#include "mini_blas.h"

//From Berkeley Vision's Caffe!
//https://github.com/BVLC/caffe/blob/master/LICENSE
void im2col_cpu(float* data_im,
    const int batch, const int channels, const int height, const int width,
    const int ksize, const int stride, float* data_col) 
{
    int c,h,w,b;
    int height_col = (height - ksize) / stride + 1;
    int width_col = (width - ksize) / stride + 1;
    int channels_col = channels * ksize * ksize;
    int im_size = height*width*channels;
    int col_size = height_col*width_col*channels_col;
    for(b = 0; b < batch; ++b){
        for ( c = 0; c < channels_col; ++c) {
            int w_offset = c % ksize;
            int h_offset = (c / ksize) % ksize;
            int c_im = c / ksize / ksize;
            for ( h = 0; h < height_col; ++h) {
                for ( w = 0; w < width_col; ++w) {
                    data_col[(c * height_col + h) * width_col + w] =
                    data_im[(c_im * height + h * stride + h_offset) * width
                        + w * stride + w_offset];
                }
            }
        }
        data_im += im_size;
        data_col+= col_size;
    }
}


#ifdef GPU

#include "opencl.h"
#include <math.h>

cl_kernel get_im2col_kernel()
{
    static int init = 0;
    static cl_kernel im2col_kernel;
    if(!init){
        im2col_kernel = get_kernel("src/im2col.cl", "im2col", 0);
        init = 1;
    }
    return im2col_kernel;
}


void im2col_ongpu(cl_mem data_im, const int batch,
        const int channels, const int height, const int width,
        const int ksize, const int stride, cl_mem data_col) 
{
    cl_setup();
    cl_kernel im2col_kernel = get_im2col_kernel();
    cl_command_queue queue = cl.queue;

    cl_uint i = 0;
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(data_im), (void*) &data_im);
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(batch), (void*) &batch);
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(channels), (void*) &channels);
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(height), (void*) &height);
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(width), (void*) &width);
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(ksize), (void*) &ksize);
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(stride), (void*) &stride);
    cl.error = clSetKernelArg(im2col_kernel, i++, sizeof(data_col), (void*) &data_col);
    check_error(cl);

    int height_col = (height - ksize) / stride + 1;
    int width_col = (width - ksize) / stride + 1;
    int channels_col = channels * ksize * ksize;

    size_t global_size[2];
    size_t local_size[2];
    global_size[0] = batch;
    global_size[1] = channels_col;
    local_size[0] = height_col;
    local_size[1] = width_col;

    clEnqueueNDRangeKernel(queue, im2col_kernel, 2, 0,
            global_size, local_size, 0, 0, 0);
    check_error(cl);
}

void im2col_gpu(float *data_im,
        const int batch, const int channels, const int height, const int width,
        const int ksize, const int stride,
        float *data_col) 
{
    cl_setup();
    cl_context context = cl.context;
    cl_command_queue queue = cl.queue;

    size_t size = sizeof(float)*(channels*height*width*batch);
    cl_mem im_gpu = clCreateBuffer(context,
            CL_MEM_READ_ONLY|CL_MEM_COPY_HOST_PTR,
            size, data_im, &cl.error);
    check_error(cl);

    int height_col = (height - ksize) / stride + 1;
    int width_col = (width - ksize) / stride + 1;
    int channels_col = channels * ksize * ksize;

    size = sizeof(float)*(height_col*width_col*channels_col*batch);
    cl_mem col_gpu = clCreateBuffer(context,
            CL_MEM_WRITE_ONLY|CL_MEM_COPY_HOST_PTR,
            size, data_col, &cl.error);
    check_error(cl);

    im2col_ongpu(im_gpu, batch, channels, height, width,
            ksize, stride, col_gpu);

    clEnqueueReadBuffer(queue, col_gpu, CL_TRUE, 0, size, data_col, 0, 0, 0);
    check_error(cl);

    clReleaseMemObject(col_gpu);
    clReleaseMemObject(im_gpu);
}

#endif