// CHECK: %[[VAL_0:.*]] = "tf._FusedConv2D"(%arg2, %arg1, %arg0) <{data_format = "NHWC", dilations = [1, 1, 1, 1], epsilon = 0.000000e+00 : f32, explicit_paddings = [], fused_ops = ["BiasAdd"], num_args = 1 : i64, operandSegmentSizes = array<i32: 1, 1, 1, 0>, padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true}> {TArgs = [f32]} : (tensor<8x32x32x3xf32>, tensor<1x1x3x128xf32>, tensor<128xf32>) -> tensor<*xf32>...

    if (bias_add_op) rewriter.setInsertionPoint(bias_add_op);

    Value fused_op = rewriter.create<FusedOpT>(fused_loc, result_type,
                                               ValueRange(operands), attrs);
    auto op_to_replace = fuse_activation ? activation : bias_add;
    rewriter.replaceOp(op_to_replace, ValueRange({fused_op}));
    return success();
  }
};

const char kDeviceAttr[] = "device";

  %conv2d = "tf._FusedConv2D"(%input, %filter, %bias, %act, %input_scale, %side_input_scale) {
    data_format = "NHWC", dilations = [1, 1, 1, 1], epsilon = 9.99999974E-5 : f32, explicit_paddings = [], filter_format = "HWIO", fused_ops = ["BiasAdd", "Relu"], leakyrelu_alpha = 2.000000e-01 : f32, num_args = 2 : i64, operandSegmentSizes = array<i32: 1, 1, 2, 2>, padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true

        batchInputOp.getNumParallelCalls(), rewriter.getBoolAttr(false));

    if (op.getMetadata() != batchInputOp.getMetadata()) {
      return failure();
    }

    auto fused_op = rewriter.create<MapAndBatchDatasetOp>(
        op.getLoc(), op.getType(), batchInputOp.getInputDataset(),
        batchInputOp.getOtherArguments(), op.getBatchSize(),
        num_parallel_calls_op.getY(), op.getDropRemainder(),

#include "tensorflow/cc/ops/sparse_ops.h"
#include "tensorflow/cc/ops/state_ops.h"
#include "tensorflow/cc/ops/string_ops.h"
#include "tensorflow/cc/ops/training_ops.h"
#include "tensorflow/cc/ops/user_ops.h"

  toco_flags.set_reduce_type_precision(reduce_type_precision);
  // Read list of user select ops.
  llvm::SmallVector<llvm::StringRef, 2> user_ops;
  (llvm::StringRef(select_user_tf_ops))
      .split(user_ops, ',', /*MaxSplit=*/-1,
             /*KeepEmpty=*/false);
  llvm::for_each(user_ops, [&toco_flags](llvm::StringRef op_name) {
    *(toco_flags.add_select_user_tf_ops()) = op_name.str();
  });

  std::string result;

that follows is specified by the `fused_ops` attribute, which is a list of TF op
names specified as strings (e.g. "Relu"). They are performed in order, where the
(first) input to each op is the output of the preceding op. The first input and
the output of each fused_op must be of type T.

Currently supported fused_op combinations are: [X] and [X,A], where X is one of

        "manip_ops",
        "nn_ops",
        "no_op",
        "parsing_ops",
        "random_ops",
        "sparse_ops",
        "state_ops",
        "string_ops",
        "training_ops",
        "user_ops",
    ],
    other_hdrs = [
        "ops/array_ops.h",
        "ops/const_op.h",
        "ops/math_ops.h",
        "ops/dataset_ops.h",
        "ops/experimental_dataset_ops.h",