def setup():
global tf
tf = import_module('tensorflow')
dtcwt.push_backend('tf')
# Make sure we run tests on cpu rather than gpus
os.environ["CUDA_VISIBLE_DEVICES"] = ""
def setup():
global tf
tf = import_module('tensorflow')
dtcwt.push_backend('tf')
# Make sure we run tests on cpu rather than gpus
os.environ["CUDA_VISIBLE_DEVICES"] = ""
def test_backend_with_guard():
"""Test that manipulating the stack with preserve_backend_stack() will
return the stack to its pristine state even i pushes and pops are
imbalanced.
"""
assert len(dtcwt._BACKEND_STACK) == 1
with dtcwt.preserve_backend_stack():
dtcwt.push_backend('numpy')
assert len(dtcwt._BACKEND_STACK) == 2
assert len(dtcwt._BACKEND_STACK) == 1
def test_switch_to_numpy(self):
assert dtcwt.Transform2d is npbackend.Transform2d
assert dtcwt.Pyramid is npbackend.Pyramid
assert dtcwt.backend_name == 'numpy'
dtcwt.push_backend('numpy')
assert dtcwt.Transform2d is npbackend.Transform2d
assert dtcwt.Pyramid is npbackend.Pyramid
assert dtcwt.backend_name == 'numpy'
dtcwt.pop_backend()
assert dtcwt.Transform2d is npbackend.Transform2d
assert dtcwt.Pyramid is npbackend.Pyramid
assert dtcwt.backend_name == 'numpy'
def test_backend_with_guard_and_exception():
"""Tests that even when preserving the backend stack, an exception is
correctly propagated.
"""
dtcwt.push_backend('numpy')
assert len(dtcwt._BACKEND_STACK) == 2
assert dtcwt.backend_name == 'numpy'
with raises(RuntimeError):
with dtcwt.preserve_backend_stack():
dtcwt.push_backend('opencl')
assert dtcwt.backend_name == 'opencl'
assert len(dtcwt._BACKEND_STACK) == 3
raise RuntimeError('test error')
assert dtcwt.backend_name == 'numpy'
assert len(dtcwt._BACKEND_STACK) == 2
def setup():
global mandrill, in_p, pyramid_ops
global tf, Transform1d, dtwavexfm2, dtwaveifm2, Pyramid_tf
global np_dtypes, tf_dtypes, stats
# Import the tensorflow modules
tf = import_module('tensorflow')
dtcwt_tf = import_module('dtcwt.tf')
dtcwt_tf_xfm1 = import_module('dtcwt.tf.transform1d')
Transform1d = getattr(dtcwt_tf, 'Transform1d')
Pyramid_tf = getattr(dtcwt_tf, 'Pyramid')
np_dtypes = getattr(dtcwt_tf_xfm1, 'np_dtypes')
tf_dtypes = getattr(dtcwt_tf_xfm1, 'tf_dtypes')
mandrill = datasets.mandrill()
# Make sure we run tests on cpu rather than gpus
os.environ["CUDA_VISIBLE_DEVICES"] = ""
dtcwt.push_backend('tf')
def setup():
global mandrill, in_p, pyramid_ops
global tf, Transform1d, dtwavexfm2, dtwaveifm2, Pyramid_tf
global np_dtypes, tf_dtypes, stats
# Import the tensorflow modules
tf = import_module('tensorflow')
dtcwt_tf = import_module('dtcwt.tf')
dtcwt_tf_xfm1 = import_module('dtcwt.tf.transform1d')
Transform1d = getattr(dtcwt_tf, 'Transform1d')
Pyramid_tf = getattr(dtcwt_tf, 'Pyramid')
np_dtypes = getattr(dtcwt_tf_xfm1, 'np_dtypes')
tf_dtypes = getattr(dtcwt_tf_xfm1, 'tf_dtypes')
mandrill = datasets.mandrill()
# Make sure we run tests on cpu rather than gpus
os.environ["CUDA_VISIBLE_DEVICES"] = ""
dtcwt.push_backend('tf')
def setup():
# Import some tf only dependencies
global mandrill, Transform2d, Pyramid
global tf, np_dtypes, tf_dtypes, dtwavexfm2, dtwaveifm2
# Import the tensorflow modules
tf = import_module('tensorflow')
dtcwt.push_backend('tf')
Transform2d = getattr(dtcwt, 'Transform2d')
Pyramid = getattr(dtcwt, 'Pyramid')
compat = import_module('dtcwt.compat')
dtwavexfm2 = getattr(compat, 'dtwavexfm2')
dtwaveifm2 = getattr(compat, 'dtwaveifm2')
import dtcwt.tf.transform2d as transform2d
np_dtypes = getattr(transform2d, 'np_dtypes')
tf_dtypes = getattr(transform2d, 'tf_dtypes')
mandrill = datasets.mandrill()
# Make sure we run tests on cpu rather than gpus
os.environ["CUDA_VISIBLE_DEVICES"] = ""
def test_switch_to_invalid(self):
with raises(ValueError):
dtcwt.push_backend('does-not-exist')
def tst():
with dtcwt.preserve_backend_stack():
dtcwt.push_backend('numpy')
assert len(dtcwt._BACKEND_STACK) == 2
raise RuntimeError('test error')
def test_switch_to_invalid(self):
dtcwt.push_backend('does-not-exist')
