| 438 | // ------------------------------------------------------------------------------------ |
| 439 | |
| 440 | void assign_conv_bias_gradient ( |
| 441 | tensor& grad, |
| 442 | const tensor& gradient_input |
| 443 | ) |
| 444 | { |
| 445 | DLIB_CASSERT( |
| 446 | grad.num_samples() == 1 && |
| 447 | grad.k() >= 1 && |
| 448 | grad.nr() == 1 && |
| 449 | grad.nc() == 1 && |
| 450 | gradient_input.k() == grad.k() && |
| 451 | gradient_input.size() > 0 && |
| 452 | is_same_object(grad,gradient_input) == false |
| 453 | ); |
| 454 | |
| 455 | auto g = grad.host(); |
| 456 | auto gi = gradient_input.host(); |
| 457 | |
| 458 | for (long k = 0; k < gradient_input.k(); ++k) |
| 459 | g[k] = 0; |
| 460 | |
| 461 | for (long n = 0; n < gradient_input.num_samples(); ++n) |
| 462 | { |
| 463 | for (long k = 0; k < gradient_input.k(); ++k) |
| 464 | { |
| 465 | for (long r = 0; r < gradient_input.nr(); ++r) |
| 466 | { |
| 467 | for (long c = 0; c < gradient_input.nc(); ++c) |
| 468 | { |
| 469 | g[k] += (*gi++); |
| 470 | } |
| 471 | } |
| 472 | } |
| 473 | } |
| 474 | } |
| 475 | |
| 476 | // ----------------------------------------------------------------------------------- |
| 477 | |