gaussian.c

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/*
    This file is part of darktable,
    Copyright (C) 2012, 2014, 2016-2017 Ulrich Pegelow.
    Copyright (C) 2013-2016 Tobias Ellinghaus.
    Copyright (C) 2014, 2016 Roman Lebedev.
    Copyright (C) 2016 johannes hanika.
    Copyright (C) 2019 Andreas Schneider.
    Copyright (C) 2019, 2025-2026 Aurélien PIERRE.
    Copyright (C) 2020-2021 Hubert Kowalski.
    Copyright (C) 2020 Pascal Obry.
    Copyright (C) 2020-2021 Ralf Brown.
    Copyright (C) 2022 Hanno Schwalm.
    Copyright (C) 2022 Martin Bařinka.
    
    darktable is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.
    
    darktable is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.
    
    You should have received a copy of the GNU General Public License
    along with darktable.  If not, see <http://www.gnu.org/licenses/>.
*/
 
 
#include "common/darktable.h"
#include <assert.h>
#include <math.h>
#include "common/gaussian.h"
#include "common/math.h"
#include "common/opencl.h"
 
#define BLOCKSIZE (1 << 6)
 
static inline __attribute__((always_inline)) void compute_gauss_params(const float sigma, dt_gaussian_order_t order, float *a0, float *a1,
                                 float *a2, float *a3, float *b1, float *b2, float *coefp, float *coefn)
{
  const float alpha = 1.695f / sigma;
  const float ema = expf(-alpha);
  const float ema2 = expf(-2.0f * alpha);
  *b1 = -2.0f * ema;
  *b2 = ema2;
  *a0 = 0.0f;
  *a1 = 0.0f;
  *a2 = 0.0f;
  *a3 = 0.0f;
  *coefp = 0.0f;
  *coefn = 0.0f;
 
  switch(order)
  {
    default:
    case DT_IOP_GAUSSIAN_ZERO:
    {
      const float k = (1.0f - ema) * (1.0f - ema) / (1.0f + (2.0f * alpha * ema) - ema2);
      *a0 = k;
      *a1 = k * (alpha - 1.0f) * ema;
      *a2 = k * (alpha + 1.0f) * ema;
      *a3 = -k * ema2;
    }
    break;
 
    case DT_IOP_GAUSSIAN_ONE:
    {
      *a0 = (1.0f - ema) * (1.0f - ema);
      *a1 = 0.0f;
      *a2 = -*a0;
      *a3 = 0.0f;
    }
    break;
 
    case DT_IOP_GAUSSIAN_TWO:
    {
      const float k = -(ema2 - 1.0f) / (2.0f * alpha * ema);
      float kn = -2.0f * (-1.0f + (3.0f * ema) - (3.0f * ema * ema) + (ema * ema * ema));
      kn /= ((3.0f * ema) + 1.0f + (3.0f * ema * ema) + (ema * ema * ema));
      *a0 = kn;
      *a1 = -kn * (1.0f + (k * alpha)) * ema;
      *a2 = kn * (1.0f - (k * alpha)) * ema;
      *a3 = -kn * ema2;
    }
  }
 
  *coefp = (*a0 + *a1) / (1.0f + *b1 + *b2);
  *coefn = (*a2 + *a3) / (1.0f + *b1 + *b2);
}
 
size_t dt_gaussian_memory_use(const int width,    // width of input image
                              const int height,   // height of input image
                              const int channels) // channels per pixel
{
  return sizeof(float) * channels * width * height;
}
 
#ifdef HAVE_OPENCL
size_t dt_gaussian_memory_use_cl(const int width,    // width of input image
                                 const int height,   // height of input image
                                 const int channels) // channels per pixel
{
  return sizeof(float) * channels * (width + BLOCKSIZE) * (height + BLOCKSIZE) * 2;
}
#endif /* HAVE_OPENCL */
 
size_t dt_gaussian_singlebuffer_size(const int width,    // width of input image
                                     const int height,   // height of input image
                                     const int channels) // channels per pixel
{
  size_t mem_use;
#ifdef HAVE_OPENCL
  mem_use = sizeof(float) * channels * (width + BLOCKSIZE) * (height + BLOCKSIZE);
#else
  mem_use = sizeof(float) * channels * width * height;
#endif
  return mem_use;
}
 
 
dt_gaussian_t *dt_gaussian_init(const int width,    // width of input image
                                const int height,   // height of input image
                                const int channels, // channels per pixel
                                const float *max,   // maximum allowed values per channel for clamping
                                const float *min,   // minimum allowed values per channel for clamping
                                const float sigma,  // gaussian sigma
                                const int order)    // order of gaussian blur
{
  dt_gaussian_t *g = (dt_gaussian_t *)malloc(sizeof(dt_gaussian_t));
  if(IS_NULL_PTR(g)) return NULL;
 
  g->width = width;
  g->height = height;
  g->channels = channels;
  g->sigma = sigma;
  g->order = order;
  g->buf = NULL;
  g->max = (float *)calloc(channels, sizeof(float));
  g->min = (float *)calloc(channels, sizeof(float));
 
  if(IS_NULL_PTR(g->min) || IS_NULL_PTR(g->max)) goto error;
 
  for(int k = 0; k < channels; k++)
  {
    g->max[k] = max[k];
    g->min[k] = min[k];
  }
 
  g->buf = dt_pixelpipe_cache_alloc_align_float_cache((size_t)channels * width * height, 0);
  if(IS_NULL_PTR(g->buf)) goto error;
 
  return g;
 
error:
  dt_pixelpipe_cache_free_align(g->buf);
  if(g->max)
  {
    dt_free(g->max);
  }
  if(g->min)
  {
    dt_free(g->min);
  }
  dt_free(g);
  return NULL;
}
 
 
__DT_CLONE_TARGETS__
void dt_gaussian_blur(dt_gaussian_t *g, const float *const in, float *const out)
{
 
  const int width = g->width;
  const int height = g->height;
  const int ch = MIN(4, g->channels); // just to appease zealous compiler warnings about stack usage
 
  float a0, a1, a2, a3, b1, b2, coefp, coefn;
 
  compute_gauss_params(g->sigma, g->order, &a0, &a1, &a2, &a3, &b1, &b2, &coefp, &coefn);
 
  float *temp = g->buf;
 
  float *Labmax = g->max;
  float *Labmin = g->min;
 
// vertical blur column by column
  __OMP_PARALLEL_FOR__()
  for(int i = 0; i < width; i++)
  {
    dt_aligned_pixel_t xp = {0.0f};
    dt_aligned_pixel_t yb = {0.0f};
    dt_aligned_pixel_t yp = {0.0f};
 
    // forward filter
    for(int k = 0; k < ch; k++)
    {
      xp[k] = CLAMPF(in[(size_t)i * ch + k], Labmin[k], Labmax[k]);
      yb[k] = xp[k] * coefp;
      yp[k] = yb[k];
    }
 
    dt_aligned_pixel_t xc = {0.0f};
    dt_aligned_pixel_t yc = {0.0f};
    dt_aligned_pixel_t xn = {0.0f};
    dt_aligned_pixel_t xa = {0.0f};
    dt_aligned_pixel_t yn = {0.0f};
    dt_aligned_pixel_t ya = {0.0f};
    for(int j = 0; j < height; j++)
    {
      size_t offset = ((size_t)j * width + i) * ch;
 
      for(int k = 0; k < ch; k++)
      {
        xc[k] = CLAMPF(in[offset + k], Labmin[k], Labmax[k]);
        yc[k] = (a0 * xc[k]) + (a1 * xp[k]) - (b1 * yp[k]) - (b2 * yb[k]);
 
        temp[offset + k] = yc[k];
 
        xp[k] = xc[k];
        yb[k] = yp[k];
        yp[k] = yc[k];
      }
    }
 
    // backward filter
    for(int k = 0; k < ch; k++)
    {
      xn[k] = CLAMPF(in[((size_t)(height - 1) * width + i) * ch + k], Labmin[k], Labmax[k]);
      xa[k] = xn[k];
      yn[k] = xn[k] * coefn;
      ya[k] = yn[k];
    }
 
    for(int j = height - 1; j > -1; j--)
    {
      size_t offset = ((size_t)j * width + i) * ch;
 
      for(int k = 0; k < ch; k++)
      {
        xc[k] = CLAMPF(in[offset + k], Labmin[k], Labmax[k]);
 
        yc[k] = (a2 * xn[k]) + (a3 * xa[k]) - (b1 * yn[k]) - (b2 * ya[k]);
 
        xa[k] = xn[k];
        xn[k] = xc[k];
        ya[k] = yn[k];
        yn[k] = yc[k];
 
        temp[offset + k] += yc[k];
      }
    }
  }
 
// horizontal blur line by line
  __OMP_PARALLEL_FOR__()
  for(int j = 0; j < height; j++)
  {
    dt_aligned_pixel_t xp = {0.0f};
    dt_aligned_pixel_t yb = {0.0f};
    dt_aligned_pixel_t yp = {0.0f};
 
    // forward filter
    for(int k = 0; k < ch; k++)
    {
      xp[k] = CLAMPF(temp[(size_t)j * width * ch + k], Labmin[k], Labmax[k]);
      yb[k] = xp[k] * coefp;
      yp[k] = yb[k];
    }
 
    dt_aligned_pixel_t xc = {0.0f};
    dt_aligned_pixel_t yc = {0.0f};
    dt_aligned_pixel_t xn = {0.0f};
    dt_aligned_pixel_t xa = {0.0f};
    dt_aligned_pixel_t yn = {0.0f};
    dt_aligned_pixel_t ya = {0.0f};
 
    for(int i = 0; i < width; i++)
    {
      size_t offset = ((size_t)j * width + i) * ch;
 
      for(int k = 0; k < ch; k++)
      {
        xc[k] = CLAMPF(temp[offset + k], Labmin[k], Labmax[k]);
        yc[k] = (a0 * xc[k]) + (a1 * xp[k]) - (b1 * yp[k]) - (b2 * yb[k]);
 
        out[offset + k] = yc[k];
 
        xp[k] = xc[k];
        yb[k] = yp[k];
        yp[k] = yc[k];
      }
    }
 
    // backward filter
    for(int k = 0; k < ch; k++)
    {
      xn[k] = CLAMPF(temp[((size_t)(j + 1) * width - 1) * ch + k], Labmin[k], Labmax[k]);
      xa[k] = xn[k];
      yn[k] = xn[k] * coefn;
      ya[k] = yn[k];
    }
 
    for(int i = width - 1; i > -1; i--)
    {
      size_t offset = ((size_t)j * width + i) * ch;
 
      for(int k = 0; k < ch; k++)
      {
        xc[k] = CLAMPF(temp[offset + k], Labmin[k], Labmax[k]);
 
        yc[k] = (a2 * xn[k]) + (a3 * xa[k]) - (b1 * yn[k]) - (b2 * ya[k]);
 
        xa[k] = xn[k];
        xn[k] = xc[k];
        ya[k] = yn[k];
        yn[k] = yc[k];
 
        out[offset + k] += yc[k];
      }
    }
  }
}
 
void dt_gaussian_blur_4c(dt_gaussian_t *g, const float *const in, float *const out)
{
  return dt_gaussian_blur(g, in, out);
}
 
void dt_gaussian_free(dt_gaussian_t *g)
{
  if(IS_NULL_PTR(g)) return;
  dt_pixelpipe_cache_free_align(g->buf);
  dt_free(g->min);
  dt_free(g->max);
  dt_free(g);
}
 
 
#ifdef HAVE_OPENCL
dt_gaussian_cl_global_t *dt_gaussian_init_cl_global()
{
  dt_gaussian_cl_global_t *g = (dt_gaussian_cl_global_t *)malloc(sizeof(dt_gaussian_cl_global_t));
 
  const int program = 6; // gaussian.cl, from programs.conf
  g->kernel_gaussian_column_1c = dt_opencl_create_kernel(program, "gaussian_column_1c");
  g->kernel_gaussian_transpose_1c = dt_opencl_create_kernel(program, "gaussian_transpose_1c");
  g->kernel_gaussian_column_4c = dt_opencl_create_kernel(program, "gaussian_column_4c");
  g->kernel_gaussian_transpose_4c = dt_opencl_create_kernel(program, "gaussian_transpose_4c");
  return g;
}
 
void dt_gaussian_free_cl(dt_gaussian_cl_t *g)
{
  if(IS_NULL_PTR(g)) return;
  dt_free(g->min);
  dt_free(g->max);
  // free device mem
  dt_opencl_release_mem_object(g->dev_temp1);
  dt_opencl_release_mem_object(g->dev_temp2);
  dt_free(g);
}
 
dt_gaussian_cl_t *dt_gaussian_init_cl(const int devid,
                                      const int width,    // width of input image
                                      const int height,   // height of input image
                                      const int channels, // channels per pixel
                                      const float *max,   // maximum allowed values per channel for clamping
                                      const float *min,   // minimum allowed values per channel for clamping
                                      const float sigma,  // gaussian sigma
                                      const int order)    // order of gaussian blur
{
  assert(channels == 1 || channels == 4);
 
  if(!(channels == 1 || channels == 4)) return NULL;
 
  dt_gaussian_cl_t *g = (dt_gaussian_cl_t *)malloc(sizeof(dt_gaussian_cl_t));
  if(IS_NULL_PTR(g)) return NULL;
 
  g->global = darktable.opencl->gaussian;
  g->devid = devid;
  g->width = width;
  g->height = height;
  g->channels = channels;
  g->sigma = sigma;
  g->order = order;
  g->dev_temp1 = NULL;
  g->dev_temp2 = NULL;
  g->max = (float *)calloc(channels, sizeof(float));
  g->min = (float *)calloc(channels, sizeof(float));
 
  if(IS_NULL_PTR(g->min) || IS_NULL_PTR(g->max)) goto error;
 
  for(int k = 0; k < channels; k++)
  {
    g->max[k] = max[k];
    g->min[k] = min[k];
  }
 
  int kernel_gaussian_transpose = (channels == 1) ? g->global->kernel_gaussian_transpose_1c
                                                  : g->global->kernel_gaussian_transpose_4c;
  int blocksize;
 
  dt_opencl_local_buffer_t locopt
    = (dt_opencl_local_buffer_t){ .xoffset = 1, .xfactor = 1, .yoffset = 0, .yfactor = 1,
                                  .cellsize = channels * sizeof(float), .overhead = 0,
                                  .sizex = BLOCKSIZE, .sizey = BLOCKSIZE };
 
  if(dt_opencl_local_buffer_opt(devid, kernel_gaussian_transpose, &locopt))
    blocksize = MIN(locopt.sizex, locopt.sizey);
  else
    blocksize = 1;
 
  // width and height of intermediate buffers. Need to be multiples of blocksize
  const size_t bwidth = ROUNDUP(width, blocksize);
  const size_t bheight = ROUNDUP(height, blocksize);
 
  g->blocksize = blocksize;
  g->bwidth = bwidth;
  g->bheight = bheight;
 
  // get intermediate vector buffers with read-write access
  g->dev_temp1 = dt_opencl_alloc_device_buffer(devid, sizeof(float) * channels * bwidth * bheight);
  if(IS_NULL_PTR(g->dev_temp1)) goto error;
  g->dev_temp2 = dt_opencl_alloc_device_buffer(devid, sizeof(float) * channels * bwidth * bheight);
  if(IS_NULL_PTR(g->dev_temp2)) goto error;
 
  return g;
 
error:
  dt_free(g->min);
  dt_free(g->max);
  dt_opencl_release_mem_object(g->dev_temp1);
  dt_opencl_release_mem_object(g->dev_temp2);
  g->dev_temp1 = g->dev_temp2 = NULL;
  dt_free(g);
  return NULL;
}
 
 
cl_int dt_gaussian_blur_cl(dt_gaussian_cl_t *g, cl_mem dev_in, cl_mem dev_out)
{
  cl_int err = -999;
  const int devid = g->devid;
 
  const int width = g->width;
  const int height = g->height;
  const int channels = g->channels;
  const size_t bpp = sizeof(float) * channels;
  cl_mem dev_temp1 = g->dev_temp1;
  cl_mem dev_temp2 = g->dev_temp2;
 
  const int blocksize = g->blocksize;
  const int bwidth = g->bwidth;
  const int bheight = g->bheight;
 
  dt_aligned_pixel_t Labmax = { 0.0f };
  dt_aligned_pixel_t Labmin = { 0.0f };
 
  for(int k = 0; k < MIN(channels, 4); k++)
  {
    Labmax[k] = g->max[k];
    Labmin[k] = g->min[k];
  }
 
  int kernel_gaussian_column = -1;
  int kernel_gaussian_transpose = -1;
 
  if(channels == 1)
  {
    kernel_gaussian_column = g->global->kernel_gaussian_column_1c;
    kernel_gaussian_transpose = g->global->kernel_gaussian_transpose_1c;
  }
  else if(channels == 4)
  {
    kernel_gaussian_column = g->global->kernel_gaussian_column_4c;
    kernel_gaussian_transpose = g->global->kernel_gaussian_transpose_4c;
  }
  else
    return err;
 
  size_t origin[] = { 0, 0, 0 };
  size_t region[] = { width, height, 1 };
  size_t local[] = { blocksize, blocksize, 1 };
  size_t sizes[3];
 
  // compute gaussian parameters
  float a0, a1, a2, a3, b1, b2, coefp, coefn;
  compute_gauss_params(g->sigma, g->order, &a0, &a1, &a2, &a3, &b1, &b2, &coefp, &coefn);
 
  // copy dev_in to intermediate buffer dev_temp1
  err = dt_opencl_enqueue_copy_image_to_buffer(devid, dev_in, dev_temp1, origin, region, 0);
  if(err != CL_SUCCESS) return err;
 
  // first blur step: column by column with dev_temp1 -> dev_temp2
  sizes[0] = ROUNDUPDWD(width, devid);
  sizes[1] = 1;
  sizes[2] = 1;
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 0, sizeof(cl_mem), (void *)&dev_temp1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 1, sizeof(cl_mem), (void *)&dev_temp2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 2, sizeof(int), (void *)&width);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 3, sizeof(int), (void *)&height);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 4, sizeof(float), (void *)&a0);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 5, sizeof(float), (void *)&a1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 6, sizeof(float), (void *)&a2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 7, sizeof(float), (void *)&a3);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 8, sizeof(float), (void *)&b1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 9, sizeof(float), (void *)&b2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 10, sizeof(float), (void *)&coefp);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 11, sizeof(float), (void *)&coefn);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 12, sizeof(float) * channels, (void *)&Labmax);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 13, sizeof(float) * channels, (void *)&Labmin);
  err = dt_opencl_enqueue_kernel_2d(devid, kernel_gaussian_column, sizes);
  if(err != CL_SUCCESS) return err;
 
  // intermediate step: transpose dev_temp2 -> dev_temp1
  sizes[0] = bwidth;
  sizes[1] = bheight;
  sizes[2] = 1;
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 0, sizeof(cl_mem), (void *)&dev_temp2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 1, sizeof(cl_mem), (void *)&dev_temp1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 2, sizeof(int), (void *)&width);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 3, sizeof(int), (void *)&height);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 4, sizeof(int), (void *)&blocksize);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 5, bpp * blocksize * (blocksize + 1), NULL);
  err = dt_opencl_enqueue_kernel_2d_with_local(devid, kernel_gaussian_transpose, sizes, local);
  if(err != CL_SUCCESS) return err;
 
 
  // second blur step: column by column of transposed image with dev_temp1 -> dev_temp2 (!! height <-> width
  // !!)
  sizes[0] = ROUNDUPDHT(height, devid);
  sizes[1] = 1;
  sizes[2] = 1;
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 0, sizeof(cl_mem), (void *)&dev_temp1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 1, sizeof(cl_mem), (void *)&dev_temp2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 2, sizeof(int), (void *)&height);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 3, sizeof(int), (void *)&width);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 4, sizeof(float), (void *)&a0);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 5, sizeof(float), (void *)&a1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 6, sizeof(float), (void *)&a2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 7, sizeof(float), (void *)&a3);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 8, sizeof(float), (void *)&b1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 9, sizeof(float), (void *)&b2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 10, sizeof(float), (void *)&coefp);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 11, sizeof(float), (void *)&coefn);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 12, sizeof(float) * channels, (void *)&Labmax);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_column, 13, sizeof(float) * channels, (void *)&Labmin);
  err = dt_opencl_enqueue_kernel_2d(devid, kernel_gaussian_column, sizes);
  if(err != CL_SUCCESS) return err;
 
 
  // transpose back dev_temp2 -> dev_temp1
  sizes[0] = bheight;
  sizes[1] = bwidth;
  sizes[2] = 1;
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 0, sizeof(cl_mem), (void *)&dev_temp2);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 1, sizeof(cl_mem), (void *)&dev_temp1);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 2, sizeof(int), (void *)&height);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 3, sizeof(int), (void *)&width);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 4, sizeof(int), (void *)&blocksize);
  dt_opencl_set_kernel_arg(devid, kernel_gaussian_transpose, 5, bpp * blocksize * (blocksize + 1), NULL);
  err = dt_opencl_enqueue_kernel_2d_with_local(devid, kernel_gaussian_transpose, sizes, local);
  if(err != CL_SUCCESS) return err;
 
  // finally produce output in dev_out
  err = dt_opencl_enqueue_copy_buffer_to_image(devid, dev_temp1, dev_out, 0, origin, region);
  if(err != CL_SUCCESS) return err;
 
  return CL_SUCCESS;
}
 
 
void dt_gaussian_free_cl_global(dt_gaussian_cl_global_t *g)
{
  if(IS_NULL_PTR(g)) return;
  // destroy kernels
  dt_opencl_free_kernel(g->kernel_gaussian_column_1c);
  dt_opencl_free_kernel(g->kernel_gaussian_transpose_1c);
  dt_opencl_free_kernel(g->kernel_gaussian_column_4c);
  dt_opencl_free_kernel(g->kernel_gaussian_transpose_4c);
  dt_free(g);
}
 
#endif
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