[PyCUDA] Install issue

Mike McFarlane

2014-11-27 16:08:52 UTC

Hi

I've installed pycuda following
http://wiki.tiker.net/PyCuda/Installation/Linux

When I try to run test/test_driver.py it fails many tests, mainly with
'TypeError: 'numpy.ndarray' does not have the buffer interface'. The output
is below for test_driver.py and the initial make.

Can anyone explain what is wrong please?

Thanks, and apologies if this mailing list isn't the right place for such
Qs.

Mike

python test_driver.py
================================================= test session starts
=================================================
platform linux2 -- Python 2.6.6 -- pytest-2.3.5
collected 23 items

test_driver.py FFF..F.F.FFFF.FFsFFF...

====================================================== FAILURES
=======================================================
___________________________________________ TestDriver.test_simple_kernel_2
___________________________________________

args = (<test_driver.TestDriver instance at 0x22ceea8>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x229bb18>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

a_gpu = drv.to_device(a)

test_driver.py:66:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

bf_obj = array([-0.4856573 , 0.45444968, 1.2984767 , -0.02761065,
0.41128042,
...0.56486648, -0.43269619, 0.55279583, -1.11403978, -0.85410458],
dtype=float32)

def to_device(bf_obj):
import sys
if sys.version_info >= (2, 7):
bf = memoryview(bf_obj).tobytes()
else:
bf = buffer(bf_obj)
result = mem_alloc(len(bf))

memcpy_htod(result, bf)

E TypeError: 'buffer' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:776:
TypeError
_______________________________________________ TestDriver.test_memory
________________________________________________

args = (<test_driver.TestDriver instance at 0x228dd88>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x23031b8>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

new_z = drv.from_device_like(drv.to_device(z), z)

test_driver.py:28:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

bf_obj = array([ -4.73744690e-01, 1.29374540e+00, -6.42129302e-01,
3.951009...1, -1.27567184e+00, 1.12105417e+00,
-6.89846277e-01], dtype=float32)

def to_device(bf_obj):
import sys
if sys.version_info >= (2, 7):
bf = memoryview(bf_obj).tobytes()
else:
bf = buffer(bf_obj)
result = mem_alloc(len(bf))

memcpy_htod(result, bf)

E TypeError: 'buffer' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:776:
TypeError
______________________________________________ TestDriver.test_gpuarray
_______________________________________________

args = (<test_driver.TestDriver instance at 0x2487b90>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x23030c8>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x2487b90>

@mark_cuda_test
def test_gpuarray(self):
a = np.arange(200000, dtype=np.float32)
b = a + 17
import pycuda.gpuarray as gpuarray

a_g = gpuarray.to_gpu(a)

test_driver.py:148:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

ary = array([ 0.00000000e+00, 1.00000000e+00, 2.00000000e+00, ...,
1.99997000e+05, 1.99998000e+05, 1.99999000e+05], dtype=float32)
allocator = <Boost.Python.function object at 0x1a8f7c0>

def to_gpu(ary, allocator=drv.mem_alloc):
"""converts a numpy array to a GPUArray"""
result = GPUArray(ary.shape, ary.dtype, allocator,
strides=ary.strides)

result.set(ary)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/gpuarray.py:913:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <[TypeError("'numpy.ndarray' does not have the buffer interface")
raised in repr()] SafeRepr object at 0x2477ea8>
ary = array([ 0.00000000e+00, 1.00000000e+00, 2.00000000e+00, ...,
1.99997000e+05, 1.99998000e+05, 1.99999000e+05], dtype=float32)

def set(self, ary):
assert ary.size == self.size
assert ary.dtype == self.dtype
if ary.strides != self.strides:
from warnings import warn
warn("Setting array from one with different strides/storage
order. "
"This will cease to work in 2013.x.",
stacklevel=2)

assert self.flags.forc

drv.memcpy_htod(self.gpudata, ary)

E TypeError: 'numpy.ndarray' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/gpuarray.py:228:
TypeError
____________________________________________ TestDriver.test_simple_kernel
____________________________________________

args = (<test_driver.TestDriver instance at 0x1e73908>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24b2488>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

block=(400, 1, 1))

test_driver.py:49:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

func = <pycuda._driver.Function object at 0x229bd70>
args = (<pycuda.driver.Out object at 0x227dcd0>, <pycuda.driver.In object
at 0x227ded0>, <pycuda.driver.In object at 0x227ddd0>)
kwargs = {}, grid = (1, 1), stream = None, block = (400, 1, 1), shared = 0,
texrefs = [], time_kernel = False
handlers = [<pycuda.driver.Out object at 0x227dcd0>, <pycuda.driver.In
object at 0x227ded0>, <pycuda.driver.In object at 0x227ddd0>]
arg_buf =
'\x00\x00!\x00\x00\x00\x00\x00\x00\x07!\x00\x00\x00\x00\x00\x00\x0e!\x00\x00\x00\x00\x00'
handler = <pycuda.driver.In object at 0x227ded0>

def function_call(func, *args, **kwargs):
grid = kwargs.pop("grid", (1, 1))
stream = kwargs.pop("stream", None)
block = kwargs.pop("block", None)
shared = kwargs.pop("shared", 0)
texrefs = kwargs.pop("texrefs", [])
time_kernel = kwargs.pop("time_kernel", False)

if kwargs:
raise ValueError(
"extra keyword arguments: %s"
% (",".join(kwargs.iterkeys())))

if block is None:
raise ValueError("must specify block size")

func._set_block_shape(*block)
handlers, arg_buf = _build_arg_buf(args)

handler.pre_call(stream)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:380:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <pycuda.driver.In object at 0x227ded0>, stream = None

def pre_call(self, stream):
if stream is not None:
memcpy_htod(self.get_device_alloc(), self.array)

memcpy_htod(self.get_device_alloc(), self.array)

E TypeError: 'numpy.ndarray' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:82:
TypeError
_______________________________________
TestDriver.test_multichannel_2d_texture
_______________________________________

args = (<test_driver.TestDriver instance at 0x2478d88>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24b2f50>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x2478d88>

@mark_cuda_test
def test_multichannel_2d_texture(self):
mod = SourceModule("""
#define CHANNELS 4
texture<float4, 2, cudaReadModeElementType> mtx_tex;

__global__ void copy_texture(float *dest)
{
int row = threadIdx.x;
int col = threadIdx.y;
int w = blockDim.y;
float4 texval = tex2D(mtx_tex, row, col);
dest[(row*w+col)*CHANNELS + 0] = texval.x;
dest[(row*w+col)*CHANNELS + 1] = texval.y;
dest[(row*w+col)*CHANNELS + 2] = texval.z;
dest[(row*w+col)*CHANNELS + 3] = texval.w;
}
""")

copy_texture = mod.get_function("copy_texture")
mtx_tex = mod.get_texref("mtx_tex")

shape = (5, 6)
channels = 4
a = np.asarray(
np.random.randn(*((channels,)+shape)),
dtype=np.float32, order="F")
drv.bind_array_to_texref(

drv.make_multichannel_2d_array(a, order="F"), mtx_tex)

test_driver.py:261:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

ndarray = array([[[-0.87390321, 0.78430617, 0.80751866, 0.0188568 ,
0.31150779,
... -1.94733143, -1.69470119, 0.88077658,
0.6898424 ]]], dtype=float32)
order = 'F'

def make_multichannel_2d_array(ndarray, order):
"""Channel count has to be the first dimension of the C{ndarray}."""

descr = ArrayDescriptor()

if order.upper() == "C":
h, w, num_channels = ndarray.shape
stride = 0
elif order.upper() == "F":
num_channels, w, h = ndarray.shape
stride = 2
else:
raise LogicError("order must be either F or C")

descr.width = w
descr.height = h
descr.format = dtype_to_array_format(ndarray.dtype)
descr.num_channels = num_channels

ary = Array(descr)

copy = Memcpy2D()

copy.set_src_host(ndarray)

E TypeError: 'numpy.ndarray' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:744:
TypeError
_____________________________________________ TestDriver.test_2d_texture
______________________________________________

args = (<test_driver.TestDriver instance at 0x2478bd8>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24b25f0>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x2478bd8>

@mark_cuda_test
def test_2d_texture(self):
mod = SourceModule("""
texture<float, 2, cudaReadModeElementType> mtx_tex;

__global__ void copy_texture(float *dest)
{
int row = threadIdx.x;
int col = threadIdx.y;
int w = blockDim.y;
dest[row*w+col] = tex2D(mtx_tex, row, col);
}
""")

copy_texture = mod.get_function("copy_texture")
mtx_tex = mod.get_texref("mtx_tex")

shape = (3, 4)
a = np.random.randn(*shape).astype(np.float32)

drv.matrix_to_texref(a, mtx_tex, order="F")

test_driver.py:188:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

matrix = array([[ 1.00075412, -1.55745828, -0.64481455, 1.14575994],
[-3.110294...],
[-2.00341797, 0.95837516, 0.69810289, -0.08028961]], dtype=float32)
texref = <pycuda._driver.TextureReference object at 0x24b0910>, order = 'F'

bind_array_to_texref(matrix_to_array(matrix, order), texref)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:764:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

matrix = array([[ 1.00075412, -1.55745828, -0.64481455, 1.14575994],
[-3.110294...],
[-2.00341797, 0.95837516, 0.69810289, -0.08028961]], dtype=float32)
order = 'F', allow_double_hack = False

def matrix_to_array(matrix, order, allow_double_hack=False):
if order.upper() == "C":
h, w = matrix.shape
stride = 0
elif order.upper() == "F":
w, h = matrix.shape
stride = -1
else:
raise LogicError("order must be either F or C")

matrix = np.asarray(matrix, order=order)
descr = ArrayDescriptor()

descr.width = w
descr.height = h

if matrix.dtype == np.float64 and allow_double_hack:
descr.format = array_format.SIGNED_INT32
descr.num_channels = 2
else:
descr.format = dtype_to_array_format(matrix.dtype)
descr.num_channels = 1

ary = Array(descr)

copy = Memcpy2D()

copy.set_src_host(matrix)

E TypeError: 'numpy.ndarray' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:712:
TypeError
_____________________________________________ TestDriver.test_fp_textures
_____________________________________________

args = (<test_driver.TestDriver instance at 0x2582b00>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24b2500>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x2582b00>

@mark_cuda_test
def test_fp_textures(self):
if drv.Context.get_device().compute_capability() < (1, 3):
return

for tp in [np.float32, np.float64]:
from pycuda.tools import dtype_to_ctype

tp_cstr = dtype_to_ctype(tp)
mod = SourceModule("""
#include <pycuda-helpers.hpp>

texture<fp_tex_%(tp)s, 1, cudaReadModeElementType> my_tex;

__global__ void copy_texture(%(tp)s *dest)
{
int i = threadIdx.x;
dest[i] = fp_tex1Dfetch(my_tex, i);
}
""" % {"tp": tp_cstr})

copy_texture = mod.get_function("copy_texture")
my_tex = mod.get_texref("my_tex")

import pycuda.gpuarray as gpuarray

shape = (384,)
a = np.random.randn(*shape).astype(tp)

a_gpu = gpuarray.to_gpu(a)

test_driver.py:522:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

ary = array([ 4.60776985e-01, 7.17113495e-01, 1.01722872e+00,
-1.146432...1,
2.04511788e-02, 1.11698084e-01, -2.13677096e+00], dtype=float32)
allocator = <Boost.Python.function object at 0x1a8f7c0>

def to_gpu(ary, allocator=drv.mem_alloc):
"""converts a numpy array to a GPUArray"""
result = GPUArray(ary.shape, ary.dtype, allocator,
strides=ary.strides)

result.set(ary)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/gpuarray.py:913:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <[TypeError("'numpy.ndarray' does not have the buffer interface")
raised in repr()] SafeRepr object at 0x2300dd0>
ary = array([ 4.60776985e-01, 7.17113495e-01, 1.01722872e+00,
-1.146432...1,
2.04511788e-02, 1.11698084e-01, -2.13677096e+00], dtype=float32)

def set(self, ary):
assert ary.size == self.size
assert ary.dtype == self.dtype
if ary.strides != self.strides:
from warnings import warn
warn("Setting array from one with different strides/storage
order. "
"This will cease to work in 2013.x.",
stacklevel=2)

assert self.flags.forc

drv.memcpy_htod(self.gpudata, ary)

E TypeError: 'numpy.ndarray' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/gpuarray.py:228:
TypeError
____________________________________________ TestDriver.test_vector_types
_____________________________________________

args = (<test_driver.TestDriver instance at 0x25a02d8>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24b29b0>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

set_them(drv.Out(dest), a, block=(400,1,1))

test_driver.py:98:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

func = <pycuda._driver.Function object at 0x24b27d0>
args = (<pycuda.driver.Out object at 0x1e6fcd0>, array((1.0, 2.0, 3.0),
dtype=[('x', '<f4'), ('y', '<f4'), ('z', '<f4')]))
kwargs = {}, grid = (1, 1), stream = None, block = (400, 1, 1), shared = 0,
texrefs = [], time_kernel = False
handlers = [<pycuda.driver.Out object at 0x1e6fcd0>]
arg_buf = '\x00\x00!\x00\x00\x00\x00\x00\x00\x00\x80?\x00\x00\x00@\x00\x00@
@'
handler = <pycuda.driver.Out object at 0x1e6fcd0>

def function_call(func, *args, **kwargs):
grid = kwargs.pop("grid", (1, 1))
stream = kwargs.pop("stream", None)
block = kwargs.pop("block", None)
shared = kwargs.pop("shared", 0)
texrefs = kwargs.pop("texrefs", [])
time_kernel = kwargs.pop("time_kernel", False)

if kwargs:
raise ValueError(
"extra keyword arguments: %s"
% (",".join(kwargs.iterkeys())))

if block is None:
raise ValueError("must specify block size")

func._set_block_shape(*block)
handlers, arg_buf = _build_arg_buf(args)

for handler in handlers:
handler.pre_call(stream)

for texref in texrefs:
func.param_set_texref(texref)

post_handlers = [handler
for handler in handlers
if hasattr(handler, "post_call")]

if stream is None:
if time_kernel:
Context.synchronize()

from time import time
start_time = time()

func._launch_kernel(grid, block, arg_buf, shared, None)

if post_handlers or time_kernel:
Context.synchronize()

if time_kernel:
run_time = time()-start_time

handler.post_call(stream)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:405:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <pycuda.driver.Out object at 0x1e6fcd0>, stream = None

def post_call(self, stream):
if stream is not None:
memcpy_dtoh(self.array, self.get_device_alloc())

memcpy_dtoh(self.array, self.get_device_alloc())

E TypeError: 'numpy.ndarray' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:90:
TypeError
________________________________________
TestDriver.test_multiple_2d_textures
_________________________________________

args = (<test_driver.TestDriver instance at 0x280f950>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24b2e60>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x280f950>

@mark_cuda_test
def test_multiple_2d_textures(self):
mod = SourceModule("""
texture<float, 2, cudaReadModeElementType> mtx_tex;
texture<float, 2, cudaReadModeElementType> mtx2_tex;

__global__ void copy_texture(float *dest)
{
int row = threadIdx.x;
int col = threadIdx.y;
int w = blockDim.y;
dest[row*w+col] =
tex2D(mtx_tex, row, col)
+
tex2D(mtx2_tex, row, col);
}
""")

copy_texture = mod.get_function("copy_texture")
mtx_tex = mod.get_texref("mtx_tex")
mtx2_tex = mod.get_texref("mtx2_tex")

shape = (3,4)
a = np.random.randn(*shape).astype(np.float32)
b = np.random.randn(*shape).astype(np.float32)

drv.matrix_to_texref(a, mtx_tex, order="F")

test_driver.py:223:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

matrix = array([[-0.60509264, -0.69680727, -1.962533 , 0.67714691],
[-1.094154...],
[ 0.40417606, -0.97287714, 0.10696917, -1.54577947]], dtype=float32)
texref = <pycuda._driver.TextureReference object at 0x24b0d00>, order = 'F'

bind_array_to_texref(matrix_to_array(matrix, order), texref)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:764:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

matrix = array([[-0.60509264, -0.69680727, -1.962533 , 0.67714691],
[-1.094154...],
[ 0.40417606, -0.97287714, 0.10696917, -1.54577947]], dtype=float32)
order = 'F', allow_double_hack = False

def matrix_to_array(matrix, order, allow_double_hack=False):
if order.upper() == "C":
h, w = matrix.shape
stride = 0
elif order.upper() == "F":
w, h = matrix.shape
stride = -1
else:
raise LogicError("order must be either F or C")

matrix = np.asarray(matrix, order=order)
descr = ArrayDescriptor()

descr.width = w
descr.height = h

if matrix.dtype == np.float64 and allow_double_hack:
descr.format = array_format.SIGNED_INT32
descr.num_channels = 2
else:
descr.format = dtype_to_array_format(matrix.dtype)
descr.num_channels = 1

ary = Array(descr)

copy = Memcpy2D()

copy.set_src_host(matrix)

E TypeError: 'numpy.ndarray' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:712:
TypeError
___________________________________________ TestDriver.test_streamed_kernel
___________________________________________

args = (<test_driver.TestDriver instance at 0x23007e8>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24b2e60>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x23007e8>

@mark_cuda_test
def test_streamed_kernel(self):
# this differs from the "simple_kernel" case in that *all*
computation
# and data copying is asynchronous. Observe how this necessitates
the
# use of page-locked memory.

mod = SourceModule("""
__global__ void multiply_them(float *dest, float *a, float *b)
{
const int i = threadIdx.x*blockDim.y + threadIdx.y;
dest[i] = a[i] * b[i];
}
""")

multiply_them = mod.get_function("multiply_them")

shape = (32, 8)
a = drv.pagelocked_zeros(shape, dtype=np.float32)
b = drv.pagelocked_zeros(shape, dtype=np.float32)
a[:] = np.random.randn(*shape)
b[:] = np.random.randn(*shape)

a_gpu = drv.mem_alloc(a.nbytes)
b_gpu = drv.mem_alloc(b.nbytes)

strm = drv.Stream()

drv.memcpy_htod_async(a_gpu, a, strm)

E TypeError: 'numpy.ndarray' does not have the buffer interface

test_driver.py:127: TypeError
_________________________________________
TestDriver.test_prepared_invocation
_________________________________________

args = (<test_driver.TestDriver instance at 0x24951b8>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24a20c8>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

drv.memcpy_htod(a_gpu, a)

E TypeError: 'numpy.ndarray' does not have the buffer interface

test_driver.py:450: TypeError
___________________________________________ TestDriver.test_constant_memory
___________________________________________

args = (<test_driver.TestDriver instance at 0x24963f8>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24a2500>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x24963f8>

@mark_cuda_test
def test_constant_memory(self):
# contributed by Andrew Wagner

module = SourceModule("""
__constant__ float const_array[32];

__global__ void copy_constant_into_global(float*
global_result_array)
{
global_result_array[threadIdx.x] = const_array[threadIdx.x];
}
""")

copy_constant_into_global =
module.get_function("copy_constant_into_global")
const_array, _ = module.get_global('const_array')

host_array = np.random.randint(0,255,(32,)).astype(np.float32)

global_result_array = drv.mem_alloc_like(host_array)

drv.memcpy_htod(const_array, host_array)

E TypeError: 'numpy.ndarray' does not have the buffer interface

test_driver.py:551: TypeError
_____________________________________
TestDriver.test_multichannel_linear_texture
_____________________________________

args = (<test_driver.TestDriver instance at 0x1e61cb0>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24a2398>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/tools.py:453:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

self = <test_driver.TestDriver instance at 0x1e61cb0>

@mark_cuda_test
def test_multichannel_linear_texture(self):
mod = SourceModule("""
#define CHANNELS 4
texture<float4, 1, cudaReadModeElementType> mtx_tex;

__global__ void copy_texture(float *dest)
{
int i = threadIdx.x+blockDim.x*threadIdx.y;
float4 texval = tex1Dfetch(mtx_tex, i);
dest[i*CHANNELS + 0] = texval.x;
dest[i*CHANNELS + 1] = texval.y;
dest[i*CHANNELS + 2] = texval.z;
dest[i*CHANNELS + 3] = texval.w;
}
""")

copy_texture = mod.get_function("copy_texture")
mtx_tex = mod.get_texref("mtx_tex")

shape = (16, 16)
channels = 4
a = np.random.randn(*(shape+(channels,))).astype(np.float32)

a_gpu = drv.to_device(a)

test_driver.py:297:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

bf_obj = array([[[ 0.06351238, -1.50826311, 0.99232352, -0.19848856],
[ 0.1630...
[-0.59885794, 0.58485585, 0.93704814, 0.02101008]]],
dtype=float32)

def to_device(bf_obj):
import sys
if sys.version_info >= (2, 7):
bf = memoryview(bf_obj).tobytes()
else:
bf = buffer(bf_obj)
result = mem_alloc(len(bf))

memcpy_htod(result, bf)

E TypeError: 'buffer' does not have the buffer interface

/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/driver.py:776:
TypeError
_____________________________________________ TestDriver.test_3d_texture
______________________________________________

args = (<test_driver.TestDriver instance at 0x2585ea8>,), kwargs = {}
pycuda = <module 'pycuda' from
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg/pycuda/__init__.pyc'>
ctx = <pycuda._driver.Context object at 0x24a2848>, clear_context_caches =
<function clear_context_caches at 0x1af6ed8>
collect = <built-in function collect>

def f(*args, **kwargs):
import pycuda.driver
# appears to be idempotent, i.e. no harm in calling it more than
once
pycuda.driver.init()

ctx = make_default_context()
try:
assert isinstance(ctx.get_device().name(), str)
assert isinstance(ctx.get_device().compute_capability(), tuple)
assert isinstance(ctx.get_device().get_attributes(), dict)

inner_f(*args, **kwargs)

copy.set_src_host(a)

E TypeError: 'numpy.ndarray' does not have the buffer interface

test_driver.py:412: TypeError
=================================== 14 failed, 8 passed, 1 skipped in 13.38
seconds ===================================
--
------------------------- make output -----------------

*** WARNING: nvcc not in path.
running install
running bdist_egg
running egg_info
writing requirements to pycuda.egg-info/requires.txt
writing pycuda.egg-info/PKG-INFO
writing top-level names to pycuda.egg-info/top_level.txt
writing dependency_links to pycuda.egg-info/dependency_links.txt
reading manifest file 'pycuda.egg-info/SOURCES.txt'
reading manifest template 'MANIFEST.in'
warning: no files found matching '*.cpp' under directory
'bpl-subset/bpl_subset/boost'
warning: no files found matching '*.html' under directory
'bpl-subset/bpl_subset/boost'
warning: no files found matching '*.inl' under directory
'bpl-subset/bpl_subset/boost'
warning: no files found matching '*.txt' under directory
'bpl-subset/bpl_subset/boost'
warning: no files found matching '*.h' under directory
'bpl-subset/bpl_subset/libs'
warning: no files found matching '*.ipp' under directory
'bpl-subset/bpl_subset/libs'
warning: no files found matching '*.pl' under directory
'bpl-subset/bpl_subset/libs'
writing manifest file 'pycuda.egg-info/SOURCES.txt'
installing library code to build/bdist.linux-x86_64/egg
running install_lib
running build_py
running build_ext
creating build/bdist.linux-x86_64/egg
creating build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/autoinit.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/compiler.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/tools.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/__init__.py ->
build/bdist.linux-x86_64/egg/pycuda
creating build/bdist.linux-x86_64/egg/pycuda/compyte
copying build/lib.linux-x86_64-2.6/pycuda/compyte/__init__.py ->
build/bdist.linux-x86_64/egg/pycuda/compyte
copying build/lib.linux-x86_64-2.6/pycuda/compyte/array.py ->
build/bdist.linux-x86_64/egg/pycuda/compyte
copying build/lib.linux-x86_64-2.6/pycuda/compyte/dtypes.py ->
build/bdist.linux-x86_64/egg/pycuda/compyte
copying build/lib.linux-x86_64-2.6/pycuda/gpuarray.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/_mymako.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/debug.py ->
build/bdist.linux-x86_64/egg/pycuda
creating build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/sparse/__init__.py ->
build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/sparse/pkt_build.py ->
build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/sparse/cg.py ->
build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/sparse/packeted.py ->
build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/sparse/coordinate.py ->
build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/sparse/operator.py ->
build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/sparse/inner.py ->
build/bdist.linux-x86_64/egg/pycuda/sparse
copying build/lib.linux-x86_64-2.6/pycuda/_pvt_struct.so ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/cumath.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/_cluda.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/characterize.py ->
build/bdist.linux-x86_64/egg/pycuda
creating build/bdist.linux-x86_64/egg/pycuda/cuda
copying build/lib.linux-x86_64-2.6/pycuda/cuda/pycuda-complex.hpp ->
build/bdist.linux-x86_64/egg/pycuda/cuda
copying build/lib.linux-x86_64-2.6/pycuda/cuda/pycuda-complex-impl.hpp ->
build/bdist.linux-x86_64/egg/pycuda/cuda
copying build/lib.linux-x86_64-2.6/pycuda/cuda/pycuda-helpers.hpp ->
build/bdist.linux-x86_64/egg/pycuda/cuda
copying build/lib.linux-x86_64-2.6/pycuda/reduction.py ->
build/bdist.linux-x86_64/egg/pycuda
creating build/bdist.linux-x86_64/egg/pycuda/gl
copying build/lib.linux-x86_64-2.6/pycuda/gl/autoinit.py ->
build/bdist.linux-x86_64/egg/pycuda/gl
copying build/lib.linux-x86_64-2.6/pycuda/gl/__init__.py ->
build/bdist.linux-x86_64/egg/pycuda/gl
copying build/lib.linux-x86_64-2.6/pycuda/driver.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/curandom.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/elementwise.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/scan.py ->
build/bdist.linux-x86_64/egg/pycuda
copying build/lib.linux-x86_64-2.6/pycuda/_driver.so ->
build/bdist.linux-x86_64/egg/pycuda
byte-compiling build/bdist.linux-x86_64/egg/pycuda/autoinit.py to
autoinit.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/compiler.py to
compiler.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/tools.py to tools.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/__init__.py to
__init__.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/compyte/__init__.py to
__init__.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/compyte/array.py to
array.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/compyte/dtypes.py to
dtypes.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/gpuarray.py to
gpuarray.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/_mymako.py to _mymako.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/debug.py to debug.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/sparse/__init__.py to
__init__.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/sparse/pkt_build.py to
pkt_build.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/sparse/cg.py to cg.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/sparse/packeted.py to
packeted.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/sparse/coordinate.py to
coordinate.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/sparse/operator.py to
operator.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/sparse/inner.py to
inner.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/cumath.py to cumath.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/_cluda.py to _cluda.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/characterize.py to
characterize.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/reduction.py to
reduction.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/gl/autoinit.py to
autoinit.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/gl/__init__.py to
__init__.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/driver.py to driver.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/curandom.py to
curandom.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/elementwise.py to
elementwise.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/scan.py to scan.pyc
creating stub loader for pycuda/_driver.so
creating stub loader for pycuda/_pvt_struct.so
byte-compiling build/bdist.linux-x86_64/egg/pycuda/_driver.py to _driver.pyc
byte-compiling build/bdist.linux-x86_64/egg/pycuda/_pvt_struct.py to
_pvt_struct.pyc
creating build/bdist.linux-x86_64/egg/EGG-INFO
copying pycuda.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO
copying pycuda.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
copying pycuda.egg-info/dependency_links.txt ->
build/bdist.linux-x86_64/egg/EGG-INFO
copying pycuda.egg-info/not-zip-safe ->
build/bdist.linux-x86_64/egg/EGG-INFO
copying pycuda.egg-info/requires.txt ->
build/bdist.linux-x86_64/egg/EGG-INFO
copying pycuda.egg-info/top_level.txt ->
build/bdist.linux-x86_64/egg/EGG-INFO
writing build/bdist.linux-x86_64/egg/EGG-INFO/native_libs.txt
creating 'dist/pycuda-2014.1-py2.6-linux-x86_64.egg' and adding
'build/bdist.linux-x86_64/egg' to it
removing 'build/bdist.linux-x86_64/egg' (and everything under it)
Processing pycuda-2014.1-py2.6-linux-x86_64.egg
removing
'/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg'
(and everything under it)
creating
/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg
Extracting pycuda-2014.1-py2.6-linux-x86_64.egg to
/usr/lib64/python2.6/site-packages
pycuda 2014.1 is already the active version in easy-install.pth

Installed
/usr/lib64/python2.6/site-packages/pycuda-2014.1-py2.6-linux-x86_64.egg
Processing dependencies for pycuda==2014.1
Searching for decorator==3.4.0
Best match: decorator 3.4.0
Processing decorator-3.4.0-py2.6.egg
decorator 3.4.0 is already the active version in easy-install.pth

Using /usr/lib64/python2.6/site-packages/decorator-3.4.0-py2.6.egg
Searching for pytest==2.3.5
Best match: pytest 2.3.5
Adding pytest 2.3.5 to easy-install.pth file
Installing py.test script to /usr/bin
Installing py.test-2.6 script to /usr/bin

Using /usr/lib/python2.6/site-packages
Searching for pytools==2014.3.4
Best match: pytools 2014.3.4
Processing pytools-2014.3.4-py2.6.egg
pytools 2014.3.4 is already the active version in easy-install.pth

Using /usr/lib64/python2.6/site-packages/pytools-2014.3.4-py2.6.egg
Searching for py==1.4.18
Best match: py 1.4.18
Adding py 1.4.18 to easy-install.pth file

Using /usr/lib/python2.6/site-packages
Searching for appdirs==1.4.0
Best match: appdirs 1.4.0
Processing appdirs-1.4.0-py2.6.egg
appdirs 1.4.0 is already the active version in easy-install.pth

Using /usr/lib64/python2.6/site-packages/appdirs-1.4.0-py2.6.egg
Finished processing dependencies for pycuda==2014.1

******************************************************************************************

*Mike McFarlane*

***@iproov.com

+44 7557 780175

******************************************************************************************