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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?那么恭喜您, 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

示例7: test_exp

# 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_exp():
    #print >>sys.stdout, 'starting test_exp'
    for shape in ((), (3,), (2, 3),
                  (1, 10000000), (10, 1000000),
                  (100, 100000), (1000, 10000), (10000, 1000)):
        a0 = theano._asarray(numpy.random.rand(*shape), dtype='float32')
        a1 = a0.copy()
        b0 = cuda_ndarray.CudaNdarray(a0)
        b1 = cuda_ndarray.CudaNdarray(a1)
        t0 = time.time()
        bsum = b0.exp()
        t1 = time.time()
        gpu_dt = t1 - t0
        t0 = time.time()
        asum = numpy.exp(a1)
        t1 = time.time()
        cpu_dt = t1 - t0
        # print shape, 'adding ', a0.size, 'cpu', cpu_dt, 'advantage', advantage(cpu_dt, gpu_dt)
        #c = numpy.asarray(b0+b1)
        if asum.shape:
            assert numpy.allclose(asum, numpy.asarray(bsum)) 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:23,代码来源:test_cuda_ndarray.py

示例8: test_copy

# 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_copy():
    #print >>sys.stdout, 'starting test_copy'
    shape = (500, 499)
    a = theano._asarray(numpy.random.rand(*shape), dtype='float32')

    #print >>sys.stdout, '.. creating device object'
    b = cuda_ndarray.CudaNdarray(a)

    #print >>sys.stdout, '.. copy'
    c = copy.copy(b)
    #print >>sys.stdout, '.. deepcopy'
    d = copy.deepcopy(b)

    #print >>sys.stdout, '.. comparisons'
    assert numpy.allclose(a, numpy.asarray(b))
    assert numpy.allclose(a, numpy.asarray(c))
    assert numpy.allclose(a, numpy.asarray(d))
    b += b
    assert numpy.allclose(a+a, numpy.asarray(b))
    assert numpy.allclose(a+a, numpy.asarray(c))
    assert numpy.allclose(a, numpy.asarray(d)) 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:23,代码来源:test_cuda_ndarray.py

示例9: test_getshape

# 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_getshape():
    shapelist = [
            ((1, 2, 3), (1, 2, 3)),
            ((1,), (1,)),
            ((1, 2, 3), (3, 2, 1)),
            ((1, 2, 3), (6,)),
            ((1, 2, 3, 2), (6, 2)),
            ((2, 3, 2), (6, 2))
             ]

    def subtest(shape):
        a = theano._asarray(numpy.random.rand(*shape_1), dtype='float32')
        b = cuda_ndarray.CudaNdarray(a)
        assert b.shape == a.shape

    for shape_1, shape_2 in shapelist:
        subtest(shape_1)
        subtest(shape_2) 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:20,代码来源:test_cuda_ndarray.py

示例10: test_stride_manipulation

# 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_stride_manipulation():

    a = theano._asarray([[0, 1, 2], [3, 4, 5]], dtype='float32')
    b = cuda_ndarray.CudaNdarray(a)
    v = b.view()
    v._dev_data += 0
    c = numpy.asarray(v)
    assert numpy.all(a == c)

    sizeof_float = 4
    offset = 0

    b_strides = b._strides
    for i in xrange(len(b.shape)):
        offset += (b.shape[i]-1) * b_strides[i]
        v._set_stride(i, -b_strides[i])

    v._dev_data += offset * sizeof_float
    c = numpy.asarray(v)

    assert numpy.all(c == [[5, 4, 3], [2, 1, 0]]) 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:23,代码来源:test_cuda_ndarray.py

示例11: test_setitem_matrixscalar0

# 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_setitem_matrixscalar0():
    a = theano._asarray([[0, 1, 2], [3, 4, 5]], dtype='float32')
    _a = cuda_ndarray.CudaNdarray(a)

    b = theano._asarray(8, dtype='float32')
    _b = cuda_ndarray.CudaNdarray(b)

    # set an element to 8
    _a[1, 1] = _b
    a[1, 1] = b
    assert numpy.allclose(a, numpy.asarray(_a))

    # test direct transfert from numpy
    _a[1, 1] = theano._asarray(888, dtype='float32')
    a[1, 1] = theano._asarray(888, dtype='float32')
    assert numpy.allclose(a, numpy.asarray(_a))

    # broadcast a 0
    _a[1, 1] = 0
    _a[0:2] = 0
    _a[1:] = 0 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:23,代码来源:test_cuda_ndarray.py

示例12: test_setitem_matrixvector1

# 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_setitem_matrixvector1():
    a = theano._asarray([[0, 1, 2], [3, 4, 5]], dtype='float32')
    _a = cuda_ndarray.CudaNdarray(a)

    b = theano._asarray([8, 9], dtype='float32')
    _b = cuda_ndarray.CudaNdarray(b)

    # set second column to 8,9
    _a[:, 1] = _b
    a[:, 1] = b
    assert numpy.allclose(a, numpy.asarray(_a))

    # test direct transfert from numpy
    _a[:, 1] =  b*100
    a[:, 1] =  b*100
    assert numpy.allclose(a, numpy.asarray(_a))

    row = theano._asarray([777, 888, 999], dtype='float32')
    _a[1, :] = row
    a[1, :] = row
    assert numpy.allclose(a, numpy.asarray(_a)) 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:23,代码来源:test_cuda_ndarray.py

示例13: test_setitem_matrix_bad_shape

# 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_setitem_matrix_bad_shape():
    a = numpy.arange(27)
    a.resize((3, 3, 3))
    a = theano._asarray(a, dtype='float32')
    _a = cuda_ndarray.CudaNdarray(a)

    b = theano._asarray([7, 8], dtype='float32')
    _b = cuda_ndarray.CudaNdarray(b)

    try:
        # attempt to assign the ndarray b with setitem
        _a[:, 1, 1] = _b
        assert False
    except ValueError as e:
        # print e
        assert True

    # test direct transfert from numpy
    try:
        # attempt to assign the ndarray b with setitem
        _a[1, 1, :] = b
        assert False
    except ValueError as e:
        # print e
        assert True 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:27,代码来源:test_cuda_ndarray.py

示例14: test_setitem_matrix_bad_ndim

# 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_setitem_matrix_bad_ndim():
    a = numpy.arange(27)
    a.resize((3, 3, 3))
    a = theano._asarray(a, dtype='float32')
    _a = cuda_ndarray.CudaNdarray(a)

    b = theano._asarray([7, 8], dtype='float32')
    _b = cuda_ndarray.CudaNdarray(b)

    try:
        # attempt to assign the ndarray b with setitem
        _a[:, :, 1] = _b
        assert False
    except ValueError as e:
        # print e
        assert True

    # test direct transfert from numpy
    try:
        # attempt to assign the ndarray b with setitem
        _a[1, :, :] = b
        assert False
    except ValueError as e:
        # print e
        assert True 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:27,代码来源:test_cuda_ndarray.py

示例15: test_setitem_matrix_bad_type

# 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_setitem_matrix_bad_type():
    a = numpy.arange(27)
    a.resize((3, 3, 3))
    a = theano._asarray(a, dtype='float32')
    _a = cuda_ndarray.CudaNdarray(a)

    b = theano._asarray([7, 8], dtype='float64')

    # test direct transfert from numpy
    try:
        # attempt to assign the ndarray b with setitem
        _a[1, :, :] = b
        assert False
    except TypeError as e:
        # print e
        assert True 
开发者ID:muhanzhang,项目名称:D-VAE,代码行数:18,代码来源:test_cuda_ndarray.py


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