Python cuda.CudaNdarray方法代码示例

本文整理汇总了Python中theano.sandbox.cuda.CudaNdarray方法的典型用法代码示例。如果您正苦于以下问题：Python cuda.CudaNdarray方法的具体用法？Python cuda.CudaNdarray怎么用？Python cuda.CudaNdarray使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类theano.sandbox.cuda的用法示例。

在下文中一共展示了cuda.CudaNdarray方法的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: test_output_broadcast_cuda

# 需要导入模块: from theano.sandbox import cuda [as 别名]
# 或者: from theano.sandbox.cuda import CudaNdarray [as 别名]
def test_output_broadcast_cuda(self):
        from theano.sandbox import cuda
        if not cuda.cuda_available:
            raise SkipTest("Optional package Cuda disabled")
        if cuda.use.device_number is None:
            # We should normally set VecAsRowAndCol as a GPUOp But we
            # don't want to do this here as this will disable others
            # tests in this file.  So we manually init the GPU if
            # needed to remove warning.
            cuda.use("gpu",
                     force=True,
                     default_to_move_computation_to_gpu=False,
                     move_shared_float32_to_gpu=False,
                     enable_cuda=False)
        v = cuda.fvector('v')
        c, r = VecAsRowAndCol()(v)
        f = theano.function([v], [c, r])

        v_val = cuda.CudaNdarray(self.rng.randn(5).astype('float32'))
        f(v_val)

开发者ID:muhanzhang，项目名称:D-VAE，代码行数:22，代码来源:test_debugmode.py

示例2: garray_to_cudandarray

# 需要导入模块: from theano.sandbox import cuda [as 别名]
# 或者: from theano.sandbox.cuda import CudaNdarray [as 别名]
def garray_to_cudandarray(x):
        """ take a gnumpy.garray and make a CudaNdarray that point to its memory
        """
        if not isinstance(x, gnumpy.garray):
            raise ValueError("We can transfer only gnumpy.garray to CudaNdarray")
        # elif x.dtype != "float32":
        #     raise ValueError("CudaNdarray support only float32")
        # We don't need this, because cudamat is always float32.
        else:
            strides = [1]
            for i in x.shape[::-1][:-1]:
                strides.append(strides[-1] * i)
            strides = strides[::-1]
            for i in range(len(strides)):
                if x.shape[i] == 1:
                    strides[i] = 0
            strides = tuple(strides)

            import ctypes
            ptr_long = long(ctypes.cast(x._base.mat.data_device, ctypes.c_void_p).value)

            # seems legit.
            z = cuda.from_gpu_pointer(ptr_long, x.shape, strides, x._base)
            return z

开发者ID:muhanzhang，项目名称:D-VAE，代码行数:26，代码来源:gnumpy_utils.py

示例3: test_to_cudandarray

# 需要导入模块: from theano.sandbox import cuda [as 别名]
# 或者: from theano.sandbox.cuda import CudaNdarray [as 别名]
def test_to_cudandarray():
    px = pycuda.gpuarray.zeros((3, 4, 5), 'float32')
    cx = to_cudandarray(px)
    assert isinstance(cx, cuda.CudaNdarray)
    assert numpy.allclose(px.get(),
                          numpy.asarray(cx))
    assert px.dtype == cx.dtype
    assert px.shape == cx.shape
    assert all(numpy.asarray(cx._strides) * 4 == px.strides)

    try:
        px = pycuda.gpuarray.zeros((3, 4, 5), 'float64')
        to_cudandarray(px)
        assert False
    except ValueError:
        pass

    try:
        to_cudandarray(numpy.zeros(4))
        assert False
    except ValueError:
        pass

开发者ID:muhanzhang，项目名称:D-VAE，代码行数:24，代码来源:test_pycuda_utils.py

示例4: test_pycuda_theano

# 需要导入模块: from theano.sandbox import cuda [as 别名]
# 或者: from theano.sandbox.cuda import CudaNdarray [as 别名]
def test_pycuda_theano():
    """Simple example with pycuda function and Theano CudaNdarray object."""
    from pycuda.compiler import SourceModule
    mod = SourceModule("""
__global__ void multiply_them(float *dest, float *a, float *b)
{
  const int i = threadIdx.x;
  dest[i] = a[i] * b[i];
}
""")

    multiply_them = mod.get_function("multiply_them")

    a = numpy.random.randn(100).astype(numpy.float32)
    b = numpy.random.randn(100).astype(numpy.float32)

    # Test with Theano object
    ga = cuda_ndarray.CudaNdarray(a)
    gb = cuda_ndarray.CudaNdarray(b)
    dest = cuda_ndarray.CudaNdarray.zeros(a.shape)
    multiply_them(dest, ga, gb,
                  block=(400, 1, 1), grid=(1, 1))
    assert (numpy.asarray(dest) == a * b).all()

开发者ID:muhanzhang，项目名称:D-VAE，代码行数:25，代码来源:test_pycuda_theano_simple.py

示例5: to_cudandarray

# 需要导入模块: from theano.sandbox import cuda [as 别名]
# 或者: from theano.sandbox.cuda import CudaNdarray [as 别名]
def to_cudandarray(x):
    """ take a pycuda.gpuarray.GPUArray and make a CudaNdarray that point to its memory

    :note: CudaNdarray support only float32, so only float32 GPUArray are accepted
    """
    if not isinstance(x, pycuda.gpuarray.GPUArray):
        raise ValueError("We can transfer only pycuda.gpuarray.GPUArray to CudaNdarray")
    elif x.dtype != "float32":
        raise ValueError("CudaNdarray support only float32")
    else:
        strides = [1]
        for i in x.shape[::-1][:-1]:
            strides.append(strides[-1] * i)
        strides = tuple(strides[::-1])
        ptr = int(x.gpudata)  # in pycuda trunk, y.ptr also works, which is a little cleaner
        z = cuda.from_gpu_pointer(ptr, x.shape, strides, x)
        return z

开发者ID:muhanzhang，项目名称:D-VAE，代码行数:19，代码来源:pycuda_utils.py

示例6: test_host_to_device

# 需要导入模块: from theano.sandbox import cuda [as 别名]
# 或者: from theano.sandbox.cuda import CudaNdarray [as 别名]
def test_host_to_device():
    #print >>sys.stdout, 'starting test_host_to_dev'
    for shape in ((), (3,), (2, 3), (3, 4, 5, 6)):
        a = theano._asarray(numpy.random.rand(*shape), dtype='float32')
        b = cuda_ndarray.CudaNdarray(a)
        c = numpy.asarray(b)
        assert numpy.all(a == c)

        # test with float32 dtype
        d = numpy.asarray(b, dtype='float32')
        assert numpy.all(a == d)

        # test with not float32 dtype
        try:
            numpy.asarray(b, dtype='int8')
            assert False
        except TypeError:
            pass

开发者ID:muhanzhang，项目名称:D-VAE，代码行数:20，代码来源:test_cuda_ndarray.py