func.func @testBatchMatMul(%lhs: tensor<2x?x2x?x3x5xf32>, %rhs: tensor<2x2x?x?x5x7xf32>) {
  %0 = "tf.BatchMatMul"(%lhs, %rhs) : (tensor<2x?x2x?x3x5xf32>, tensor<2x2x?x?x5x7xf32>) -> tensor<2x?x?x?x3x7xf32>
  func.return
}

// -----

// Mismatching batch dimensions.
func.func @testBatchMatMul(%lhs: tensor<1x3x5xf32>, %rhs: tensor<2x5x7xf32>) {

// CHECK:           %[[VAL_1:.*]] = arith.constant dense<[2, 2, 6]> : tensor<3xi64>
// CHECK:           %[[VAL_2:.*]] = "tf.Reshape"(%[[VAL_0]], %[[VAL_1]]) : (tensor<4x6xf32>, tensor<3xi64>) -> tensor<2x2x6xf32>
// CHECK:           return %[[VAL_2]] : tensor<2x2x6xf32>
// CHECK:         }
func.func @reshape(%arg0: tensor<4x6xf32>) -> tensor<2x2x6xf32> {

  %405 = "tfl.reshape"(%404, %cst_0) : (tensor<2x12x64xf32>, tensor<2xi32>) -> tensor<2x768xf32>
  return %405 : tensor<2x768xf32>
  // CHECK: %cst = arith.constant dense_resource<__elided__> : tensor<3xi32>
  // CHECK: %cst_0 = arith.constant dense_resource<__elided__> : tensor<2xi32>

  func.return %result : tensor<10x8x24x24x64xf32>
}

// -----

// CHECK-LABEL: @max_pool_grad_same
func.func @max_pool_grad_same(%orig_input: tensor<2x13x25x7xf32>, %orig_output: tensor<2x4x7x7xf32>, %grad: tensor<2x4x7x7xf32>) -> tensor<2x13x25x7xf32> {
  // CHECK: padding = dense<{{\[\[}}0, 0], [0, 1], [1, 1], [0, 0]]> : tensor<4x2xi64>
  %result = "tf.MaxPoolGrad"(%orig_input, %orig_output, %grad) {
     data_format = "NHWC",

// CHECK: return %[[TRANSPOSE]]

// -----

// Tests that a float `stablehlo.transpose` is not converted to `tfl.transpose`.

func.func @transpose_float(%arg0: tensor<2x3x4xf32>) -> tensor<4x3x2xf32> {
  %0 = stablehlo.transpose %arg0, dims = [2, 1, 0] : (tensor<2x3x4xf32>) -> tensor<4x3x2xf32>
  return %0 : tensor<4x3x2xf32>
}
// CHECK-LABEL: transpose_float
// CHECK-NOT: tfl.transpose
// CHECK: stablehlo.transpose

// -----

//   %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: tf.Reshape
    // CHECK-SAME: tensor<1x3x7xf32>
    %1 = "tf.Reshape"(%arg1, %0) : (tensor<3x7xf32>, tensor<3xi32>) -> tensor<*xf32>
    return %1 : tensor<*xf32>
  }

  // CHECK-LABEL: func @gather_concat_reshape
  func.func @gather_concat_reshape(%arg0: tensor<?x1x7xf32>, %arg1: tensor<?x7xf32>) -> tensor<*xf32> {
    %0 = "tf.Shape"(%arg0) : (tensor<?x1x7xf32>) -> tensor<3xi32>