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deconvolutiondepthwise.comp 3.3 kB

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  1. // Tencent is pleased to support the open source community by making ncnn available.
  2. //
  3. // Copyright (C) 2019 THL A29 Limited, a Tencent company. All rights reserved.
  4. //
  5. // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
  6. // in compliance with the License. You may obtain a copy of the License at
  7. //
  8. // https://opensource.org/licenses/BSD-3-Clause
  9. //
  10. // Unless required by applicable law or agreed to in writing, software distributed
  11. // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
  12. // CONDITIONS OF ANY KIND, either express or implied. See the License for the
  13. // specific language governing permissions and limitations under the License.
  14. #version 450
  15. #if NCNN_fp16_storage
  16. #extension GL_EXT_shader_16bit_storage: require
  17. #endif
  18. #if NCNN_fp16_arithmetic
  19. #extension GL_AMD_gpu_shader_half_float: require
  20. #endif
  21. layout (constant_id = 0) const int kernel_w = 1;
  22. layout (constant_id = 1) const int kernel_h = 1;
  23. layout (constant_id = 2) const int dilation_w = 1;
  24. layout (constant_id = 3) const int dilation_h = 1;
  25. layout (constant_id = 4) const int stride_w = 1;
  26. layout (constant_id = 5) const int stride_h = 1;
  27. layout (constant_id = 6) const int bias_term = 0;
  28. layout (constant_id = 7) const int group = 1;
  29. layout (local_size_x_id = 233) in;
  30. layout (local_size_y_id = 234) in;
  31. layout (local_size_z_id = 235) in;
  32. layout (binding = 0) readonly buffer bottom_blob { sfp bottom_blob_data[]; };
  33. layout (binding = 1) writeonly buffer top_blob { sfp top_blob_data[]; };
  34. layout (binding = 2) readonly buffer weight_blob { sfp weight_data[]; };
  35. layout (binding = 3) readonly buffer bias_blob { sfp bias_data[]; };
  36. layout (push_constant) uniform parameter
  37. {
  38. int dims;
  39. int w;
  40. int h;
  41. int c;
  42. int cstep;
  43. int outdims;
  44. int outw;
  45. int outh;
  46. int outc;
  47. int outcstep;
  48. } p;
  49. void main()
  50. {
  51. int gx = int(gl_GlobalInvocationID.x);
  52. int gy = int(gl_GlobalInvocationID.y);
  53. int gz = int(gl_GlobalInvocationID.z);
  54. if (gx >= p.outw || gy >= p.outh || gz >= p.outc)
  55. return;
  56. afp sum;
  57. if (bias_term == 1)
  58. {
  59. sum = afp(bias_data[gz]);
  60. }
  61. else
  62. {
  63. sum = afp(0.f);
  64. }
  65. const int kernel_extent_w = dilation_w * (kernel_w - 1) + 1;
  66. const int kernel_extent_h = dilation_h * (kernel_h - 1) + 1;
  67. // depth-wise deconvolution
  68. int v_offset_0 = gz * p.cstep;
  69. int w_offset_0 = gz * kernel_w * kernel_h;
  70. for (int y = 0; y < kernel_h; y++)
  71. {
  72. int sys = (gy + y * dilation_h - (kernel_extent_h - 1));
  73. if (sys % stride_h != 0)
  74. continue;
  75. int sy = sys / stride_h;
  76. if (sy < 0 || sy >= p.h)
  77. continue;
  78. for (int x = 0; x < kernel_w; x++)
  79. {
  80. int sxs = (gx + x * dilation_w - (kernel_extent_w - 1));
  81. if (sxs % stride_w != 0)
  82. continue;
  83. int sx = sxs / stride_w;
  84. if (sx < 0 || sx >= p.w)
  85. continue;
  86. int v_offset = v_offset_0 + sy * p.w + sx;
  87. int w_offset = w_offset_0 + y * kernel_w + x;
  88. sum += afp(weight_data[w_offset]) * afp(bottom_blob_data[v_offset]);
  89. }
  90. }
  91. top_blob_data[gz * p.outcstep + gy * p.outw + gx] = sfp(sum);
  92. }