//   %arg1)
//     : (tensor<i32>, tensor<2x2xi32>, tensor<2xf32>, tensor<2x2x2xf32>)
//     -> tensor<5x2xf32>
//
// is lowered to
//
//   %shape = "tf.Const"() {value = dense<[-1, 2]> : tensor<2xi64>}
//   %inp0 = "tf.Reshape"(%arg0, %shape)
//     : (tensor<2xf32>, tensor<2xi64>) -> tensor<1x2xf32>
//   %inp1 = "tf.Reshape"(%arg1, %shape)
//     : (tensor<2x2x2xf32>, tensor<2xi64>) -> tensor<4x2xf32>

// CHECK-NEXT:    %[[RESHAPED_1:.*]] = mhlo.reshape %[[TRANSPOSED_1]]
// CHECK-NEXT:    %[[BMM_0:.*]] = "tfl.batch_matmul"(%[[RESHAPED_0]], %[[RESHAPED_1]]) <{adj_x = false, adj_y = false, asymmetric_quantize_inputs = false}> : (tensor<3x5x12xf32>, tensor<3x12x4xf32>) -> tensor<3x5x4xf32>
// CHECK-NEXT:    %[[RESHAPED_BMM:.*]] = mhlo.reshape %[[BMM_0]]
// CHECK-NEXT:    return %[[RESHAPED_BMM]] : tensor<3x5x1x4xf32>
}

// CHECK:           }) : (tensor<5x4x3x7xf32>, tensor<2x2xi32>, tensor<2x5x3xf32>) -> tensor<5x4x3x7xf32>
// CHECK:           return %[[VAL_3]] : tensor<5x4x3x7xf32>
// CHECK:         }
func.func @convert_scatter_update_to_non_trailing_operand_dimensions(
  %arg0: tensor<5x4x3x7xf32>,
  %arg1: tensor<2x2xi32>,
  %arg2: tensor<2x5x3xf32>) -> tensor<5x4x3x7xf32>
{
  %0 = "mhlo.scatter"(%arg0, %arg1, %arg2) ({

func.func @testFullyConnectedWithBadInputShape(%arg0: tensor<2x2x11xf32>, %arg1: tensor<40x40xf32>, %arg2: none) -> tensor<40xf32> {
  // expected-error @+1 {{expect 'input' num_elements % 40 == 0, got input type 'tensor<2x2x11xf32>'}}
  %0 = "tfl.fully_connected"(%arg0, %arg1, %arg2) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<2x2x11xf32>, tensor<40x40xf32>, none) -> tensor<1x40xf32>

func.func @conv2d_backprop_input_grouped(
    %filter: tensor<2x2x5x21xf32>,
    %out_backprop: tensor<5x2x2x21xf32>
  ) -> tensor<5x3x3x15xf32> {
  %input_sizes = "tf.Const" () { value = dense<[5, 3, 3, 15]> : tensor<4xi32> } : () -> tensor<4xi32>

  // Verify filter transformation for grouped convolution.

  // CHECK: %[[RESHAPE:.*]] = mhlo.reshape %arg0 : (tensor<2x2x5x21xf32>) -> tensor<2x2x5x3x7xf32>