def test_maxout_conv_c01b_cifar10(self):
if cuda.cuda_available is False:
raise SkipTest('Optional package cuda disabled')
if not hasattr(cuda, 'unuse'):
raise Exception("Theano version too old to run this test!")
# Tests that we can run a small convolutional model on GPU,
assert cuda.cuda_enabled is False
# Even if there is a GPU, but the user didn't specify device=gpu
# we want to run this test.
try:
old_floatX = config.floatX
cuda.use('gpu')
config.floatX = 'float32'
try:
train = yaml_parse.load(yaml_string_maxout_conv_c01b_cifar10)
except NoDataPathError:
raise SkipTest("PYLEARN2_DATA_PATH environment variable "
"not defined")
train.main_loop()
# Check that the performance is close to the expected one:
# test_y_misclass: 0.3777000308036804
misclass_chan = train.algorithm.monitor.channels['test_y_misclass']
assert misclass_chan.val_record[-1] < 0.38
# test_y_nll: 1.0978516340255737
nll_chan = train.algorithm.monitor.channels['test_y_nll']
assert nll_chan.val_record[-1] < 1.1
finally:
config.floatX = old_floatX
cuda.unuse()
assert cuda.cuda_enabled is False
def test_maxout_conv_c01b_cifar10(self):
if cuda.cuda_available is False:
raise SkipTest('Optional package cuda disabled')
if not hasattr(cuda, 'unuse'):
raise Exception("Theano version too old to run this test!")
# Tests that we can run a small convolutional model on GPU,
assert cuda.cuda_enabled is False
# Even if there is a GPU, but the user didn't specify device=gpu
# we want to run this test.
try:
old_floatX = config.floatX
cuda.use('gpu')
config.floatX = 'float32'
try:
train = yaml_parse.load(yaml_string_maxout_conv_c01b_cifar10)
except NoDataPathError:
raise SkipTest("PYLEARN2_DATA_PATH environment variable "
"not defined")
train.main_loop()
# Check that the performance is close to the expected one:
# test_y_misclass: 0.3777000308036804
misclass_chan = train.algorithm.monitor.channels['test_y_misclass']
assert misclass_chan.val_record[-1] < 0.38, \
("misclass_chan.val_record[-1] = %g" %
misclass_chan.val_record[-1])
# test_y_nll: 1.0978516340255737
nll_chan = train.algorithm.monitor.channels['test_y_nll']
assert nll_chan.val_record[-1] < 1.1
finally:
config.floatX = old_floatX
cuda.unuse()
assert cuda.cuda_enabled is False
def test_maxout_conv_c01b_basic(self):
if cuda.cuda_available is False:
raise SkipTest('Optional package cuda disabled')
if not hasattr(cuda, 'unuse'):
raise Exception("Theano version too old to run this test!")
# Tests that we can run a small convolutional model on GPU,
assert cuda.cuda_enabled is False
# Even if there is a GPU, but the user didn't specify device=gpu
# we want to run this test.
try:
old_floatX = config.floatX
cuda.use('gpu')
config.floatX = 'float32'
train = yaml_parse.load(yaml_string_maxout_conv_c01b_basic)
train.main_loop()
finally:
config.floatX = old_floatX
cuda.unuse()
assert cuda.cuda_enabled is False
def test_maxout_conv_c01b_basic(self):
if cuda.cuda_available is False:
raise SkipTest('Optional package cuda disabled')
if not hasattr(cuda, 'unuse'):
raise Exception("Theano version too old to run this test!")
# Tests that we can run a small convolutional model on GPU,
assert cuda.cuda_enabled is False
# Even if there is a GPU, but the user didn't specify device=gpu
# we want to run this test.
try:
old_floatX = config.floatX
cuda.use('gpu')
config.floatX = 'float32'
train = yaml_parse.load(yaml_string_maxout_conv_c01b_basic)
train.main_loop()
finally:
config.floatX = old_floatX
cuda.unuse()
assert cuda.cuda_enabled is False
