XlaCompileOnDemandOp);                               \
  REGISTER_KERNEL_BUILDER(                                                     \
      Name("XlaDynamicSlice").HostMemory("size_indices").Device(DEVICE),       \
      XlaCompileOnDemandOp);                                                   \
  REGISTER_KERNEL_BUILDER(Name("XlaDynamicUpdateSlice").Device(DEVICE),        \

      // $window_strides, $padding, $lhs_dilation, $rhs_dilation,
      // $feature_group_count
      CompileTimeConstantOperand<TF::XlaConvV2Op, 2, 3, 4, 5, 6>,
      CompileTimeConstantOperand<TF::XlaDynamicSliceOp, 2>,  // $slice_indices
      CompileTimeConstantOperand<TF::XlaGatherOp, 2>,        // $slice_sizes
      // $padding_low, $padding_high, $padding_interior
      CompileTimeConstantOperand<TF::XlaPadOp, 2, 3, 4>,

https://www.tensorflow.org/performance/xla/operation_semantics#dynamicslice
.

DynamicSlice extracts a sub-array from the input array at dynamic
start_indices. The size of the slice in each dimension is passed in
size_indices, which specify the end point of exclusive slice intervals in each
dimension -- [start, start + size). The shape of start_indices must have rank 1,
with dimension size equal to the rank of operand.
  }];