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提交 f8e25def authored 作者: Frederic Bastien's avatar Frederic Bastien
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theano/tensor/tests/test_opt.py
浏览文件 @ f8e25def
......@@ -96,7 +96,7 @@ class test_greedy_distribute(unittest.TestCase):
mul_canonizer.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):
x, y = vectors('xy')
eps = scalar('eps')
......@@ -153,7 +153,7 @@ class test_canonize(unittest.TestCase):
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)
fx, fy, fz = fmatrices('xyz')
dx, dy, dz = dmatrices('xyz')
......@@ -219,7 +219,7 @@ class test_canonize(unittest.TestCase):
f = compile.function(list(sym_inputs), g,
#we need the optimisation enabled, debug do this.
mode=mode)
out = f(*val_inputs)
assert(len(f.maker.env.toposort())==nb_elemwise)
assert(out_dtype==out.dtype)
......@@ -233,7 +233,7 @@ class test_canonize(unittest.TestCase):
Test with and without DimShuffle
"""
raise SkipTest("Current implementation of Canonizer don't implement all case. Skip the corresponding test")
shp=(5,5)
fx, fy, fz = fmatrices('xyz')
dx, dy, dz = dmatrices('xyz')
......@@ -297,11 +297,11 @@ class test_canonize(unittest.TestCase):
f = compile.function(list(sym_inputs), g,
#we need the optimisation enabled, debug do this.
mode=mode)
out = f(*val_inputs)
assert(len(f.maker.env.toposort())==nb_elemwise)
assert(out_dtype==out.dtype)
def test_multiple_case(self):
""" test those case take from the comment in Canonizer
x / x -> 1
......@@ -461,7 +461,7 @@ class test_canonize(unittest.TestCase):
assert isinstance(topo[1].op.scalar_op,theano.scalar.basic.TrueDiv)
assert len(topo[1].inputs)==2
assert(out_dtype==out.dtype)
#test 2 * x / 2 -> x
for id,(g, sym_inputs, val_inputs, out_dtype) in enumerate([
((2*dx)/2,[dx],[dxv],'float64'),
......@@ -477,7 +477,7 @@ class test_canonize(unittest.TestCase):
assert len(topo)==1
topo[0].op==theano.compile.function_module.deep_copy_op
assert(out_dtype==out.dtype)
#test x / abs(x) -> sign(x)
for id,(g, sym_inputs, val_inputs, out_dtype) in enumerate([
(dx/abs(dx),[dx],[0.5-dxv],'float64'),
......@@ -516,13 +516,13 @@ class test_canonize(unittest.TestCase):
def test_abs_mul_div(self):
"""
test that if we have
test that if we have
4 * x / abs(2*x) it get simplifier during canonicalisation.
"""
x=T.dscalar()
a=T.abs_(x)
if theano.config.mode=='FAST_COMPILE':
mode = theano.compile.mode.get_mode('FAST_RUN').excluding("local_elemwise_fusion")
else:
......@@ -838,9 +838,9 @@ class test_fusion(unittest.TestCase):
print "Executed",len(cases),"cases", "failed", failed
if failed>0:
raise Exception("Failed %d cases"%failed, fail1, fail2, fail3, fail4)
return times
def test_elemwise_fusion(self):
shp=(5,5)
mode=copy.copy(compile.mode.get_default_mode())
......@@ -867,13 +867,13 @@ class test_fusion(unittest.TestCase):
param type s: a slice object
param s: a slice to apply to the case to execute. If None, exec all case.
"""
shp=(3000,3000)
shp=(1000,1000)
nb_repeat=50
# linker=gof.CLinker
# linker=gof.OpWiseCLinker
mode1=copy.copy(compile.get_default_mode())
mode1._optimizer=mode1._optimizer.including('local_elemwise_fusion')
#TODO:clinker is much faster... but use to much memory
......@@ -890,7 +890,7 @@ class test_fusion(unittest.TestCase):
print "times2 without local_elemwise_fusion"
print times2, times2.min(), times2.max(), times2.sum()
d=times2/times1
print "times2/times1"
print d
print "min", d.min(), "argmin", d.argmin(), "max", d.max(), "mean", d.mean(), "std", d.std()
......@@ -912,7 +912,7 @@ class test_fusion(unittest.TestCase):
def speed_fusion_gpu(self):
import theano.sandbox.cuda as cuda
self.speed_fusion(shared_fn=tcn.float32_shared_constructor, gpu=True, s=slice(0,15))
def speed_log_exp(self):
s=slice(31,36)
# linker=gof.CLinker
......@@ -968,7 +968,7 @@ class test_fusion(unittest.TestCase):
else: print None
gc.collect();gc.collect();gc.collect()
d=nd
# pdb.set_trace()
if False:
gc.collect();gc.collect();gc.collect()
......@@ -1000,7 +1000,7 @@ class test_fusion(unittest.TestCase):
# cases[id]=None #to remove g, that link to out that link to the ndarray!
#g.owner.inputs[0] is out... make owner a weakref?
def test_log1p():
m = theano.config.mode
if m == 'FAST_COMPILE':
......@@ -1034,8 +1034,8 @@ def test_log1p():
assert [node.op for node in f.maker.env.toposort()][3:] \
== [T.log1p, alloc]
f([1e-7, 10], [[0, 0], [0, 0]]) #debugmode will verify values
f([1e-7, 10], [[0, 0], [0, 0]]) #debugmode will verify values
if 0:
# at one point this worked, but it has been broken since
# the constant up-casting made 1 -> 1.0+0.0j
......@@ -1310,7 +1310,7 @@ class test_assert(unittest.TestCase):
def test_local_mul_specialize():
# test a few cases to make sure that the basics are covered
#
#
mode = theano.config.mode
if mode == 'FAST_COMPILE':
......@@ -1388,11 +1388,11 @@ def speed_local_pow_specialize_range():
def test_local_pow_specialize():
# test a few cases to make sure that the basics are covered
#
#
mode = theano.config.mode
if mode == 'FAST_COMPILE':
mode = 'FAST_RUN'
mode = 'FAST_RUN'
mode = compile.mode.get_mode(mode)
mode = mode.excluding('fusion')
......@@ -1447,7 +1447,7 @@ def test_local_pow_specialize_device():
mode = theano.config.mode
if mode == 'FAST_COMPILE':
mode = 'FAST_RUN'
mode = 'FAST_RUN'
mode = compile.mode.get_mode(mode)
mode = mode.excluding('fusion').excluding('gpu')
......@@ -1460,7 +1460,7 @@ def test_local_pow_specialize_device():
assert len(f.maker.env.toposort()[0].op.scalar_op.env.nodes)==6
assert isinstance(nodes[0].scalar_op,theano.scalar.Composite)
assert numpy.allclose(f(val),val**15)
f = function([v], v**(-15), mode=mode)
nodes = [node.op for node in f.maker.env.toposort()]
assert len(nodes)==2
......@@ -1468,14 +1468,14 @@ def test_local_pow_specialize_device():
assert isinstance(nodes[0].scalar_op,theano.scalar.Composite)
assert isinstance(nodes[-1].scalar_op,theano.scalar.basic.Inv)
assert numpy.allclose(f(val_no0),val_no0**(-15))
f = function([v], v**(16), mode=mode)
nodes = [node.op for node in f.maker.env.toposort()]
assert len(nodes) == 1
assert len(f.maker.env.toposort()[0].op.scalar_op.env.nodes)==4
assert isinstance(nodes[0].scalar_op,theano.scalar.Composite)
assert numpy.allclose(f(val),val**16)
f = function([v], v**(-16), mode=mode)
nodes = [node.op for node in f.maker.env.toposort()]
assert len(nodes) == 2
......@@ -1483,7 +1483,7 @@ def test_local_pow_specialize_device():
assert isinstance(nodes[0].scalar_op,theano.scalar.Composite)
assert isinstance(nodes[-1].scalar_op,theano.scalar.basic.Inv)
assert numpy.allclose(f(val_no0),val_no0**(-16))
class T_Rebroadcast(unittest.TestCase):
def test_local_useless_rebroadcast(self):
......@@ -1754,7 +1754,7 @@ class T_local_erfc(unittest.TestCase):
self.mode_fusion = theano.compile.mode.get_default_mode().including('canonicalize').including('fast_run').excluding('gpu')
self.mode = self.mode_fusion.excluding('fusion')
self.mode._optimizer.position_cutoff = 1.50001
def test_local_one_minus_erfc(self):
""" test opt: 1-erfc(x) => erf(x) and -erfc(x)+1 => erf(x)
"""
......@@ -1839,7 +1839,7 @@ class T_local_erfc(unittest.TestCase):
val = [-100,-30,-27,-26.4,-26.2,-26,-11,-10,-9,-3,-2,-1,0,1,2,3,9,10,11,27,26.4,26.2,26,28,30,100]
if theano.config.mode in ["DebugMode", "DEBUG_MODE", "FAST_COMPILE"]:
#python mode don't like the inv(0) in computation, but the switch don't select this value. So it is computed for no good reason.
val.remove(0)
val.remove(0)
if theano.config.mode in ["DebugMode", "DEBUG_MODE"] and theano.config.floatX=='float32':
# In float32 their is a plage of values close to 10 that we stabilize as it give bigger error then the stabilized version.
# The orig value in float32 -30.0, the stab value -20.1 the orig value in float64 -18.1.
......@@ -2069,7 +2069,7 @@ def test_make_vector():
b = T.bscalar()
i = T.iscalar()
d = T.dscalar()
assert opt.MakeVector(dtype="int8")(b,b).dtype=="int8"
assert opt.MakeVector(dtype="int32")(i,b).dtype=="int32"
assert opt.MakeVector(dtype="int32")(b,i).dtype=="int32"
......
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