// CHECK-DAG: "tf.PadV2"(%arg0, {{.*}}, {{.*}}) {{.*}} -> tensor<3x?x?x10xf16>
  // CHECK-DAG: return {{.*}}: tensor<?x?x?x10xf16>
  %0 = "tf.SpaceToBatchND"(%input, %block_shape, %paddings) : (tensor<3x5x7x10xf16>, tensor<2xi64>, tensor<2x2xi64>) -> tensor<?x?x?x10xf16>
  func.return %0 : tensor<?x?x?x10xf16>
}

// Verify the result shape for the tf.PadV2 op.

// Float16-DAG: %[[b:.*]] = arith.constant dense<0.000000e+00> : tensor<16xf16>
// Float16-DAG: %[[const:.*]] = "tfl.no_value"() <{value}> : () -> none
// Float16-DAG: %[[dq_w:.*]] = "tfl.dequantize"(%[[w]]) : (tensor<3x3x3x8x16xf16>) -> tensor<3x3x3x8x16xf32>
// Float16-DAG: %[[dq_b:.*]] = "tfl.dequantize"(%[[b]]) : (tensor<16xf16>) -> tensor<16xf32>

    // CHECK: %cst_0 = arith.constant dense<[1, 1, 1, 128]> : tensor<4xi32>
    // CHECK: %cst_1 = arith.constant dense<[8, 1]> : tensor<2xi32>
    // CHECK: %0 = "tfl.reshape"(%arg0, %cst_1) : (tensor<1x8xf32>, tensor<2xi32>) -> tensor<8x1xf32>
    // CHECK: %1 = tfl.mul(%0, %cst) <{fused_activation_function = "NONE"}> : (tensor<8x1xf32>, tensor<8x16xf32>) -> tensor<8x16xf32>