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update v11: Synchronize multithreaded communication modifications

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Sample/demo.py
import torch
# import sys
# from os.path import abspath, dirname
# sys.path.insert(0, abspath(dirname(__file__)))
# print(sys.path)
from neighbor_sampler import NeighborSampler
# edge_index = torch.tensor([[0, 1, 1, 2, 2, 2, 3], [1, 0, 2, 1, 3, 0, 2]])
......
Sample/neighbor_sampler.py
......@@ -5,8 +5,7 @@ import math
import torch
import torch.multiprocessing as mp
from typing import Optional, Tuple
#import ctypes
#sample_lib = ctypes.cdll.LoadLibrary('Sample/sample_cores.cpython-37m-x86_64-linux-gnu.so')
from base import BaseSampler, NegativeSampling
from sample_cores import get_neighbors, neighbor_sample_from_nodes, heads_unique
......@@ -17,17 +16,20 @@ class NeighborSampler(BaseSampler):
num_layers: int,
fanout: list,
workers = 1,
edge_index : torch.Tensor = None,
edge_index : Optional[torch.Tensor] = None,
deg = None,
neighbors = None
) -> None:
r"""__init__
Args:
edge_index: all edges in the graph
num_nodes: the num of all nodes in the graph
num_layers: the num of layers to be sampled
fanout: the list of max neighbors' number chosen for each layer
workers: the number of threads, default value is 1
edge_index: all edges in the graph
neighbors: all nodes' neighbors
deg: the degree of all nodes
should provide edge_index or (neighbors, deg)
"""
super().__init__()
self.num_layers = num_layers
......@@ -55,10 +57,10 @@ class NeighborSampler(BaseSampler):
def _set_neighbors_and_deg(self,neighbors,deg):
self.neighbors = neighbors
self.deg = deg
def sample_from_nodes(
self,
nodes: torch.Tensor
nodes: torch.Tensor
) -> Tuple[torch.Tensor, list]:
r"""Performs mutilayer sampling from the nodes specified in: nodes
The specific number of layers is determined by parameter: num_layers
......@@ -123,6 +125,7 @@ class NeighborSampler(BaseSampler):
if neg_sampling is None or neg_sampling.is_binary():
edge_label_index = inverse_seed.view(2, -1)
# edge_label_index不知道是啥 edge_label是seed links的标签
metadata = {'edge_label_index':edge_label_index, 'edge_label':edge_label}
elif neg_sampling.is_triplet():
......@@ -130,8 +133,11 @@ class NeighborSampler(BaseSampler):
dst_pos_index = inverse_seed[num_pos:2 * num_pos]
dst_neg_index = inverse_seed[2 * num_pos:]
dst_neg_index = dst_neg_index.view(num_pos, -1).squeeze(-1)
# src_index是seed里src点的索引
# dst_pos_index是seed里dst_pos点的索引
# dst_neg_index是seed里dst_neg点的索引
metadata = {'src_index':src_index, 'dst_pos_index':dst_pos_index, 'dst_neg_index':dst_neg_index}
# sampled_nodes最前方是原始序列的采样起点也就是去重后的seed
return sampled_nodes, sampled_edge_index_list, metadata
def _sample_one_layer_from_nodes(
......
Sample/sample_cores.cpp
......@@ -172,6 +172,6 @@ PYBIND11_MODULE(sample_cores, m)
py::class_<TemporalNeighborBlock>(m, "TemporalNeighborBlock")
.def(py::init<std::vector<vector<NodeIDType>*>&,
std::vector<int> &>())
.def_readonly("neighbors", &TemporalNeighborBlock::neighbors)
.def_readonly("deg", &TemporalNeighborBlock::deg);
.def_readonly("neighbors", &TemporalNeighborBlock::neighbors, py::return_value_policy::copy)
.def_readonly("deg", &TemporalNeighborBlock::deg, py::return_value_policy::copy);
}
pybind11 @ 0e01c243
Subproject commit 0e01c243c7ffae3a2e52f998bacfe82f56aa96d9
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