Python gpu_from_cuda Examples

Example #1

def test_transfer_cuda_gpu():
    import theano.sandbox.cuda as cuda_ndarray
    if cuda_ndarray.cuda_available == False:
        raise SkipTest("Can't test interaction with cuda if cuda not present")
    g = GpuArrayType(dtype='float32', broadcastable=(False, False))('g')
    c = cuda_ndarray.CudaNdarrayType((False, False))('c')

    av = theano._asarray(rng.rand(5, 4), dtype='float32')
    gv = gpuarray.array(av)
    cv = cuda_ndarray.CudaNdarray(av)
    gvs = gv[:, ::-2]
    cvs = cv[:, ::-2]

    f = theano.function([c], gpu_from_cuda(c))
    fv = f(cv)
    assert GpuArrayType.values_eq_approx(fv, gv)

    fvs = f(cvs)
    assert GpuArrayType.values_eq_approx(fvs, gvs)

    f = theano.function([g], cuda_from_gpu(g))
    fv = f(gv)
    assert cuda_ndarray.CudaNdarrayType.values_eq_approx(fv, cv)

    fvs = f(gvs)
    assert cuda_ndarray.CudaNdarrayType.values_eq_approx(fvs, cvs)

Example #2

File: test_basic_ops.py Project: alexsavio/Theano

def test_transfer_cuda_gpu():
    import theano.sandbox.cuda as cuda_ndarray
    if cuda_ndarray.cuda_available == False:
        raise SkipTest("Can't test interaction with cuda if cuda not present")
    g = GpuArrayType(dtype='float32', broadcastable=(False, False))('g')
    c = cuda_ndarray.CudaNdarrayType((False, False))('c')

    av = theano._asarray(rng.rand(5, 4), dtype='float32')
    gv = gpuarray.array(av)
    cv = cuda_ndarray.CudaNdarray(av)
    gvs = gv[:,::-2]
    cvs = cv[:,::-2]

    f = theano.function([c], gpu_from_cuda(c))
    fv = f(cv)
    assert GpuArrayType.values_eq_approx(fv, gv)

    fvs = f(cvs)
    assert GpuArrayType.values_eq_approx(fvs, gvs)

    f = theano.function([g], cuda_from_gpu(g))
    fv = f(gv)
    assert cuda_ndarray.CudaNdarrayType.values_eq_approx(fv, cv)

    fvs = f(gvs)
    assert cuda_ndarray.CudaNdarrayType.values_eq_approx(fvs, cvs)