来自 numpy 数组的 PyopenCL 3D RGBA 图像

PyopenCL 3D RGBA image from numpy array

我想使用 pyopencl 从 numpy 数组构建 OpenCL 3D RGBA 图像。我知道 cl.image_from_array() 函数,它基本上就是这样做的,但不对 cl.enqueue_copy() 公开的命令队列或事件提供任何控制。所以我真的很想使用后一个函数,将 3D RGBA 图像从主机传输到设备,但我似乎无法正确获取图像构造函数的语法。

所以在这个环境下

import pyopencl as cl
import numpy as np

platform = cl.get_platforms()[0]
devs = platform.get_devices()
device1 = devs[1]
mf = cl.mem_flags
ctx = cl.Context([device1])
Queue1=cl.CommandQueue(ctx,properties=cl.command_queue_properties.PROFILING_ENABLE)

我想做一些类似于

的事情
  d_colortest = cl.image_from_array(ctx,np.zeros((256,256,256,4)).astype(np.float32),num_channels=4,mode='w')

使用函数

d_image = cl.Image(...)
event = cl.enqueue_copy(...)

我调整了 cl.image_from_array() 函数以能够 return 事件,这基本上很简单:

def p_Array(queue_s, name, ary, num_channels=4, mode="w", norm_int=False,copy=True):
    q = eval(queue_s)
    if not ary.flags.c_contiguous:
        raise ValueError("array must be C-contiguous")

    dtype = ary.dtype
    if num_channels is None:

        from pyopencl.array import vec
        try:
            dtype, num_channels = vec.type_to_scalar_and_count[dtype]
        except KeyError:
            # It must be a scalar type then.
            num_channels = 1

        shape = ary.shape
        strides = ary.strides

    elif num_channels == 1:
        shape = ary.shape
        strides = ary.strides
    else:
        if ary.shape[-1] != num_channels:
            raise RuntimeError("last dimension must be equal to number of channels")

        shape = ary.shape[:-1]
        strides = ary.strides[:-1]

    if mode == "r":
        mode_flags = cl.mem_flags.READ_ONLY
    elif mode == "w":
        mode_flags = cl.mem_flags.WRITE_ONLY
    else:
        raise ValueError("invalid value '%s' for 'mode'" % mode)

    img_format = {
            1: cl.channel_order.R,
            2: cl.channel_order.RG,
            3: cl.channel_order.RGB,
            4: cl.channel_order.RGBA,
            }[num_channels]

    assert ary.strides[-1] == ary.dtype.itemsize

    if norm_int:
        channel_type = cl.DTYPE_TO_CHANNEL_TYPE_NORM[dtype]
    else:
        channel_type = cl.DTYPE_TO_CHANNEL_TYPE[dtype]

    d_image = cl.Image(ctx, mode_flags,
            cl.ImageFormat(img_format, channel_type),
            shape=shape[::-1])
    if copy:
        event = cl.enqueue_copy(q,d_image,ary,origin=(0,0,0),region=shape[::-1])
        event_list.append((event,queue_s,name))
    return d_image, event