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VoVAllen dd65ee211e [CI] Change tests for flexibility
* change ci image

* fix

* force bash

* fix

* fix python version

* fix

* fix

* fix

* update gpu

* cuda

* jenkins

* fix build sh

* fix

* Revert "fix"

This reverts commit 6b091914b3ef6b4300fa662ee375aa4b27944f5c.

* try fix

* fix

* Revert "fix"

This reverts commit e42c3035fa4974c6b197aaba0748f7b45113ddaa.

* try fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix tests

* try fix

* fix

* fix

* fix

* fix

* fix

* fix

* fix ctx problem

* fix many tests

* fix typo

* add backend

* move to pytorch folder

* fix?

* fix ci

* try skip

* try false

* try?

* try?

* Revert to 7d9a52f

* fix various

* fix lint

* Revert Jenkinsfile

* revert env

* revert env

* address comment

* remove file
2019-12-16 14:54:37 +08:00

301 行
8.5 KiB
Python

import numpy as np
import scipy.sparse as sp
import dgl
import dgl.function as fn
import backend as F
import unittest
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'] = F.randn((10, D))
g.edata['e'] = F.randn((17, D))
return g
@unittest.skipIf(dgl.backend.backend_name == "tensorflow", reason="TF doesn't support inplace update")
def test_inplace_recv():
u = F.tensor([0, 0, 0, 3, 4, 9])
v = F.tensor([1, 2, 3, 9, 9, 0])
def message_func(edges):
return {'m' : edges.src['f'] + edges.dst['f']}
def reduce_func(nodes):
return {'f' : F.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([0,1,2,3,9], reduce_func, apply_func)
result = g.get_n_repr()['f']
# inplace deg bucket run
v1 = F.clone(f)
g.ndata['f'] = v1
g.send((u, v), message_func)
g.recv([0,1,2,3,9], reduce_func, apply_func, inplace=True)
r1 = g.get_n_repr()['f']
# check result
assert F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# inplace e2v
v1 = F.clone(f)
g.ndata['f'] = v1
g.send((u, v), message_func)
g.recv([0,1,2,3,9], fn.sum(msg='m', out='f'), apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
@unittest.skipIf(dgl.backend.backend_name == "tensorflow", reason="TF doesn't support inplace update")
def test_inplace_snr():
u = F.tensor([0, 0, 0, 3, 4, 9])
v = F.tensor([1, 2, 3, 9, 9, 0])
def message_func(edges):
return {'m' : edges.src['f']}
def reduce_func(nodes):
return {'f' : F.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.clone(f)
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 F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# inplace v2v spmv
v1 = F.clone(f)
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 F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# inplace e2v spmv
v1 = F.clone(f)
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 F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
@unittest.skipIf(dgl.backend.backend_name == "tensorflow", reason="TF doesn't support inplace update")
def test_inplace_push():
nodes = F.tensor([0, 3, 4, 9])
def message_func(edges):
return {'m' : edges.src['f']}
def reduce_func(nodes):
return {'f' : F.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.clone(f)
g.ndata['f'] = v1
g.push(nodes, message_func, reduce_func, apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# inplace v2v spmv
v1 = F.clone(f)
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 F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# inplace e2v spmv
v1 = F.clone(f)
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 F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
@unittest.skipIf(dgl.backend.backend_name == "tensorflow", reason="TF doesn't support inplace update")
def test_inplace_pull():
nodes = F.tensor([1, 2, 3, 9])
def message_func(edges):
return {'m' : edges.src['f']}
def reduce_func(nodes):
return {'f' : F.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.clone(f)
g.ndata['f'] = v1
g.pull(nodes, message_func, reduce_func, apply_func, inplace=True)
r1 = g.ndata['f']
# check result
assert F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# inplace v2v spmv
v1 = F.clone(f)
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 F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# inplace e2v spmv
v1 = F.clone(f)
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 F.allclose(r1, result)
# check inplace
assert F.allclose(v1, r1)
# test send_and_recv with apply_func
_test(apply_func)
# test send_and_recv without apply_func
_test(None)
@unittest.skipIf(dgl.backend.backend_name == "tensorflow", reason="TF doesn't support inplace update")
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 F.allclose(nf, new_nf)
# test apply all nodes, should not be done in place
g.ndata['f'] = nf
g.apply_nodes(apply_node_func, inplace=True)
assert F.allclose(nf, g.ndata['f']) == 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 F.allclose(ef, new_ef)
# test apply all edges, should not be done in place
g.edata['e'] == ef
g.apply_edges(apply_edge_func, inplace=True)
assert F.allclose(ef, g.edata['e']) == False
if __name__ == '__main__':
test_inplace_recv()
test_inplace_snr()
test_inplace_push()
test_inplace_pull()
test_inplace_apply()