如何使用PyOpenCl向内核传递参数

import pyopencl as cl
import numpy as np

platform = cl.get_platforms()[0]
device = platform.get_devices()[0]
context = cl.Context([device])
queue = cl.CommandQueue(context)

input_data = np.array([1, 2, 3, 4, 5], dtype=np.float32)
output_data = np.empty_like(input_data)

input_buffer = cl.Buffer(context, cl.mem_flags.READ_ONLY | cl.mem_flags.COPY_HOST_PTR, hostbuf=input_data)
output_buffer = cl.Buffer(context, cl.mem_flags.WRITE_ONLY, size=output_data.nbytes)

kernel_code = """
__kernel void add_numbers(__global const float* input, __global float* output) {
    int i = get_global_id(0);
    output[i] = input[i] + 10;
}
"""

program = cl.Program(context, kernel_code).build()

program.add_numbers(queue, input_data.shape, None, input_buffer, output_buffer)

cl.enqueue_copy(queue, output_data, output_buffer)

import pyopencl as cl
import numpy as np

# 创建上下文和命令队列
platform = cl.get_platforms()[0]
device = platform.get_devices()[0]
context = cl.Context([device])
queue = cl.CommandQueue(context)

# 创建输入和输出缓冲区
input_data = np.array([1, 2, 3, 4, 5], dtype=np.float32)
output_data = np.empty_like(input_data)

input_buffer = cl.Buffer(context, cl.mem_flags.READ_ONLY | cl.mem_flags.COPY_HOST_PTR, hostbuf=input_data)
output_buffer = cl.Buffer(context, cl.mem_flags.WRITE_ONLY, size=output_data.nbytes)

# 编写内核代码
kernel_code = """
__kernel void add_numbers(__global const float* input, __global float* output) {
    int i = get_global_id(0);
    output[i] = input[i] + 10;
}
"""

# 创建并构建内核程序
program = cl.Program(context, kernel_code).build()

# 设置内核参数并执行内核
program.add_numbers(queue, input_data.shape, None, input_buffer, output_buffer)

# 从输出缓冲区中读取结果
cl.enqueue_copy(queue, output_data, output_buffer)

print("Input:", input_data)
print("Output:", output_data)