Python chainer.backends.cuda.available() Examples

The following are 9 code examples of chainer.backends.cuda.available(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module chainer.backends.cuda , or try the search function .
Example #1
Source File: test_link.py    From chainer with MIT License 6 votes vote down vote up 
def setUp(self):
        x_shape_0 = 2
        x_shape_1 = numpy.int64(3)
        self.link = chainer.Link(x=((x_shape_0, x_shape_1), 'd'),
                                 u=(None, 'd'))
        with self.link.init_scope():
            self.link.y = chainer.Parameter(shape=(2,))
            self.link.v = chainer.Parameter()
        self.p = numpy.array([1, 2, 3], dtype='f')
        self.link.add_persistent('p', self.p)
        self.link.name = 'a'
        self.link.x.update_rule = chainer.UpdateRule()
        self.link.x.update_rule.enabled = False
        self.link.u.update_rule = chainer.UpdateRule()
        if cuda.available:
            self.current_device_id = cuda.cupy.cuda.get_device_id()
Example #2
Source File: test_link.py    From chainer with MIT License 6 votes vote down vote up 
def setUp(self):
        self.link = chainer.Link()
        shape = (2, 2)
        dtype = numpy.float32
        y_array = numpy.random.rand(*shape).astype(dtype)
        pa_array = numpy.random.rand(*shape).astype(dtype)
        ps_scalar = 2.4

        with self.link.init_scope():
            # Initialized parameter
            self.link.y = chainer.Parameter(y_array)
            # Uninitialized parameter
            self.link.v = chainer.Parameter()
            # Persistent ndarray
            self.link.add_persistent('pa', pa_array)
            # Persistent scalar
            self.link.add_persistent('ps', ps_scalar)
        self.y_array = y_array
        self.pa_array = pa_array
        self.ps_scalar = ps_scalar

        if cuda.available:
            self.current_device_id = cuda.cupy.cuda.get_device_id()
Example #3
Source File: test_link.py    From chainer with MIT License 5 votes vote down vote up 
def tearDown(self):
        if cuda.available \
                and cuda.cupy.cuda.get_device_id() != self.current_device_id:
            cuda.Device(self.current_device_id).use()
Example #4
Source File: conftest.py    From chainer with MIT License 5 votes vote down vote up 
def pytest_runtest_teardown(item, nextitem):
    if cuda.available:
        assert cuda.cupy.cuda.runtime.getDevice() == 0


# testing.run_module(__name__, __file__)
Example #5
Source File: test_cuda.py    From chainer with MIT License 5 votes vote down vote up 
def test_to_gpu_unavailable(self):
        x = numpy.array([1])
        if not cuda.available:
            with self.assertRaises(RuntimeError):
                cuda.to_gpu(x)
Example #6
Source File: _runtime_info.py    From chainer with MIT License 5 votes vote down vote up 
def __init__(self):
        self.chainer_version = chainer.__version__
        self.chainerx_available = chainerx.is_available()
        self.numpy_version = numpy.__version__
        self.platform_version = platform.platform()
        if cuda.available:
            self.cuda_info = cuda.cupyx.get_runtime_info()
        else:
            self.cuda_info = None
        if intel64.is_ideep_available():
            self.ideep_version = intel64.ideep.__version__
        else:
            self.ideep_version = None
Example #7
Source File: backend.py    From chainer with MIT License 5 votes vote down vote up 
def get_array_module(*args):
    """Gets an appropriate NumPy-compatible module to process arguments

    This function will return their data arrays' array module for
    :class:`~chainer.Variable` arguments.

    Args:
        args: Values to determine whether NumPy, CuPy, or ChainerX should be
            used.

    Returns:
        module: :mod:`numpy`, :mod:`cupy`, or :mod:`chainerx` is returned based
        on the types of the arguments.

    """
    is_chainerx_available = chainerx.is_available()
    if is_chainerx_available or cuda.available:
        arrays = []
        for arg in args:
            # Unwrap arrays
            if isinstance(arg, chainer.variable.Variable):
                array = arg.data
            else:
                array = arg
            if is_chainerx_available and isinstance(array, chainerx.ndarray):
                return chainerx
            arrays.append(array)
        if cuda.available:
            return cuda.cupy.get_array_module(*arrays)
    return numpy
Example #8
Source File: random.py    From chainer with MIT License 5 votes vote down vote up 
def do_setup(deterministic=True):
    if cuda.available:
        cuda.cupy.testing.random.do_setup(deterministic)
    else:
        _numpy_do_setup(deterministic)
Example #9
Source File: random.py    From chainer with MIT License 5 votes vote down vote up 
def do_teardown():
    if cuda.available:
        cuda.cupy.testing.random.do_teardown()
    else:
        _numpy_do_teardown()


# In some tests (which utilize condition.repeat or condition.retry),
# setUp/tearDown is nested. _setup_random() and _teardown_random() do their
# work only in the outermost setUp/tearDown pair.