def test_unpickle_gpuarray_as_numpy_ndarray_flag2():
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = True
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'GpuArray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
try:
mat = u.load()
except ImportError:
# Windows sometimes fail with nonsensical errors like:
# ImportError: No module named type
# ImportError: No module named copy_reg
# when "type" and "copy_reg" are builtin modules.
if sys.platform == 'win32':
exc_type, exc_value, exc_trace = sys.exc_info()
reraise(SkipTest, exc_value, exc_trace)
raise
assert isinstance(mat, numpy.ndarray)
assert mat[0] == -42.0
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_unpickle_cudandarray_as_numpy_ndarray_flag0():
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = False
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'CudaNdarray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
if cuda_available:
try:
mat = u.load()
except ImportError:
# Windows sometimes fail with nonsensical errors like:
# ImportError: No module named type
# ImportError: No module named copy_reg
# when "type" and "copy_reg" are builtin modules.
if sys.platform == 'win32':
exc_type, exc_value, exc_trace = sys.exc_info()
reraise(SkipTest, exc_value, exc_trace)
raise
assert isinstance(mat, CudaNdarray)
assert numpy.asarray(mat)[0] == -42.0
else:
assert_raises(ImportError, u.load)
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_n_samples_compatibility():
"""
This test checks if the new change to MultinomialFromUniform is still compatible
with old interface. Here I will load a graph created (using the old interface) as follows:
RandomStreams = theano.sandbox.rng_mrg.MRG_RandomStreams
th_rng = RandomStreams(12345)
X = T.matrix('X')
pvals = T.exp(X)
pvals = pvals / pvals.sum(axis=1, keepdims=True)
samples = th_rng.multinomial(pvals=pvals)
pickle.dump([X, samples], open("multinomial_test_graph.pkl", "w"))
"""
folder = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(folder, "multinomial_test_graph.pkl"),
"rb") as pkl_file:
if PY3:
u = CompatUnpickler(pkl_file, encoding="latin1")
else:
u = CompatUnpickler(pkl_file)
try:
X, samples = u.load()
except ImportError:
# Windows sometimes fail with nonsensical errors like:
# ImportError: No module named type
# ImportError: No module named copy_reg
# when "type" and "copy_reg" are builtin modules.
if sys.platform == 'win32':
exc_type, exc_value, exc_trace = sys.exc_info()
reraise(SkipTest, exc_value, exc_trace)
raise
f = theano.function([X], samples)
res = f(numpy.random.randn(20, 10))
assert numpy.all(res.sum(axis=1) == 1)
def test_n_samples_compatibility():
"""
This test checks if the new change to MultinomialFromUniform is still compatible
with old interface. Here I will load a graph created (using the old interface) as follows:
RandomStreams = theano.sandbox.rng_mrg.MRG_RandomStreams
th_rng = RandomStreams(12345)
X = T.matrix('X')
pvals = T.exp(X)
pvals = pvals / pvals.sum(axis=1, keepdims=True)
samples = th_rng.multinomial(pvals=pvals)
pickle.dump([X, samples], open("multinomial_test_graph.pkl", "w"))
"""
folder = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(folder, "multinomial_test_graph.pkl"),
"rb") as pkl_file:
if PY3:
u = CompatUnpickler(pkl_file, encoding="latin1")
else:
u = CompatUnpickler(pkl_file)
try:
X, samples = u.load()
except ImportError:
# Windows sometimes fail with nonsensical errors like:
# ImportError: No module named type
# ImportError: No module named copy_reg
# when "type" and "copy_reg" are builtin modules.
if sys.platform == 'win32':
exc_type, exc_value, exc_trace = sys.exc_info()
reraise(SkipTest, exc_value, exc_trace)
raise
f = theano.function([X], samples)
res = f(np.random.randn(20, 10))
assert np.all(res.sum(axis=1) == 1)
def test_unpickle_gpuarray_as_numpy_ndarray_flag2():
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = True
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = "GpuArray.pkl"
with open(os.path.join(testfile_dir, fname), "rb") as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
try:
mat = u.load()
except ImportError:
# Windows sometimes fail with nonsensical errors like:
# ImportError: No module named type
# ImportError: No module named copy_reg
# when "type" and "copy_reg" are builtin modules.
if sys.platform == "win32":
exc_type, exc_value, exc_trace = sys.exc_info()
reraise(SkipTest, exc_value, exc_trace)
raise
assert isinstance(mat, numpy.ndarray)
assert mat[0] == -42.0
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_unpickle_legacy_op():
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'test_gpuarray_multinomial_wo_replacement.pkl'
if not PY3:
with open(os.path.join(testfile_dir, fname), 'r') as fp:
u = CompatUnpickler(fp)
m = u.load()
assert isinstance(m, GPUAChoiceFromUniform)
def test_unpickle_legacy_op(self):
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = "test_sandbox_multinomial_wo_replacement.pkl"
if not PY3:
with open(os.path.join(testfile_dir, fname), "r") as fp:
u = CompatUnpickler(fp)
m = u.load()
print(m)
assert isinstance(m, multinomial.ChoiceFromUniform)
def test_node_outputs_not_used(self):
# In the past, we where removing some not used variable from
# fgraph.variables event if the apply had other output used in
# the graph. This caused a crash.
# This test run the pickle that reproduce this case.
with open(os.path.join(os.path.dirname(__file__),
'test_fg_old_crash.pkl'),
'rb') as f:
from theano.misc.pkl_utils import CompatUnpickler
if PY3:
u = CompatUnpickler(f, encoding="latin1")
else:
u = CompatUnpickler(f)
d = u.load()
f = theano.function(**d)
def test_node_outputs_not_used(self):
# In the past, we where removing some not used variable from
# fgraph.variables event if the apply had other output used in
# the graph. This caused a crash.
# This test run the pickle that reproduce this case.
with open(
os.path.join(os.path.dirname(__file__),
'test_fg_old_crash.pkl'), 'rb') as f:
from theano.misc.pkl_utils import CompatUnpickler
if PY3:
u = CompatUnpickler(f, encoding="latin1")
else:
u = CompatUnpickler(f)
d = u.load()
f = theano.function(**d)
def test_unpickle_gpuarray_as_numpy_ndarray_flag0():
# Test when pygpu isn't there for unpickle are in test_pickle.py
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = False
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'GpuArray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
mat = u.load()
assert isinstance(mat, pygpu.gpuarray.GpuArray)
assert np.asarray(mat)[0] == -42.0
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_node_outputs_not_used(self):
"""In the past, we where removing some not used variable from
fgraph.variables event if the apply had other output used in
the graph. This caused a crash.
This test run the pickle that reproduce this case.
"""
if sys.version_info[:2] < (2, 7):
raise SkipTest("This test need python 2.7 or more recent.")
with open(
os.path.join(os.path.dirname(__file__),
'test_fg_old_crash.pkl'), 'rb') as f:
from theano.misc.pkl_utils import CompatUnpickler
if PY3:
u = CompatUnpickler(f, encoding="latin1")
else:
u = CompatUnpickler(f)
d = u.load()
f = theano.function(**d)
def test_unpickle_gpuarray_as_numpy_ndarray_flag0():
""" Test when pygpu isn't there for unpickle are in test_pickle.py"""
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = False
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'GpuArray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
mat = u.load()
assert isinstance(mat, pygpu.gpuarray.GpuArray)
assert np.asarray(mat)[0] == -42.0
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_node_outputs_not_used(self):
"""In the past, we where removing some not used variable from
fgraph.variables event if the apply had other output used in
the graph. This caused a crash.
This test run the pickle that reproduce this case.
"""
if sys.version_info[:2] < (2, 7):
raise SkipTest("This test need python 2.7 or more recent.")
with open(os.path.join(os.path.dirname(__file__),
'test_fg_old_crash.pkl'),
'rb') as f:
from theano.misc.pkl_utils import CompatUnpickler
if PY3:
u = CompatUnpickler(f, encoding="latin1")
else:
u = CompatUnpickler(f)
d = u.load()
f = theano.function(**d)
def test_unpickle_cudandarray_as_numpy_ndarray_flag1():
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = True
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'CudaNdarray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
mat = u.load()
assert isinstance(mat, numpy.ndarray)
assert mat[0] == -42.0
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_unpickle_gpuarray_as_numpy_ndarray_flag2():
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = True
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'GpuArray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
mat = u.load()
assert isinstance(mat, numpy.ndarray)
assert mat[0] == -42.0
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_unpickle_cudandarray_as_numpy_ndarray_flag0():
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = False
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'CudaNdarray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
if cuda_available:
mat = u.load()
assert isinstance(mat, CudaNdarray)
assert numpy.asarray(mat)[0] == -42.0
else:
assert_raises(ImportError, u.load)
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_unpickle_gpuarray_as_numpy_ndarray_flag1():
# Only test when pygpu isn't
# available. test_unpickle_gpuarray_as_numpy_ndarray_flag0 in
# test_type.py test it when pygpu is there.
if have_pygpu:
raise SkipTest("pygpu active")
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = False
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = 'GpuArray.pkl'
with open(os.path.join(testfile_dir, fname), 'rb') as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
assert_raises((ImportError, ContextNotDefined), u.load)
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
def test_n_samples_compatibility():
"""
This test checks if the new change to MultinomialFromUniform is still compatible
with old interface. Here I will load a graph created (using the old interface) as follows:
RandomStreams = theano.sandbox.rng_mrg.MRG_RandomStreams
th_rng = RandomStreams(12345)
X = T.matrix('X')
pvals = T.exp(X)
pvals = pvals / pvals.sum(axis=1, keepdims=True)
samples = th_rng.multinomial(pvals=pvals)
pickle.dump([X, samples], open("multinomial_test_graph.pkl", "w"))
"""
folder = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(folder, "multinomial_test_graph.pkl"), "rb") as pkl_file:
if PY3:
u = CompatUnpickler(pkl_file, encoding="latin1")
else:
u = CompatUnpickler(pkl_file)
X, samples = u.load()
f = theano.function([X], samples)
res = f(numpy.random.randn(20,10))
assert numpy.all(res.sum(axis=1) == 1)
def test_n_samples_compatibility():
"""
This test checks if the new change to MultinomialFromUniform is still compatible
with old interface. Here I will load a graph created (using the old interface) as follows:
RandomStreams = theano.sandbox.rng_mrg.MRG_RandomStreams
th_rng = RandomStreams(12345)
X = T.matrix('X')
pvals = T.exp(X)
pvals = pvals / pvals.sum(axis=1, keepdims=True)
samples = th_rng.multinomial(pvals=pvals)
pickle.dump([X, samples], open("multinomial_test_graph.pkl", "w"))
"""
folder = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(folder, "multinomial_test_graph.pkl"),
"rb") as pkl_file:
if PY3:
u = CompatUnpickler(pkl_file, encoding="latin1")
else:
u = CompatUnpickler(pkl_file)
X, samples = u.load()
f = theano.function([X], samples)
res = f(numpy.random.randn(20, 10))
assert numpy.all(res.sum(axis=1) == 1)
def test_unpickle_gpuarray_as_numpy_ndarray_flag1():
oldflag = config.experimental.unpickle_gpu_on_cpu
config.experimental.unpickle_gpu_on_cpu = False
try:
testfile_dir = os.path.dirname(os.path.realpath(__file__))
fname = "GpuArray.pkl"
with open(os.path.join(testfile_dir, fname), "rb") as fp:
if PY3:
u = CompatUnpickler(fp, encoding="latin1")
else:
u = CompatUnpickler(fp)
with pytest.raises((ImportError, ContextNotDefined)):
u.load()
finally:
config.experimental.unpickle_gpu_on_cpu = oldflag
