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提交 24102962 authored 作者: Pascal Lamblin's avatar Pascal Lamblin
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Test new cases for local_subtensor_merge, and fix one of them.

上级 3944c371
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正在显示 包含 100 行增加 和 61 行删除
theano/tensor/opt.py
浏览文件 @ 24102962
......@@ -1152,11 +1152,13 @@ def local_subtensor_merge(node):
1) var[int:][-1] -> var[-1] # a little different for when the first subtensor is empty.
2) var[::-1][int] -> var[-int-1]
3) var[::-1][:int] -> var[:-int-1:-1]
4) var[int1::][:int2] -> var[int1:switch(idx1>=0,
idx1,
maximum(u.owner.inputs[0].shape[0]+idx1, 0)
) + idx2]
4) var[int1::][:int2] ->
var[int1:int2 + switch(int2<0,
0,
switch(int1>=0,
int1,
maximum(u.owner.inputs[0].shape[0]+int1,
0))]
"""
if (isinstance(node.op, T.Subtensor) and
len(node.op.idx_list)==1):
......@@ -1270,11 +1272,17 @@ def local_subtensor_merge(node):
elif isinstance(idx2, int):
idx2 = T.as_tensor_variable(idx2)
# The maximum is needed to don't have shape[0] - idx1 < 0
idx2_neg = T.maximum(u.owner.inputs[0].shape[0]+idx1, 0)
new_idx2 = T.switch(idx1>=0, idx1, idx2_neg)+idx2
# Get positive version of idx1
# TODO: use Razvan's code for that
# The maximum is needed so that shape[0] + idx1 >= 0
neg_idx1 = T.maximum(u.owner.inputs[0].shape[0]+idx1, 0)
new_idx1 = T.switch((idx1 >= 0), idx1, neg_idx1)
# If idx2<0, we are indexing from the end, so idx2 is OK
# If we are indexing from the beginning, we need to add pos_idx1
new_idx2 = idx2 + T.switch((idx2 < 0), 0, new_idx1)
return [u.owner.inputs[0][idx1:new_idx2]]
return [u.owner.inputs[0][new_idx1:new_idx2]]
@register_canonicalize
@gof.local_optimizer([None])
......
theano/tensor/tests/test_opt.py
浏览文件 @ 24102962
......@@ -1271,13 +1271,17 @@ class test_local_subtensor_lift(unittest.TestCase):
f([1,2,3], 4) # let debugmode test something
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.rng = numpy.random.RandomState(seed=utt.fetch_seed())
def test_const(self):
# var[const::][-1] -> var[-1]
x = TT.matrix('x')
x_val = [[0,1],[2,3]]
for idx in range(-5,4):
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'))
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
......@@ -1286,20 +1290,23 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
if idx<2:
# The first subtensor is non-empty, so it makes sense
f(x_val) # let debugmode test something
else:
# A non-empty subtensor of an empty one should be an IndexError
self.assertRaises(IndexError, f, x_val)
f = function([x], x[::-1][idx], mode=mode_opt.excluding('local_subtensor_merge'))
self.assertRaises(IndexError, f, x_val)
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
else:
# A non-empty subtensor of an empty one should be an IndexError
self.assertRaises(IndexError, f, x_val)
self.assertRaises(IndexError, g, x_val)
def test_scalar(self):
# var[int::][-1] -> var[-1]
x = TT.matrix('x')
y = TT.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'))
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
......@@ -1308,13 +1315,16 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
x_val = [[0,1],[2,3]]
for idx in range(-10,2):
f(x_val, idx) # let debugmode test something
for idx in range(2,5):
self.assertRaises(IndexError, f, x_val, idx)
f = function([x,y], x[::-1][y], mode=mode_opt.excluding('local_subtensor_merge'))
self.assertRaises(IndexError, f, x_val, idx)
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
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
else:
self.assertRaises(IndexError, f, x_val, idx)
self.assertRaises(IndexError, g, x_val, idx)
def test_dont_opt(self):
# Test that we don't optimize some case
......@@ -1329,14 +1339,18 @@ class test_local_subtensor_merge(unittest.TestCase):
assert isinstance(topo[0].op, TT.Subtensor)
assert isinstance(topo[1].op, TT.Subtensor)
assert isinstance(topo[2].op, theano.compile.function_module.DeepCopyOp)
f([[0,1],[2,3]]) # let debugmode test something
# let debugmode test something
for x_s in self.x_shapes:
if x_s[0] > 1:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
f(x_val)
def test_const2(self):
# var[::-1][const] -> var[-1]
x = TT.matrix('x')
x_val = [[0,1],[2,3]]
for idx in range(-5,4):
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'))
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
......@@ -1345,20 +1359,22 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
if idx<2 and idx>=-2:
# The first subtensor is non-empty, so it makes sense
f(x_val) # let debugmode test something
else:
# A non-empty subtensor of an empty one should be an IndexError
self.assertRaises(IndexError, f, x_val)
f2 = function([x], x[::-1][idx], mode=mode_opt.excluding('local_subtensor_merge'))
self.assertRaises(IndexError, f2, x_val)
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
else:
# A non-empty subtensor of an empty one should be an IndexError
self.assertRaises(IndexError, f, x_val)
self.assertRaises(IndexError, g, x_val)
def test_scalar2(self):
# var[::-1][int] -> var[-1]
x = TT.matrix('x')
y = TT.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'))
#theano.printing.debugprint(f, print_type=True)
topo=f.maker.env.toposort()
......@@ -1367,13 +1383,14 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
x_val = [[0,1],[2,3]]
for idx in range(-2,2):
f(x_val, idx) # let debugmode test something
for idx in range(2,5)+range(-5,-2):
self.assertRaises(IndexError, f, x_val, idx)
f = function([x,y], x[::-1][y], mode=mode_opt.excluding('local_subtensor_merge'))
self.assertRaises(IndexError, f, x_val, idx)
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
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_dont_opt2(self):
# Test that we don't optimize some case
......@@ -1388,13 +1405,16 @@ class test_local_subtensor_merge(unittest.TestCase):
assert isinstance(topo[0].op, TT.Subtensor)
assert isinstance(topo[1].op, TT.Subtensor)
assert isinstance(topo[2].op, theano.compile.function_module.DeepCopyOp)
f([[0,1],[2,3]]) # let debugmode test something
# let debugmode test something
for x_s in self.x_shapes:
if x_s[0] > 0:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
f(x_val)
def test_const3(self):
# var[::-1][:const] -> var[-1]
x = TT.matrix('x')
x_val = [[0,1],[2,3]]
for idx in range(-5,4):
for idx in range(-9,8):
f = function([x], x[::-1][:idx], mode=mode_opt)
#theano.printing.debugprint(f, print_type=True)
......@@ -1404,7 +1424,9 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
f(x_val) # let debugmode test something
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
def test_scalar3(self):
# var[::-1][:int] -> var[-1]
......@@ -1419,9 +1441,10 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
x_val = [[0,1],[2,3]]
for idx in range(-5,5):
f(x_val, idx) # let debugmode test something
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
def test_dont_opt3(self):
# Test that we don't optimize some case
......@@ -1436,14 +1459,16 @@ class test_local_subtensor_merge(unittest.TestCase):
assert isinstance(topo[0].op, TT.Subtensor)
assert isinstance(topo[1].op, TT.Subtensor)
assert isinstance(topo[2].op, theano.compile.function_module.DeepCopyOp)
f([[0,1],[2,3]]) # let debugmode test something
# let debugmode test something
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
f(x_val)
def test_const4(self):
# var[const1::][:const2]
x = TT.matrix('x')
x_val = [[0,1],[2,3]]
for idx1 in range(-3,3):
for idx2 in range(-3,3):
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)
......@@ -1453,7 +1478,9 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
f(x_val) # let debugmode test something
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
def test_scalar4(self):
# var[int1:][:int2]
......@@ -1469,10 +1496,11 @@ class test_local_subtensor_merge(unittest.TestCase):
#print topo[-1].op
assert isinstance(topo[-1].op, theano.compile.function_module.DeepCopyOp)
x_val = [[0,1],[2,3]]
for idx1 in range(-5,5):
for idx2 in range(-5,5):
f(x_val, idx1, idx2) # let debugmode test something
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
def test_dont_opt4(self):
# Test that we don't optimize some case
......@@ -1487,7 +1515,10 @@ class test_local_subtensor_merge(unittest.TestCase):
assert isinstance(topo[0].op, TT.Subtensor)
assert isinstance(topo[1].op, TT.Subtensor)
assert isinstance(topo[2].op, theano.compile.function_module.DeepCopyOp)
f([[0,1],[2,3]]) # let debugmode test something
# let debugmode test something
for x_s in self.x_shapes:
x_val = self.rng.uniform(size=x_s).astype(config.floatX)
f(x_val)
def test_local_fill_useless():
m = theano.config.mode
......
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