diff --git a/tensorflow/core/kernels/sparse_add_op.cc b/tensorflow/core/kernels/sparse_add_op.cc
index 346206365af8d5..2bd05fa41adc26 100644
--- a/tensorflow/core/kernels/sparse_add_op.cc
+++ b/tensorflow/core/kernels/sparse_add_op.cc
@@ -44,6 +44,11 @@ class SparseAddOp : public OpKernel {
                     b_indices->shape().DebugString()));
     const int64 a_nnz = a_indices->dim_size(0);
     const int64 b_nnz = b_indices->dim_size(0);
+    const int num_dims = a_indices->dim_size(1);
+    OP_REQUIRES(ctx, b_indices->dim_size(1) == num_dims,
+                errors::InvalidArgument(
+                    "Input indices must have the same dimension, got ",
+                    num_dims, " and ", b_indices->dim_size(1)));
 
     OP_REQUIRES_OK(ctx, ctx->input("a_values", &a_values_t));
     OP_REQUIRES_OK(ctx, ctx->input("b_values", &b_values_t));
@@ -72,6 +77,13 @@ class SparseAddOp : public OpKernel {
                     "Input shapes should be a vector but received shapes ",
                     a_shape->shape().DebugString(), " and ",
                     b_shape->shape().DebugString()));
+    OP_REQUIRES(
+        ctx, a_shape->NumElements() == num_dims,
+        errors::InvalidArgument("Second dimension of a_indices and length of "
+                                "a_shape must match, got ",
+                                num_dims, " and ", a_shape->NumElements()));
+    OP_REQUIRES(ctx, num_dims > 0,
+                errors::InvalidArgument("Tesors must not be empty"));
     OP_REQUIRES(
         ctx, a_shape->IsSameSize(*b_shape),
         errors::InvalidArgument(
@@ -100,11 +112,6 @@ class SparseAddOp : public OpKernel {
     std::vector<std::pair<bool, int64>> entries_to_copy;  // from_a?, idx
     entries_to_copy.reserve(a_nnz + b_nnz);
     std::vector<T> out_values;
-    const int num_dims = a_shape->dim_size(0);
-
-    OP_REQUIRES(ctx, num_dims > 0,
-                errors::InvalidArgument("Invalid input_a shape. Received: ",
-                                        a_shape->DebugString()));
 
     // The input and output sparse tensors are assumed to be ordered along
     // increasing dimension number.