} : (tensor<*xi32>, tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>

    func.return %out : tensor<*xf32>
  }

  // For weight-only
  func.func @dequantize_i8(%input : tensor<*xi8>, %scale : tensor<*xf32>, %zp : tensor<*xi32>) -> tensor<*xf32> {
    // Use identity op to avoid the weight being constant-folded.
    %identity = "tf.Identity"(%input) : (tensor<*xi8>) -> tensor<*xi8>

        // For not quantizable ops, search for dequantize attached to the
        // quantized op of the output.
        if (Operation* quantize_op = dyn_cast_or_null<QuantizeOpT>(
                *quantized_op->getResult(i).getUsers().begin())) {
          result = quantize_op->getResult(0);
        } else {
          quantized_op->emitError()
              << "Output[" << i

        support generators and Sequences.
*   `tf.lite`
    *   Legalization for `NMS` ops in TFLite.
    *   add `narrow_range` and `axis` to `quantize_v2` and `dequantize` ops.
    *   Added support for `FusedBatchNormV3` in converter.
    *   Add an `errno`-like field to `NNAPI` delegate for detecting `NNAPI`
        errors for fallback behaviour.