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提交 75657df1 authored 作者: lamblin's avatar lamblin
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Merge pull request #587 from nouiz/test_fix

Test fix
上级 6465523c b0e55935
隐藏空白字符变更
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正在显示 包含 103 行增加 和 74 行删除
theano/sandbox/cuda/opt.py
浏览文件 @ 75657df1
......@@ -87,7 +87,8 @@ class InputToGpuOptimizer(Optimizer):
# This happen frequently as we do 2 pass of the gpu optimizations
if (len(input.clients) == 1 and
input.clients[0][0].op == gpu_from_host):
(input.clients[0][0] == 'output' or
input.clients[0][0].op == gpu_from_host)):
return
try:
......
theano/tensor/tests/test_opt.py
浏览文件 @ 75657df1
......@@ -141,11 +141,12 @@ def test_add_canonizer_problem0():
class test_greedy_distribute(unittest.TestCase):
def test_main(self):
a, b, c, d, x, y, z = matrices('abcdxyz')
e = (a/z + b/x) * x * z
g = Env([a,b,c,d,x,y,z], [e])
e = (a / z + b / x) * x * z
g = Env([a, b, c, d, x, y, z], [e])
##print pprint(g.outputs[0])
mul_canonizer.optimize(g)
gof.TopoOptimizer(gof.LocalOptGroup(local_greedy_distributor), order = 'out_to_in').optimize(g)
gof.TopoOptimizer(gof.LocalOptGroup(local_greedy_distributor),
order='out_to_in').optimize(g)
##print pprint(g.outputs[0])
def test_kording_bug(self):
......@@ -155,18 +156,17 @@ class test_greedy_distribute(unittest.TestCase):
#r = theano.tensor.mul(theano.tensor.fill(x, 2.*a), x/a , (y+z) , a)
#r = theano.tensor.mul((x/a+y) , a, z)
r = tensor.mul(
s - 1
, eps + x/s
, eps + y/s
, s)
r = tensor.mul(s - 1,
eps + x / s,
eps + y / s,
s)
f = function([s, eps, x,y], r**2)
f = function([s, eps, x, y], r ** 2)
s_val = numpy.asarray(4, dtype=config.floatX)
eps_val = numpy.asarray(1.e-6, dtype=config.floatX)
x_val = numpy.asarray([1.5,2], dtype=config.floatX)
y_val = numpy.asarray([2.3,3.1], dtype=config.floatX)
x_val = numpy.asarray([1.5, 2], dtype=config.floatX)
y_val = numpy.asarray([2.3, 3.1], dtype=config.floatX)
r0 = f(s_val, eps_val, x_val, y_val)
r1 = f(s_val, eps_val, x_val, y_val)
......@@ -197,10 +197,13 @@ class test_canonize(unittest.TestCase):
print pprint(g.outputs[0])
def test_elemwise_multiple_inputs_optimisation(self):
"""
verify that the Canonizer merge sequential Elemwise({mul,add}) part 1
This part are that case that is done, but don't include case that are not implemented but are suposed to be.
"""verify that the Canonizer merge sequential Elemwise({mul,add}) part 1
This part are that case that is done, but don't include case
that are not implemented but are suposed to be.
Test with and without DimShuffle
"""
shp=(5,5)
......@@ -1584,28 +1587,33 @@ class test_local_subtensor_lift(unittest.TestCase):
class test_local_subtensor_merge(unittest.TestCase):
def setUp(self):
utt.seed_rng()
self.x_shapes = [(2,2), (5,3), (4,1), (1,2), (0,2), (2,0), (1,0), (0,0)]
self.x_shapes = [(2, 2), (5, 3), (4, 1), (1, 2),
(0, 2), (2, 0), (1, 0), (0, 0)]
self.rng = numpy.random.RandomState(seed=utt.fetch_seed())
def test_const(self):
# var[const::][-1] -> var[-1]
x = tensor.matrix('x')
for idx in range(-7,6):
for idx in range(-7, 6):
f = function([x], x[idx::][-1], mode=mode_opt)
g = function([x], x[idx::][-1], mode=mode_opt.excluding('local_subtensor_merge'))
g = function([x], x[idx::][-1], mode=mode_opt.excluding(
'local_subtensor_merge'))
topo=f.maker.env.toposort()
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
topo = f.maker.env.toposort()
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
assert isinstance(topo[-1].op,
theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
if idx < x_s[0] and x_s[0] > 0:
# The first subtensor is non-empty, so it makes sense
f(x_val) # let debugmode test something
f(x_val) # let debugmode test something
else:
# A non-empty subtensor of an empty one should be an IndexError
# A non-empty subtensor of an empty one should be
# an IndexError
self.assertRaises(IndexError, f, x_val)
self.assertRaises(IndexError, g, x_val)
......@@ -1613,15 +1621,18 @@ class test_local_subtensor_merge(unittest.TestCase):
# var[int::][-1] -> var[-1]
x = tensor.matrix('x')
y = tensor.iscalar('y')
f = function([x,y], x[y::][-1], mode=mode_opt)
g = function([x,y], x[y::][-1], mode=mode_opt.excluding('local_subtensor_merge'))
f = function([x, y], x[y::][-1], mode=mode_opt)
g = function([x, y], x[y::][-1],
mode=mode_opt.excluding('local_subtensor_merge'))
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
topo = f.maker.env.toposort()
#print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
assert isinstance(topo[-1].op,
theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
......@@ -1629,7 +1640,7 @@ class test_local_subtensor_merge(unittest.TestCase):
for idx in range(-9, 8):
if (idx < x_s[0]) and (x_s[0] > 0):
# The first subtensor is non-empty
f(x_val, idx) # let debugmode test something
f(x_val, idx) # let debugmode test something
else:
self.assertRaises(IndexError, f, x_val, idx)
self.assertRaises(IndexError, g, x_val, idx)
......@@ -1637,24 +1648,28 @@ class test_local_subtensor_merge(unittest.TestCase):
def test_const2(self):
# var[::-1][const] -> var[-1]
x = tensor.matrix('x')
for idx in range(-8,7):
for idx in range(-8, 7):
f = function([x], x[::-1][idx], mode=mode_opt)
g = function([x], x[::-1][idx], mode=mode_opt.excluding('local_subtensor_merge'))
g = function([x], x[::-1][idx],
mode=mode_opt.excluding('local_subtensor_merge'))
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
topo = f.maker.env.toposort()
#print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
assert isinstance(topo[-1].op,
theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
if (idx < x_s[0]) and (idx >= -x_s[0]):
# The first subtensor is non-empty, so it makes sense
f(x_val) # let debugmode test something
f(x_val) # let debugmode test something
else:
# A non-empty subtensor of an empty one should be an IndexError
# A non-empty subtensor of an empty one should be
# an IndexError
self.assertRaises(IndexError, f, x_val)
self.assertRaises(IndexError, g, x_val)
......@@ -1662,105 +1677,115 @@ class test_local_subtensor_merge(unittest.TestCase):
# var[::-1][int] -> var[-1]
x = tensor.matrix('x')
y = tensor.iscalar('y')
f = function([x,y], x[::-1][y], mode=mode_opt)
g = function([x,y], x[::-1][y], mode=mode_opt.excluding('local_subtensor_merge'))
f = function([x, y], x[::-1][y], mode=mode_opt)
g = function([x, y], x[::-1][y],
mode=mode_opt.excluding('local_subtensor_merge'))
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
topo = f.maker.env.toposort()
#print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
assert isinstance(topo[-1].op,
theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
for idx in range(-x_s[0], x_s[0]):
f(x_val, idx) # let debugmode test something
f(x_val, idx) # let debugmode test something
for idx in (range(x_s[0],9) + range(-9,-x_s[0])):
self.assertRaises(IndexError, f, x_val, idx)
self.assertRaises(IndexError, g, x_val, idx)
def test_const3(self):
# var[::-1][:const] -> var[-1]
x = tensor.matrix('x')
for idx in range(-9,8):
for idx in range(-9, 8):
f = function([x], x[::-1][:idx], mode=mode_opt)
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
#print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
f(x_val) # let debugmode test something
f(x_val) # let debugmode test something
def test_scalar3(self):
# var[::-1][:int] -> var[-1]
x = tensor.matrix('x')
y = tensor.iscalar('y')
f = function([x,y], x[::-1][:y], mode=mode_opt)
f = function([x, y], x[::-1][:y], mode=mode_opt)
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
topo = f.maker.env.toposort()
#print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
assert isinstance(topo[-1].op,
theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
for idx in range(-7,7):
f(x_val, idx) # let debugmode test something
for idx in range(-7, 7):
f(x_val, idx) # let debugmode test something
def test_const4(self):
# var[const1::][:const2]
x = tensor.matrix('x')
for idx1 in range(-7,7):
for idx2 in range(-7,7):
for idx1 in range(-7, 7):
for idx2 in range(-7, 7):
f = function([x], x[idx1:][:idx2], mode=mode_opt)
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
topo = f.maker.env.toposort()
#print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
assert isinstance(topo[-1].op,
theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
f(x_val) # let debugmode test something
f(x_val) # let debugmode test something
def test_scalar4(self):
# var[int1:][:int2]
x = tensor.matrix('x')
y = tensor.iscalar('y')
z = tensor.iscalar('y')
f = function([x,y,z], x[y:][:z], mode=mode_opt)
f = function([x, y, z], x[y:][:z], mode=mode_opt)
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
topo = f.maker.env.toposort()
#print [t for t in topo if isinstance(t.op, tensor.Subtensor)]
assert len([t for t in topo if isinstance(t.op, tensor.Subtensor)]) == 1
assert len([t for t in topo
if isinstance(t.op, tensor.Subtensor)]) == 1
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
assert isinstance(topo[-1].op,
theano.compile.function_module.DeepCopyOp)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
for idx1 in range(-11,11):
for idx2 in range(-11,11):
f(x_val, idx1, idx2) # let debugmode test something
for idx1 in range(-11, 11):
for idx2 in range(-11, 11):
f(x_val, idx1, idx2) # let debugmode test something
def test_const_general(self):
# Some cases of merge: shape, (start, stop, step) of first, (start, stop, step) of second subtensor
# Some cases of merge: shape, (start, stop, step) of first,
# (start, stop, step) of second subtensor
cases = [
((2,3), (None, None, None), (None, None, -1)),
((2, 3), (None, None, None), (None, None, -1)),
((12, 1), (None, None, -4), (None, None, 1)),
((5,3), (1, 4, 2), (None, None, -1)),
((5, 3), (1, 4, 2), (None, None, -1)),
]
x = tensor.matrix('x')
......@@ -1771,8 +1796,6 @@ class test_local_subtensor_merge(unittest.TestCase):
x_val = self.rng.uniform(size=shape).astype(config.floatX)
f(x_val)
def test_scalar5(self):
# General case with two real slices
# var[b1:e1:s1][b2:e2:s2]
......@@ -1824,15 +1847,20 @@ class test_local_subtensor_merge(unittest.TestCase):
def test_const5(self):
# Bug reported by Graham
data = self.rng.uniform(size=(8,8,8)).astype(theano.config.floatX)
data = self.rng.uniform(size=(8, 8, 8)).astype(theano.config.floatX)
x = theano.tensor.tensor3('x')
nops = 1
if theano.config.mode == "FAST_COMPILE":
nops = 2
# test 1)
y = x[3:6,2:6,1:7][1]
fun = theano.function([x], y)
val = fun(data)
assert numpy.all(val == data[3:6,2:6,1:7][1])
assert len([n for n in fun.maker.env.toposort()
if isinstance(n.op, theano.tensor.basic.Subtensor)]) == 1
if isinstance(n.op, tensor.basic.Subtensor)]) == nops
# test 2)
y = x[2,3][1]
......@@ -1840,7 +1868,7 @@ class test_local_subtensor_merge(unittest.TestCase):
val = fun(data)
assert numpy.all(val == data[2,3][1])
assert len([n for n in fun.maker.env.toposort()
if isinstance(n.op, theano.tensor.basic.Subtensor)]) == 1
if isinstance(n.op, tensor.basic.Subtensor)]) == nops
# test 3)
y = x[3:6,2,1:7][1]
......@@ -1848,7 +1876,7 @@ class test_local_subtensor_merge(unittest.TestCase):
val = fun(data)
assert numpy.all(val == data[3:6,2,1:7][1])
assert len([n for n in fun.maker.env.toposort()
if isinstance(n.op, theano.tensor.basic.Subtensor)]) == 1
if isinstance(n.op, tensor.basic.Subtensor)]) == nops
def test_scalar6(self):
......
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