Fixed Eigen-version Conv2DBackpropInput kernel, marked with "eigen_tensor".

LaunchConv2DBackpropInputOp, a template functor class used in
Conv2DFastBackpropInputOp class was specialized in a wrong place, in
conv_grad_filter_ops.cc (ODR violation). This caused wrong functor to be called
inside the op kernel class, because the correct functor definition was overriden
by a wrong specialization. The functor class that should have been specialized
in conv_grad_filter_ops.cc was LaunchConv2DBackpropFilterOp.

PiperOrigin-RevId: 182438025

1 files changed, 4 insertions, 6 deletions

diff --git a/tensorflow/core/kernels/conv_grad_filter_ops.cc b/tensorflow/core/kernels/conv_grad_filter_ops.cc
index 5e4feb2584..512bcc6c01 100644
--- a/tensorflow/core/kernels/conv_grad_filter_ops.cc
+++ b/tensorflow/core/kernels/conv_grad_filter_ops.cc
@@ -93,16 +93,15 @@ typedef Eigen::ThreadPoolDevice CPUDevice;
 typedef Eigen::GpuDevice GPUDevice;
 
 template <typename T>
-struct LaunchConv2DBackpropInputOp<CPUDevice, T> {
+struct LaunchConv2DBackpropFilterOp<CPUDevice, T> {
   void operator()(OpKernelContext* ctx, bool use_cudnn, bool cudnn_use_autotune,
                   const Tensor& out_backprop, const Tensor& input,
                   int row_stride, int col_stride, const Padding& padding,
                   Tensor* filter_backprop, TensorFormat data_format) {
     const CPUDevice& d = ctx->eigen_device<CPUDevice>();
-    functor::SpatialConvolutionBackwardInput<CPUDevice, T>()(
+    functor::SpatialConvolutionBackwardFilter<CPUDevice, T>()(
         d, filter_backprop->tensor<T, 4>(), input.tensor<T, 4>(),
-        out_backprop.tensor<T, 4>(), filter_backprop->dim_size(0),
-        filter_backprop->dim_size(1), row_stride, col_stride);
+        out_backprop.tensor<T, 4>(), row_stride, col_stride);
   }
 };
 
@@ -273,7 +272,7 @@ class Conv2DFastBackpropFilterOp : public OpKernel {
     }
 #endif
 
-    LaunchConv2DBackpropInputOp<Device, T>()(
+    LaunchConv2DBackpropFilterOp<Device, T>()(
         context, false, false, out_backprop, input, dims.spatial_dims[0].stride,
         dims.spatial_dims[1].stride, padding_, filter_backprop, data_format_);
   }
@@ -603,7 +602,6 @@ class Conv2DSlowBackpropFilterOp : public OpKernel {
       return;
     }
 
-
     // For now we take the stride from the second and third dimensions only (we
     // do not support striding on the batch or depth dimension).
     const int stride_rows = GetTensorDim(strides_, data_format_, 'H');