From aeae4825b35eb8cb18b5478a1d8863272b8a3634 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <nobody@tensorflow.org>
Date: Thu, 25 Feb 2016 15:02:54 -0800
Subject: [PATCH] Add symbolic gradient functions for Conv2D and MaxPool
 Change: 115608522

---
 tensorflow/core/ops/nn_grad.cc | 66 ++++++++++++++++++++++++++++++++++
 1 file changed, 66 insertions(+)

diff --git a/tensorflow/core/ops/nn_grad.cc b/tensorflow/core/ops/nn_grad.cc
index b12b7469a11..2565fc07194 100644
--- a/tensorflow/core/ops/nn_grad.cc
+++ b/tensorflow/core/ops/nn_grad.cc
@@ -15,6 +15,8 @@ limitations under the License.
 
 #include "tensorflow/core/framework/function.h"
 #include "tensorflow/core/lib/core/errors.h"
+#include "tensorflow/core/util/padding.h"
+#include "tensorflow/core/util/tensor_format.h"
 
 namespace tensorflow {
 
@@ -94,4 +96,68 @@ Status CrossEntropyGrad(const AttrSlice& attrs, FunctionDef* g) {
 }
 REGISTER_OP_GRADIENT("CrossEntropy", CrossEntropyGrad);
 
+Status Conv2DGrad(const AttrSlice& attrs, FunctionDef* g) {
+  // clang-format off
+  *g = FDH::Define(
+    // Arg defs
+    {"input: T", "filter: T", "grad: T"},
+    // Ret val defs
+    {"input_grad: T", "filter_grad: T"},
+    // Attr defs
+    {"T: {float, double}",
+     "strides: list(int)",
+     "use_cudnn_on_gpu: bool = true",
+     GetPaddingAttrString(),
+     GetConvnetDataFormatAttrString()},
+    // Nodes
+    {
+      {{"i_shape"}, "Shape", {"input"}, {{"T", "$T"}}},
+      {{"input_grad"}, "Conv2DBackpropInput", {"i_shape", "filter", "grad"},
+       /*Attrs=*/{{"T", "$T"},
+                  {"strides", "$strides"},
+                  {"padding", "$padding"},
+                  {"data_format", "$data_format"},
+                  {"use_cudnn_on_gpu", "$use_cudnn_on_gpu"}}},
+
+      {{"f_shape"}, "Shape", {"filter"}, {{"T", "$T"}}},
+      {{"filter_grad"}, "Conv2DBackpropFilter", {"input", "f_shape", "grad"},
+       /*Attrs=*/{{"T", "$T"},
+                  {"strides", "$strides"},
+                  {"padding", "$padding"},
+                  {"data_format", "$data_format"},
+                  {"use_cudnn_on_gpu", "$use_cudnn_on_gpu"}}},
+    });
+  // clang-format on
+  return Status::OK();
+}
+REGISTER_OP_GRADIENT("Conv2D", Conv2DGrad);
+
+Status MaxPoolGrad(const AttrSlice& attrs, FunctionDef* g) {
+  // clang-format off
+  *g = FDH::Define(
+    // Arg defs
+    {"input: float", "grad: float"},
+    // Ret val defs
+    {"output: float"},
+    // Attr defs
+    {"ksize: list(int) >= 4",
+     "strides: list(int) >= 4",
+     GetPaddingAttrString()},
+    // Nodes
+    {
+      // Invoke MaxPool again to recompute the outputs (removed by CSE?).
+      {{"maxpool"}, "MaxPool", {"input"},
+       /*Attrs=*/{{"ksize", "$ksize"},
+                  {"strides", "$strides"},
+                  {"padding", "$padding"}}},
+      {{"output"}, "MaxPoolGrad", {"input", "maxpool", "grad"},
+       /*Attrs=*/{{"ksize", "$ksize"},
+                  {"strides", "$strides"},
+                  {"padding", "$padding"}}}
+    });
+  // clang-format on
+  return Status::OK();
+}
+REGISTER_OP_GRADIENT("MaxPool", MaxPoolGrad);
+
 }  // end namespace tensorflow