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Da Zheng 8918cce0b5 [MXNet] add unit tests for mxnet (#227)
[MXNet] add unit tests for mxnet
2018-12-03 11:04:11 -05:00

295 行
8.8 KiB
Python

import os
os.environ['DGLBACKEND'] = 'mxnet'
import mxnet as mx
import numpy as np
import scipy.sparse as sp
import dgl
import dgl.function as fn
D = 5
def generate_graph():
g = dgl.DGLGraph()
g.add_nodes(10)
# create a graph where 0 is the source and 9 is the sink
for i in range(1, 9):
g.add_edge(0, i)
g.add_edge(i, 9)
# add a back flow from 9 to 0
g.add_edge(9, 0)
g.ndata['f'] = mx.nd.random.normal(shape=(10, D))
g.edata['e'] = mx.nd.random.normal(shape=(17, D))
return g
def test_inplace_recv():
u = mx.nd.array([0, 0, 0, 3, 4, 9], dtype=np.int64)
v = mx.nd.array([1, 2, 3, 9, 9, 0], dtype=np.int64)
def message_func(edges):
return {'m' : edges.src['f'] + edges.dst['f']}
def reduce_func(nodes):
return {'f' : mx.nd.sum(nodes.mailbox['m'], 1)}
def apply_func(nodes):
return {'f' : 2 * nodes.data['f']}
def _test(apply_func):
g = generate_graph()
f = g.ndata['f']
# one out place run to get result
g.send((u, v), message_func)
g.recv(mx.nd.array([0,1,2,3,9], dtype=np.int64),
reduce_func, apply_func)
result = g.get_n_repr()['f']
# inplace deg bucket run
v1 = f.copy()
g.ndata['f'] = v1
g.send((u, v), message_func)
g.recv(mx.nd.array([0,1,2,3,9], dtype=np.int64),
reduce_func, apply_func, inplace=True)
r1 = g.get_n_repr()['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# inplace e2v
v1 = f.copy()
g.ndata['f'] = v1
g.send((u, v), message_func)
g.recv(mx.nd.array([0,1,2,3,9], dtype=np.int64),
fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
def test_inplace_snr():
u = mx.nd.array([0, 0, 0, 3, 4, 9], dtype=np.int64)
v = mx.nd.array([1, 2, 3, 9, 9, 0], dtype=np.int64)
def message_func(edges):
return {'m' : edges.src['f']}
def reduce_func(nodes):
return {'f' : mx.nd.sum(nodes.mailbox['m'], 1)}
def apply_func(nodes):
return {'f' : 2 * nodes.data['f']}
def _test(apply_func):
g = generate_graph()
f = g.ndata['f']
# an out place run to get result
g.send_and_recv((u, v), fn.copy_src(src='f', out='m'),
fn.sum(msg='m', out='f'), apply_func)
result = g.ndata['f']
# inplace deg bucket
v1 = f.copy()
g.ndata['f'] = v1
g.send_and_recv((u, v), message_func, reduce_func, apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# inplace v2v spmv
v1 = f.copy()
g.ndata['f'] = v1
g.send_and_recv((u, v), fn.copy_src(src='f', out='m'),
fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# inplace e2v spmv
v1 = f.copy()
g.ndata['f'] = v1
g.send_and_recv((u, v), message_func,
fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
def test_inplace_push():
nodes = mx.nd.array([0, 3, 4, 9], dtype=np.int64)
def message_func(edges):
return {'m' : edges.src['f']}
def reduce_func(nodes):
return {'f' : mx.nd.sum(nodes.mailbox['m'], 1)}
def apply_func(nodes):
return {'f' : 2 * nodes.data['f']}
def _test(apply_func):
g = generate_graph()
f = g.ndata['f']
# an out place run to get result
g.push(nodes,
fn.copy_src(src='f', out='m'), fn.sum(msg='m', out='f'), apply_func)
result = g.ndata['f']
# inplace deg bucket
v1 = f.copy()
g.ndata['f'] = v1
g.push(nodes, message_func, reduce_func, apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# inplace v2v spmv
v1 = f.copy()
g.ndata['f'] = v1
g.push(nodes, fn.copy_src(src='f', out='m'),
fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# inplace e2v spmv
v1 = f.copy()
g.ndata['f'] = v1
g.push(nodes,
message_func, fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
def test_inplace_pull():
nodes = mx.nd.array([1, 2, 3, 9], dtype=np.int64)
def message_func(edges):
return {'m' : edges.src['f']}
def reduce_func(nodes):
return {'f' : mx.nd.sum(nodes.mailbox['m'], 1)}
def apply_func(nodes):
return {'f' : 2 * nodes.data['f']}
def _test(apply_func):
g = generate_graph()
f = g.ndata['f']
# an out place run to get result
g.pull(nodes,
fn.copy_src(src='f', out='m'), fn.sum(msg='m', out='f'), apply_func)
result = g.ndata['f']
# inplace deg bucket
v1 = f.copy()
g.ndata['f'] = v1
g.pull(nodes, message_func, reduce_func, apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# inplace v2v spmv
v1 = f.copy()
g.ndata['f'] = v1
g.pull(nodes, fn.copy_src(src='f', out='m'),
fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# inplace e2v spmv
v1 = f.copy()
g.ndata['f'] = v1
g.pull(nodes,
message_func, fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert np.allclose(r1.asnumpy(), result.asnumpy())
# check inplace
assert np.allclose(v1.asnumpy(), r1.asnumpy())
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
def test_inplace_apply():
def apply_node_func(nodes):
return {'f': nodes.data['f'] * 2}
def apply_edge_func(edges):
return {'e': edges.data['e'] * 2}
g = generate_graph()
nodes = [1, 2, 3, 9]
nf = g.ndata['f']
# out place run
g.apply_nodes(apply_node_func, nodes)
new_nf = g.ndata['f']
# in place run
g.ndata['f'] = nf
g.apply_nodes(apply_node_func, nodes, inplace=True)
# check results correct and in place
assert np.allclose(nf.asnumpy(), new_nf.asnumpy())
# test apply all nodes, should not be done in place
g.ndata['f'] = nf
g.apply_nodes(apply_node_func, inplace=True)
assert np.allclose(nf.asnumpy(), g.ndata['f'].asnumpy()) == False
edges = [3, 5, 7, 10]
ef = g.edata['e']
# out place run
g.apply_edges(apply_edge_func, edges)
new_ef = g.edata['e']
# in place run
g.edata['e'] = ef
g.apply_edges(apply_edge_func, edges, inplace=True)
g.edata['e'] = ef
assert np.allclose(ef.asnumpy(), new_ef.asnumpy())
# test apply all edges, should not be done in place
g.edata['e'] == ef
g.apply_edges(apply_edge_func, inplace=True)
assert np.allclose(ef.asnumpy(), g.edata['e'].asnumpy()) == False
if __name__ == '__main__':
test_inplace_recv()
test_inplace_snr()
test_inplace_push()
test_inplace_pull()
test_inplace_apply()