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Diffstat (limited to 'tensorflow/cc/gradients/math_grad.cc')
| -rw-r--r-- | tensorflow/cc/gradients/math_grad.cc | 20 |
1 files changed, 20 insertions, 0 deletions
diff --git a/tensorflow/cc/gradients/math_grad.cc b/tensorflow/cc/gradients/math_grad.cc index cd215f740d..1329b568ab 100644 --- a/tensorflow/cc/gradients/math_grad.cc +++ b/tensorflow/cc/gradients/math_grad.cc @@ -1022,6 +1022,26 @@ Status ProdGrad(const Scope& scope, const Operation& op, } REGISTER_GRADIENT_OP("Prod", ProdGrad); +Status SegmentSumGrad(const Scope& scope, const Operation& op, + const std::vector<Output>& grad_inputs, + std::vector<Output>* grad_outputs) { + // The SegmentSum operation sums segments of the Tensor that have the same + // index in the segment_ids parameter. + // i.e z = [2, 3, 4, 5], segment_ids [0, 0, 0, 1] + // will produce [2 + 3 + 4, 5] = [9, 5] + // The gradient that will flow back to the gather operation will look like + // [x1, x2], it will have the same shape as the output of the SegmentSum + // operation. The differentiation step of the SegmentSum operation just + // broadcast the gradient in order to retrieve the z's shape. + // dy/dz = [x1, x1, x1, x2] + grad_outputs->push_back(Gather(scope, grad_inputs[0], op.input(1))); + + // stop propagation along segment_ids + grad_outputs->push_back(NoGradient()); + return scope.status(); +} +REGISTER_GRADIENT_OP("SegmentSum", SegmentSumGrad); + // MatMulGrad helper function used to compute two MatMul operations // based on input matrix transposition combinations. Status MatMulGradHelper(const Scope& scope, const bool is_batch, |