func.func @reshape_vector_shape(tensor<4x4x4xf32>) -> tensor<16x4xf32> {
^bb0(%arg0: tensor<4x4x4xf32>) :
  %shape0 = arith.constant dense<[[16, 4]]> : tensor<1x2xi32>
  // expected-error @+1 {{'tfl.reshape' op requires 'shape' to be rank 1, but got 2}}
  %1 = "tfl.reshape"(%arg0, %shape0) : (tensor<4x4x4xf32>, tensor<1x2xi32>) -> tensor<16x4xf32>
  func.return %1 : tensor<16x4xf32>
}

// -----

  %3 = stablehlo.uniform_quantize %2 : (tensor<1x2x!quant.uniform<i32:f32:1, {2.000000e+00, 2.000000e+00}>>) -> tensor<1x2x!quant.uniform<i8:f32, 4.000000e+00:7>>
  return %3 : tensor<1x2x!quant.uniform<i8:f32, 4.000000e+00:7>>
}

func.func @fuseTileWithBinaryOp(%arg0: tensor<1x1xf32>) -> tensor<1x2xf32> {
  %cst = arith.constant dense<[[1,2]]> : tensor<1x2xi32>
  %cst1 = arith.constant dense<[[3.0, 4.0]]> : tensor<1x2xf32>
  %0 = "tfl.sqrt"(%arg0) : (tensor<1x1xf32>) -> tensor<1x1xf32>
  %1 = "tfl.tile"(%0, %cst) : (tensor<1x1xf32>, tensor<1x2xi32>) -> tensor<1x2xf32>

// CHECK: %[[Q1:.*]] =  "tfl.quantize"(%arg1) <{qtype = tensor<1x2x!quant.uniform<u8:f32, 1.000000e-01:128>>}> {volatile}
// CHECK: %[[DQ1:.*]] = "tfl.dequantize"(%[[Q1]]) : (tensor<1x2x!quant.uniform<u8:f32, 1.000000e-01:128>>) -> tensor<1x2xf32>
// CHECK: %[[RQ0:.*]] = "tfl.quantize"(%arg0) <{qtype = tensor<1x2x!quant.uniform<u8:f32, 1.000000e-01:128>>}> : (tensor<1x2x!quant.uniform<u8:f32, 2.000000e+00:128>>) -> tensor<1x2x!quant.uniform<u8:f32, 1.000000e-01:128>>