func.return %24 : tensor<1x4xf32>
}

func.func @cumsum(%arg0: tensor<3x3xf32>, %arg1: tensor<i32>) -> tensor<3x3xf32> {
  %0 = "tf.Cumsum"(%arg0, %arg1) {exclusive = false, reverse = false} : (tensor<3x3xf32>, tensor<i32>) -> tensor<3x3xf32>
  func.return %0 : tensor<3x3xf32>
  // CHECK-LABEL: cumsum
  // CHECK: "tfl.cumsum"(%arg0, %arg1) <{exclusive = false, reverse = false}> : (tensor<3x3xf32>, tensor<i32>) -> tensor<3x3xf32>
}

    %1 = arith.constant dense<[[2.3, 3.4, 4.5, 5.5]]> : tensor<1x4xf32>
    %2 = "tf.Add"(%0, %1) : (tensor<1x4xf32>, tensor<1x4xf32>) -> tensor<1x4xf32>
    %3 = tensor.cast %2 : tensor<1x4xf32> to tensor<1x?xf32>
    func.return %3 : tensor<1x?xf32>
}

// NOTE: Assertions have been autogenerated by utils/generate-test-checks.py
// CHECK-LABEL:   func @embedding(

  // CHECK: return %arg0
  func.return %0 : tensor<2x4xf32>
}

// CHECK-LABEL: func @testBroadcastToNoOp
func.func @testBroadcastToNoOp(%arg0: tensor<2x4xf32>, %arg1: tensor<2xi32>) -> tensor<2x4xf32> {
  %0 = "tf.BroadcastTo"(%arg0, %arg1) : (tensor<2x4xf32>, tensor<2xi32>) -> tensor<2x4xf32>

  // CHECK: return %arg0
  func.return %0 : tensor<2x4xf32>
}

func.func @testPackedTPUPartitionedInputV2(tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<4x4xf32> {
^bb0(%arg0: tensor<2x4xf32>, %arg1: tensor<2x4xf32>):
  // expected-error @+1 {{expected 1 inputs, got 2}}
  %0 = "tf.TPUPartitionedInputV2"(%arg0, %arg1) {partition_dims = [2, 1], is_packed = true} : (tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<4x4xf32>
  func.return %0 : tensor<4x4xf32>
}

// -----

    "tf.AssignVariableOp"(%arg0, %partitioned_output#0) : (tensor<!tf_type.resource<tensor<3x2xf32>>>, tensor<3x2xf32>) -> ()
    "tf.AssignVariableOp"(%arg1, %partitioned_output#1) : (tensor<!tf_type.resource<tensor<3x2xf32>>>, tensor<3x2xf32>) -> ()
    func.return
  }
  func.func @computation(%arg0: tensor<3x4xf32>) -> tensor<3x4xf32> {
    func.return %arg0: tensor<3x4xf32>
  }
}

// -----

// -----

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

func.func @reshape_float(%arg0: tensor<2x3x4xf32>) -> tensor<6x4xf32> {
  %0 = stablehlo.reshape %arg0 : (tensor<2x3x4xf32>) -> tensor<6x4xf32>
  return %0 : tensor<6x4xf32>
}
// CHECK-LABEL: reshape_float
// CHECK-NOT: tfl.reshape
// CHECK: stablehlo.reshape

// -----