%0 = "tf.ExpandDims"(%arg0, %cst) {device = ""} : (tensor<8x64xf32>, tensor<i32>) -> tensor<8x64x1xf32>
  %1 = "tf.AddV2"(%0, %arg1) {device = ""} : (tensor<8x64x1xf32>, tensor<8x64x64xf32>) -> tensor<8x64x64xf32>
  %2 = "tf.Transpose"(%1, %cst_1) {device = ""} : (tensor<8x64x64xf32>, tensor<3xi32>) -> tensor<64x8x64xf32>
  %3 = "tf.Reshape"(%2, %cst_2) {device = ""} : (tensor<64x8x64xf32>, tensor<2xi32>) -> tensor<512x64xf32>

  func.return %2 : tensor<4x4x4xf32>
}

func.func @testSingleLstmFloat16(%arg0: tensor<4x4xf32>, %arg1: tensor<4xf32>, %arg2: tensor<4x4x4xf32>) -> tensor<4x4x4xf32> {
  // CHECK-LABEL: testSingleLstm
  // CHECK-DAG:  %[[CST_0:.*]] = "tfl.pseudo_const"() <{value = dense<0.000000e+00> : tensor<4x4xf16>}> : () -> tensor<4x4xf16>

module {
func.func @main(%arg0: tensor<4x68x68x3xf32>, %arg1: tensor<5x5x3x8xf32>) -> tensor<4x64x64x8xf32> {
  %0 = "tf.Conv2D"(%arg0, %arg1) {padding = "VALID", strides = [1, 1, 1, 1]} : (tensor<4x68x68x3xf32>, tensor<5x5x3x8xf32>) -> tensor<4x64x64x8xf32>
  func.return %0 : tensor<4x64x64x8xf32>
}