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interop.py
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139 lines (117 loc) · 3.68 KB
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#!/usr/bin/python
#######################################################
# Copyright (c) 2015, ArrayFire
# All rights reserved.
#
# This file is distributed under 3-clause BSD license.
# The complete license agreement can be obtained at:
# http://arrayfire.com/licenses/BSD-3-Clause
########################################################
import arrayfire as af
from . import _util
def simple_interop(verbose = False):
if af.AF_NUMPY_FOUND:
import numpy as np
n = np.random.random((5,))
a = af.to_array(n)
n2 = np.array(a)
assert((n==n2).all())
n2[:] = 0
a.to_ndarray(n2)
assert((n==n2).all())
n = np.random.random((5,3))
a = af.to_array(n)
n2 = np.array(a)
assert((n==n2).all())
n2[:] = 0
a.to_ndarray(n2)
assert((n==n2).all())
n = np.random.random((5,3,2))
a = af.to_array(n)
n2 = np.array(a)
assert((n==n2).all())
n2[:] = 0
a.to_ndarray(n2)
assert((n==n2).all())
n = np.random.random((5,3,2,2))
a = af.to_array(n)
n2 = np.array(a)
assert((n==n2).all())
n2[:] = 0
a.to_ndarray(n2)
assert((n==n2).all())
if af.AF_PYCUDA_FOUND and af.get_active_backend() == 'cuda':
import pycuda.autoinit
import pycuda.gpuarray as cudaArray
n = np.random.random((5,))
c = cudaArray.to_gpu(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
n = np.random.random((5,3))
c = cudaArray.to_gpu(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
n = np.random.random((5,3,2))
c = cudaArray.to_gpu(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
n = np.random.random((5,3,2,2))
c = cudaArray.to_gpu(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
if af.AF_PYOPENCL_FOUND and af.backend.name() == 'opencl':
# This needs fixing upstream
# https://github.com/arrayfire/arrayfire/issues/1728
# import pyopencl as cl
# import pyopencl.array as clArray
# ctx = cl.create_some_context()
# queue = cl.CommandQueue(ctx)
# n = np.random.random((5,))
# c = cl.array.to_device(queue, n)
# a = af.to_array(c)
# n2 = np.array(a)
# assert((n==n2).all())
# n = np.random.random((5,3))
# c = cl.array.to_device(queue, n)
# a = af.to_array(c)
# n2 = np.array(a)
# assert((n==n2).all())
# n = np.random.random((5,3,2))
# c = cl.array.to_device(queue, n)
# a = af.to_array(c)
# n2 = np.array(a)
# assert((n==n2).all())
# n = np.random.random((5,3,2,2))
# c = cl.array.to_device(queue, n)
# a = af.to_array(c)
# n2 = np.array(a)
# assert((n==n2).all())
pass
if af.AF_NUMBA_FOUND and af.get_active_backend() == 'cuda':
import numba
from numba import cuda
n = np.random.random((5,))
c = cuda.to_device(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
n = np.random.random((5,3))
c = cuda.to_device(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
n = np.random.random((5,3,2))
c = cuda.to_device(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
n = np.random.random((5,3,2,2))
c = cuda.to_device(n)
a = af.to_array(c)
n2 = np.array(a)
assert((n==n2).all())
_util.tests['interop'] = simple_interop