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Modify Array.get() to cope with non-contiguous / padded arrays in 2 and 3 dimensions #54

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Modify Array.get() to cope with non-contiguous / padded arrays in 2 and 3 dimensions #54

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2bc4f3e
Implement Array.get for non-contiguous device arrays in two and three…
tsmithe Jun 27, 2014
4ac34d8
Clean up
tsmithe Jun 28, 2014
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65 changes: 59 additions & 6 deletions pyopencl/array.py
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Original file line number Diff line number Diff line change
Expand Up @@ -648,22 +648,75 @@ def get(self, queue=None, ary=None, async=False):
size (not necessarily shape) and dtype.
"""

if not self.size:
return ary or np.empty(self.shape, self.dtype)

index = 0
order = None
prev_stride = None
new_strides = []
for stride in self.strides:
if prev_stride:
if not order and stride > prev_stride:
order = 'F'
elif not order and stride < prev_stride:
order = 'C'
elif ((order == 'F' and stride < prev_stride) or
(order == 'C' and stride > prev_stride)):
raise TypeError(
"Array must have row- or column-major layout")
new_strides = map(lambda x: x * self.shape[index], new_strides)
new_strides.append(1)
prev_stride = stride
index += 1
if not order: order = 'C'
new_strides = map(lambda x: x * self.dtype.itemsize, new_strides)
new_strides = list(new_strides)

element_strides = list(map(lambda x: int(x / self.dtype.itemsize),
self.strides))

if order == 'F':
new_strides.reverse()
element_strides.reverse()

if ary is None:
ary = np.empty(self.shape, self.dtype)

ary = _as_strided(ary, strides=self.strides)
if self.flags.forc:
ary = _as_strided(ary, strides=self.strides)
cl.enqueue_copy(queue or self.queue, ary, self.base_data,
device_offset=self.offset,
is_blocking=not async)
return ary

ary = _as_strided(ary, strides = new_strides)

else:
if ary.size != self.size:
raise TypeError("'ary' has non-matching size")
if ary.dtype != self.dtype:
raise TypeError("'ary' has non-matching type")

assert self.flags.forc, "Array in get() must be contiguous"
region = list(self.shape)
region[0] *= self.dtype.itemsize

if self.size:
cl.enqueue_copy(queue or self.queue, ary, self.base_data,
device_offset=self.offset,
is_blocking=not async)
if len(self.shape) == 2:
row_pitch = element_strides[0] * element_strides[1] * self.dtype.itemsize
slice_pitch = 1
elif len(self.shape) == 3:
row_pitch = element_strides[-1] * element_strides[-2] * self.dtype.itemsize
slice_pitch = row_pitch * self.shape[0]
else:
raise TypeError(
"Only 2- or 3-D non-contiguous arrays are currently supported")

cl.enqueue_copy(queue or self.queue, ary, self.base_data,
buffer_origin=(self.offset, 0, 0),
host_origin=(0, 0, 0),
region=tuple(region),
buffer_pitches=(row_pitch, slice_pitch),
host_pitches=(0,0))

return ary

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