// CHECK:           return %[[VAL_4]] : tensor<2x3xf16>
// CHECK:         }
func.func @floordiv_f16_broadcast(%arg0: tensor<2x3xf16>, %arg1: tensor<3xf16>) -> tensor<2x3xf16> {
  %0 = "chlo.broadcast_divide"(%arg0, %arg1) {broadcast_dimensions = array<i64: 1>} : (tensor<2x3xf16>, tensor<3xf16>) -> tensor<2x3xf16>

// CHECK-LABEL: func @floordiv_f16_broadcast
func.func @floordiv_f16_broadcast(%arg0: tensor<2x3xf16>, %arg1: tensor<3xf16>) -> tensor<2x3xf16> {
  // CHECK-NEXT:  chlo.broadcast_divide
  // CHECK-NEXT:  mhlo.floor
  // CHECK-NEXT:  return
  %0 = "tf.FloorDiv"(%arg0, %arg1) : (tensor<2x3xf16>, tensor<3xf16>) -> tensor<2x3xf16>
  func.return %0: tensor<2x3xf16>
}

// -----

// CHECK-LABEL: func @floordiv_dynamic

  %cst_1 = arith.constant dense<1.5> : tensor<256xf32>
  %cst_2 = arith.constant dense<2.0> : tensor<1x1x1x256xf32>
  %0 = "tfl.conv_2d"(%arg0, %cst_0, %cst_1) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32} : (tensor<1x8x8x207xf32>, tensor<256x3x3x207xf32>, tensor<256xf32>) -> tensor<1x8x8x256xf32>