df, client=client, comms=comms) self.batch_edgelists = work_futures
def test_replicate_cudf_dataframe_no_weights(input_data_path, mg_device_count): skip_if_not_enough_devices(mg_device_count) df = cudf.read_csv(input_data_path, delimiter=' ', names=['src', 'dst'], dtype=['int32', 'int32']) with MGContext(mg_device_count): worker_to_futures = replication.replicate_cudf_dataframe(df) for worker in worker_to_futures: replicated_df = worker_to_futures[worker].result() assert df.equals(replicated_df), "There is a mismatch in one " \ "of the replications"
def test_replicate_cudf_dataframe_no_weights(input_data_path, dask_client): gc.collect() df = cudf.read_csv( input_data_path, delimiter=" ", names=["src", "dst"], dtype=["int32", "int32"], ) worker_to_futures = replication.replicate_cudf_dataframe(df) for worker in worker_to_futures: replicated_df = worker_to_futures[worker].result() assert_frame_equal(df, replicated_df)
def test_replicate_cudf_dataframe_no_weights(input_data_path, mg_device_count): gc.collect() skip_if_not_enough_devices(mg_device_count) df = cudf.read_csv( input_data_path, delimiter=" ", names=["src", "dst"], dtype=["int32", "int32"], ) with MGContext(number_of_devices=mg_device_count, p2p=True): worker_to_futures = replication.replicate_cudf_dataframe(df) for worker in worker_to_futures: replicated_df = worker_to_futures[worker].result() assert df.equals(replicated_df), ("There is a mismatch in one " "of the replications")