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| author |  RJ Ryan <rjryan@google.com> | 2017-07-10 16:41:33 -0700 |
|---|---|---|
| committer |  TensorFlower Gardener <gardener@tensorflow.org> | 2017-07-10 16:51:17 -0700 |
| commit | a6773e98e97956b7adf3aa51eb3548261f51d6f7 (patch) | |
| tree | a4fa423385edabe441d7644c6df7a62803e7e2a3 /tensorflow/cc | |
| parent | 285f9766471e10fa9fee4299940225a33515c010 (diff) | |
Add a PadV2 op with support for specifying a pad value.
Added a `constant_values` keyword argument to the tf.pad Python API for compatibility with numpy.pad. For now, only scalar values are supported. To efficiently support specifying a `[D, 2]` tensor for `constant_values` to pick per-dimension pre/post constant values will require adding Eigen and XLA support first.
PiperOrigin-RevId: 161460091
Diffstat (limited to 'tensorflow/cc')
| -rw-r--r-- | tensorflow/cc/gradients/array_grad.cc | 8 |
1 files changed, 7 insertions, 1 deletions
diff --git a/tensorflow/cc/gradients/array_grad.cc b/tensorflow/cc/gradients/array_grad.cc index 48185db3cb..6545e4ee3e 100644 --- a/tensorflow/cc/gradients/array_grad.cc +++ b/tensorflow/cc/gradients/array_grad.cc @@ -269,6 +269,7 @@ Status ScatterNdNonAliasingAddGrad(const Scope& scope, const Operation& op, } REGISTER_GRADIENT_OP("ScatterNdNonAliasingAdd", ScatterNdNonAliasingAddGrad); +template <bool IsPadV2> Status PadGrad(const Scope& scope, const Operation& op, const std::vector<Output>& grad_inputs, std::vector<Output>* grad_outputs) { @@ -281,9 +282,14 @@ Status PadGrad(const Scope& scope, const Operation& op, auto begin = Reshape(scope, pad_before, {-1}); grad_outputs->push_back(Slice(scope, grad_inputs[0], begin, Shape(scope, x))); grad_outputs->push_back(NoGradient()); + // PadV2 adds a "constant_values" input. + if (IsPadV2) { + grad_outputs->push_back(NoGradient()); + } return scope.status(); } -REGISTER_GRADIENT_OP("Pad", PadGrad); +REGISTER_GRADIENT_OP("Pad", PadGrad<false>); +REGISTER_GRADIENT_OP("PadV2", PadGrad<true>); Status SpaceToBatchGrad(const Scope& scope, const Operation& op, const std::vector<Output>& grad_inputs, |