提交 5b2cb6f4 authored 作者: Razvan Pascanu's avatar Razvan Pascanu

merge

......@@ -5,6 +5,7 @@ from theano import function
import numpy
from numpy import array
from numpy.testing import dec
from theano import config
from theano.tests import unittest_tools as utt
......@@ -162,8 +163,14 @@ class T_extending(unittest.TestCase):
fn = lambda x, y: x / y)
@dec.knownfailureif(isinstance(theano.compile.mode.get_default_mode(),theano.compile.debugmode.DebugMode),
"This test fail in DEBUG_MODE but this don't make theano generate some bad code. It is a trouble with DEBUG_MODE")
def test_extending_2(self):
'''
This test fails in DebugMode for the same reasons the test in
tensor/tests/test_basic.py:T_scalarfromtensor.test0
fails on debug mode ( as much as I could tell - Razvan )
'''
from theano import gof
class Double(gof.Type):
......@@ -699,29 +706,31 @@ class T_loading_and_saving(unittest.TestCase):
my_obj = theano.function([theano.In(x, borrow=True)]
, theano.Out(y, borrow=True))
f = file('obj.save', 'wb')
cPickle.dump(my_obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
f.close()
mode_instance = theano.compile.mode.get_mode(None)
if not isinstance(mode_instance, theano.compile.debugmode.DebugMode):
f = file('obj.save', 'wb')
cPickle.dump(my_obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
f.close()
f = file('obj.save', 'rb')
loaded_obj = cPickle.load(f)
f.close()
f = file('obj.save', 'rb')
loaded_obj = cPickle.load(f)
f.close()
obj1 = my_obj
obj2 = my_obj
obj3 = my_obj
obj1 = my_obj
obj2 = my_obj
obj3 = my_obj
f = file('objects.save', 'wb')
for obj in [obj1, obj2, obj3]:
cPickle.dump(obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
f.close()
f = file('objects.save', 'wb')
for obj in [obj1, obj2, obj3]:
cPickle.dump(obj, f, protocol=cPickle.HIGHEST_PROTOCOL)
f.close()
f = file('objects.save', 'rb')
loaded_objects = []
for i in range(3):
loaded_objects.append(cPickle.load(f))
f.close()
f = file('objects.save', 'rb')
loaded_objects = []
for i in range(3):
loaded_objects.append(cPickle.load(f))
f.close()
class T_modes(unittest.TestCase):
......@@ -754,8 +763,8 @@ class T_using_gpu(unittest.TestCase):
import numpy
import time
vlen = 10 * 30 * 768 # 10 x #cores x # threads per core
iters = 1000
vlen = 10 * 30 * 70 # 10 x #cores x # threads per core
iters = 10
rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
......@@ -782,8 +791,8 @@ class T_using_gpu(unittest.TestCase):
import numpy
import time
vlen = 10 * 30 * 768 # 10 x #cores x # threads per core
iters = 1000
vlen = 10 * 30 * 70 # 10 x #cores x # threads per core
iters = 10
rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
......@@ -811,8 +820,8 @@ class T_using_gpu(unittest.TestCase):
import numpy
import time
vlen = 10 * 30 * 768 # 10 x #cores x # threads per core
iters = 1000
vlen = 10 * 30 * 70 # 10 x #cores x # threads per core
iters = 10
rng = numpy.random.RandomState(22)
x = shared(numpy.asarray(rng.rand(vlen), config.floatX))
......
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