Fix empty input crash for SparseFillEmptyRowsGrad.

PiperOrigin-RevId: 478085721
tensorflow · Sep 30, 2022 · af4a6a3 · af4a6a3
1 parent 2c04e3f
commit af4a6a3
Show file tree

Hide file tree

Showing 2 changed files with 33 additions and 17 deletions.
diff --git a/tensorflow/core/kernels/sparse_fill_empty_rows_op_gpu.cu.cc b/tensorflow/core/kernels/sparse_fill_empty_rows_op_gpu.cu.cc
@@ -297,9 +297,12 @@ struct SparseFillEmptyRows<GPUDevice, T, Tindex> {
       empty_row_indicator = empty_row_indicator_t.vec<bool>().data();
     }
 
-    TF_RETURN_IF_ERROR(wrap_kernel_call(ComputeEmptyRowIndicatorKernel<Tindex>,
-                                        /*device=*/device, /*size=*/dense_rows,
-                                        elements_per_row, empty_row_indicator));
+    if (dense_rows > 0) {
+      TF_RETURN_IF_ERROR(
+          wrap_kernel_call(ComputeEmptyRowIndicatorKernel<Tindex>,
+                           /*device=*/device, /*size=*/dense_rows,
+                           elements_per_row, empty_row_indicator));
+    }
 
     // For each row, the number of empty rows up to and including that row.
     Tensor num_empty_rows_through_t;
@@ -405,14 +408,16 @@ struct SparseFillEmptyRows<GPUDevice, T, Tindex> {
             done);
       }
 
-      OP_REQUIRES_OK_ASYNC(
-          context,
-          wrap_kernel_call(ScatterNewElementsKernel<T, Tindex>,
-                           /*device=*/device, /*size=*/dense_rows, rank,
-                           default_value, num_empty_rows_through,
-                           input_row_ends, empty_row_indicator, output_indices,
-                           output_values),
-          done);
+      if (dense_rows > 0) {
+        OP_REQUIRES_OK_ASYNC(
+            context,
+            wrap_kernel_call(ScatterNewElementsKernel<T, Tindex>,
+                             /*device=*/device, /*size=*/dense_rows, rank,
+                             default_value, num_empty_rows_through,
+                             input_row_ends, empty_row_indicator,
+                             output_indices, output_values),
+            done);
+      }
 
       done();
     };
@@ -461,9 +466,11 @@ struct SparseFillEmptyRows<GPUDevice, T, Tindex> {
     TF_RETURN_IF_ERROR(
         context->allocate_temp(index_type, TensorShape({N}), &row_indices_t));
     auto row_indices = row_indices_t.flat<Tindex>();
-    TF_RETURN_IF_ERROR(wrap_kernel_call(CopyRowIndicesKernel<Tindex>,
-                                        /*device=*/device, /*size=*/N, rank,
-                                        indices, row_indices));
+    if (N > 0) {
+      TF_RETURN_IF_ERROR(wrap_kernel_call(CopyRowIndicesKernel<Tindex>,
+                                          /*device=*/device, /*size=*/N, rank,
+                                          indices, row_indices));
+    }
     // Allocate input_index_map.
     TF_RETURN_IF_ERROR(context->allocate_temp(index_type, TensorShape({N}),
                                               input_index_map_t));
@@ -528,9 +535,11 @@ struct SparseFillEmptyRowsGrad<GPUDevice, T, Tindex> {
     auto visited = visited_t.vec<bool>();
     visited.device(device) = visited.constant(false);
 
-    TF_RETURN_IF_ERROR(wrap_kernel_call(
-        GatherOriginalGradValuesKernel<T, Tindex>, /*device=*/device,
-        /*size=*/N, reverse_index_map, grad_values, d_values, visited));
+    if (N > 0) {
+      TF_RETURN_IF_ERROR(wrap_kernel_call(
+          GatherOriginalGradValuesKernel<T, Tindex>, /*device=*/device,
+          /*size=*/N, reverse_index_map, grad_values, d_values, visited));
+    }
 
     // Now we mask out the visited values and sum the remaining ones (which
     // correspond to the empty rows in the forward input) to compute

diff --git a/tensorflow/python/kernel_tests/sparse_ops/sparse_ops_test.py b/tensorflow/python/kernel_tests/sparse_ops/sparse_ops_test.py
@@ -514,6 +514,13 @@ def testFillNumber(self):
         self.assertAllEqual(empty_row_indicator_out,
                             np.array([0, 0, 1, 0, 1]).astype(np.bool_))
 
+  def testSparseFillEmptyRowsGradEmpty(self):
+    with test_util.use_gpu():
+      grad, _ = self.evaluate(
+          sparse_ops.sparse_fill_empty_rows_grad(
+              reverse_index_map=[], grad_values=[]))
+      self.assertAllEqual(grad, [])
+
   @test_util.run_deprecated_v1
   def testFillFloat(self):
     with self.session():