message: fix an initialization problem in MklFusedBatchNorm
diff: @@ -1008,7 +1008,7 @@ class MklFusedBatchNormOp : public OpKernel {
  tf_shape_scale, mkl_shape_saved_mean);
  DCHECK(*saved_mean_tensor);
  - // Set NAN mean value in case of empty input tensor
  + // Set 0 mean value in case of empty input tensor
  auto saved_mean_data = (*saved_mean_tensor)->flat<U>().data();
  std::fill_n(saved_mean_data, num_elements, static_cast<U>(0));
  @@ -1019,7 +1019,7 @@ class MklFusedBatchNormOp : public OpKernel {
  mkl_shape_saved_variance);
  DCHECK(*saved_variance_tensor);
  - // Set NAN variance value in case of empty input tensor
  + // Set 0 variance value in case of empty input tensor
  auto saved_variance_data = (*saved_variance_tensor)->flat<U>().data();
  std::fill_n(saved_variance_data, num_elements, static_cast<U>(0));
  @@ -1346,16 +1346,12 @@ class MklFusedBatchNormGradOp : public OpKernel {
  mkl_shape_p.SetMklTensor(false);
  AllocateOutputSetMklShape(context, kP1Index, &p1_tensor, TensorShape({}),
  mkl_shape_p);
  -#ifndef ENABLE_MKLDNN_V1
  std::fill_n(p1_tensor->flat<U>().data(), p1_tensor->shape().num_elements(),
  static_cast<U>(0));
  -#endif // !ENABLE_MKLDNN_V1
  AllocateOutputSetMklShape(context, kP2Index, &p2_tensor, TensorShape({}),
  mkl_shape_p);
  -#ifndef ENABLE_MKLDNN_V1
  std::fill_n(p2_tensor->flat<U>().data(), p2_tensor->shape().num_elements(),
  static_cast<U>(0));
  -#endif // !ENABLE_MKLDNN_V1
  }
  memory::dims GetMeanVarianceDims() { return memory::dims({1, depth_}); }
  