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nv-dlasalle 1425150459 Fix test naming (#4023)
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
2022-05-23 17:21:06 +08:00

248 行
8.4 KiB
Python

import dgl
import dgl.function as fn
from collections import Counter
import numpy as np
import scipy.sparse as ssp
import itertools
from itertools import product
import backend as F
import networkx as nx
import unittest, pytest
from dgl import DGLError
import test_utils
from test_utils import parametrize_idtype, get_cases
from scipy.sparse import rand
rfuncs = {'sum': fn.sum, 'max': fn.max, 'min': fn.min, 'mean': fn.mean}
fill_value = {'sum': 0, 'max': float("-inf")}
feat_size = 2
@unittest.skipIf(dgl.backend.backend_name != 'pytorch', reason='Only support PyTorch for now')
def create_test_heterograph(idtype):
# test heterograph from the docstring, plus a user -- wishes -- game relation
# 3 users, 2 games, 2 developers
# metagraph:
# ('user', 'follows', 'user'),
# ('user', 'plays', 'game'),
# ('user', 'wishes', 'game'),
# ('developer', 'develops', 'game')])
g = dgl.heterograph({
('user', 'follows', 'user'): ([0, 1, 2, 1], [0, 0, 1, 1]),
('user', 'plays', 'game'): ([0, 1, 2, 1], [0, 0, 1, 1]),
('user', 'wishes', 'game'): ([0, 1, 1], [0, 0, 1]),
('developer', 'develops', 'game'): ([0, 1, 0], [0, 1, 1]),
}, idtype=idtype, device=F.ctx())
assert g.idtype == idtype
assert g.device == F.ctx()
return g
@parametrize_idtype
def test_unary_copy_u(idtype):
def _test(mfunc):
g = create_test_heterograph(idtype)
x1 = F.randn((g.num_nodes('user'), feat_size))
x2 = F.randn((g.num_nodes('developer'), feat_size))
F.attach_grad(x1)
F.attach_grad(x2)
g.nodes['user'].data['h'] = x1
g.nodes['developer'].data['h'] = x2
#################################################################
# apply_edges() is called on each relation type separately
#################################################################
with F.record_grad():
[g.apply_edges(fn.copy_u('h', 'm'), etype = rel)
for rel in g.canonical_etypes]
r1 = g['plays'].edata['m']
F.backward(r1, F.ones(r1.shape))
n_grad1 = F.grad(g.ndata['h']['user'])
# TODO (Israt): clear not working
g.edata['m'].clear()
#################################################################
# apply_edges() is called on all relation types
#################################################################
g.apply_edges(fn.copy_u('h', 'm'))
r2 = g['plays'].edata['m']
F.backward(r2, F.ones(r2.shape))
n_grad2 = F.grad(g.nodes['user'].data['h'])
# correctness check
def _print_error(a, b):
for i, (x, y) in enumerate(zip(F.asnumpy(a).flatten(), F.asnumpy(b).flatten())):
if not np.allclose(x, y):
print('@{} {} v.s. {}'.format(i, x, y))
if not F.allclose(r1, r2):
_print_error(r1, r2)
assert F.allclose(r1, r2)
if not F.allclose(n_grad1, n_grad2):
print('node grad')
_print_error(n_grad1, n_grad2)
assert(F.allclose(n_grad1, n_grad2))
_test(fn.copy_u)
@parametrize_idtype
def test_unary_copy_e(idtype):
def _test(mfunc):
g = create_test_heterograph(idtype)
feat_size = 2
x1 = F.randn((4,feat_size))
x2 = F.randn((4,feat_size))
x3 = F.randn((3,feat_size))
x4 = F.randn((3,feat_size))
F.attach_grad(x1)
F.attach_grad(x2)
F.attach_grad(x3)
F.attach_grad(x4)
g['plays'].edata['eid'] = x1
g['follows'].edata['eid'] = x2
g['develops'].edata['eid'] = x3
g['wishes'].edata['eid'] = x4
#################################################################
# apply_edges() is called on each relation type separately
#################################################################
with F.record_grad():
[g.apply_edges(fn.copy_e('eid', 'm'), etype = rel)
for rel in g.canonical_etypes]
r1 = g['develops'].edata['m']
F.backward(r1, F.ones(r1.shape))
e_grad1 = F.grad(g['develops'].edata['eid'])
#################################################################
# apply_edges() is called on all relation types
#################################################################
g.apply_edges(fn.copy_e('eid', 'm'))
r2 = g['develops'].edata['m']
F.backward(r2, F.ones(r2.shape))
e_grad2 = F.grad(g['develops'].edata['eid'])
# # correctness check
def _print_error(a, b):
for i, (x, y) in enumerate(zip(F.asnumpy(a).flatten(), F.asnumpy(b).flatten())):
if not np.allclose(x, y):
print('@{} {} v.s. {}'.format(i, x, y))
if not F.allclose(r1, r2):
_print_error(r1, r2)
assert F.allclose(r1, r2)
if not F.allclose(e_grad1, e_grad2):
print('edge grad')
_print_error(e_grad1, e_grad2)
assert(F.allclose(e_grad1, e_grad2))
_test(fn.copy_e)
@parametrize_idtype
def test_binary_op(idtype):
def _test(lhs, rhs, binary_op):
g = create_test_heterograph(idtype)
n1 = F.randn((g.num_nodes('user'), feat_size))
n2 = F.randn((g.num_nodes('developer'), feat_size))
n3 = F.randn((g.num_nodes('game'), feat_size))
x1 = F.randn((g.num_edges('plays'),feat_size))
x2 = F.randn((g.num_edges('follows'),feat_size))
x3 = F.randn((g.num_edges('develops'),feat_size))
x4 = F.randn((g.num_edges('wishes'),feat_size))
builtin_msg_name = "{}_{}_{}".format(lhs, binary_op, rhs)
builtin_msg = getattr(fn, builtin_msg_name)
#################################################################
# apply_edges() is called on each relation type separately
#################################################################
F.attach_grad(n1)
F.attach_grad(n2)
F.attach_grad(n3)
g.nodes['user'].data['h'] = n1
g.nodes['developer'].data['h'] = n2
g.nodes['game'].data['h'] = n3
F.attach_grad(x1)
F.attach_grad(x2)
F.attach_grad(x3)
F.attach_grad(x4)
g['plays'].edata['h'] = x1
g['follows'].edata['h'] = x2
g['develops'].edata['h'] = x3
g['wishes'].edata['h'] = x4
with F.record_grad():
[g.apply_edges(builtin_msg('h', 'h', 'm'), etype = rel)
for rel in g.canonical_etypes]
r1 = g['plays'].edata['m']
loss = F.sum(r1.view(-1), 0)
F.backward(loss)
n_grad1 = F.grad(g.nodes['game'].data['h'])
#################################################################
# apply_edges() is called on all relation types
#################################################################
F.attach_grad(n1)
F.attach_grad(n2)
F.attach_grad(n3)
g.nodes['user'].data['h'] = n1
g.nodes['developer'].data['h'] = n2
g.nodes['game'].data['h'] = n3
F.attach_grad(x1)
F.attach_grad(x2)
F.attach_grad(x3)
F.attach_grad(x4)
g['plays'].edata['h'] = x1
g['follows'].edata['h'] = x2
g['develops'].edata['h'] = x3
g['wishes'].edata['h'] = x4
with F.record_grad():
g.apply_edges(builtin_msg('h', 'h', 'm'))
r2 = g['plays'].edata['m']
loss = F.sum(r2.view(-1), 0)
F.backward(loss)
n_grad2 = F.grad(g.nodes['game'].data['h'])
# correctness check
def _print_error(a, b):
for i, (x, y) in enumerate(zip(F.asnumpy(a).flatten(), F.asnumpy(b).flatten())):
if not np.allclose(x, y):
print('@{} {} v.s. {}'.format(i, x, y))
if not F.allclose(r1, r2):
_print_error(r1, r2)
assert F.allclose(r1, r2)
if n_grad1 is not None or n_grad2 is not None:
if not F.allclose(n_grad1, n_grad2):
print('node grad')
_print_error(n_grad1, n_grad2)
assert(F.allclose(n_grad1, n_grad2))
target = ["u", "v", "e"]
for lhs, rhs in product(target, target):
if lhs == rhs:
continue
for binary_op in ["add", "sub", "mul", "div", "dot"]:
print(lhs, rhs, binary_op)
_test(lhs, rhs, binary_op)
if __name__ == '__main__':
test_unary_copy_u()
test_unary_copy_e()