%cst_1 = arith.constant dense<1> : tensor<i32>
  %dequant = "tfl.dequantize"(%arg1) : (tensor<1024x256x!quant.uniform<u8:f32, 0.038859266393324911:129>>) -> tensor<1024x256xf32>
  %split:2 = "tfl.split"(%cst_1, %dequant) {num_splits = 2 : i32} : (tensor<i32>, tensor<1024x256xf32>) -> (tensor<1024x128xf32>, tensor<1024x128xf32>)
  %0 = "tfl.transpose"(%split#0, %cst) : (tensor<1024x128xf32>, tensor<2xi32>) -> tensor<128x1024xf32>

    %cst_0 = "tf.Const"() {value = dense<2.000000e+00> : tensor<1024x2xf32>} : () -> tensor<1024x2xf32>
    %cst_1 = "tf.Const"() {value = dense<[2, 1024]> : tensor<2xi32>} : () -> tensor<2xi32>
    // Original identity preserved.
    %cst_identity = "tf.Identity"(%cst_0) {device = ""} : (tensor<1024x2xf32>) -> tensor<1024x2xf32>
    %0 = "tf.Reshape"(%cst_identity, %cst_1) : (tensor<1024x2xf32>, tensor<2xi32>) -> tensor<2x1024xf32>

// CHECK: return %[[v4]] : tensor<?x?x8x?xf32>
}

func.func @einsum_ellipsis(%arg0: tensor<1x512x128xf32>, %arg1: tensor<128x256xf32>) -> tensor<1x512x256xf32> {
  %0 = "tf.Einsum"(%arg0, %arg1) {device = "", equation = "...x,xy->...y"} : (tensor<1x512x128xf32>, tensor<128x256xf32>) -> tensor<1x512x256xf32>
  func.return %0 : tensor<1x512x256xf32>
// CHECK-LABEL: einsum_ellipsis

  func.return %0 : tensor<4x64x128xf32>
}

// CHECK-LABEL:   func @convert_gather_transpose(
// CHECK-SAME:                                   %[[VAL_0:.*]]: tensor<128x256xf32>,
// CHECK-SAME:                                   %[[VAL_1:.*]]: tensor<4x1xi32>) -> tensor<4x128xf32> {
// CHECK:           %[[VAL_2:.*]] = "tf.Const"{{.*}}value = dense<[1, 0]> : tensor<2xi64>