// Canonicalization includes const folding, which is utilized here to optimize
  // away ops that can't get constant folded after PrepareTF pass. For example,
  // tf.Conv2D is split into tf.Transpose and tfl.Conv2D.
  pass_manager->addNestedPass<mlir::func::FuncOp>(
      mlir::createCanonicalizerPass());
  pass_manager->addNestedPass<mlir::func::FuncOp>(mlir::createCSEPass());

    const auto float_graph = model_->subgraphs()->Get(subgraph_idx);
    ASSERT_EQ(quantized_graph->tensors()->size(),
              float_graph->tensors()->size());
    // Make sure the graph only has one Conv operation.
    ASSERT_EQ(quantized_graph->operators()->size(), 1);
    const auto op = quantized_graph->operators()->Get(0);
    const uint32_t op_code_idx = op->opcode_index();