#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace cc_op {

// String with single fuzzer file content.
string WriteSingleFuzzer(const OpInfo& op_info, bool is_fuzzable);

// Do we have all we need to create a fuzzer
bool OpFuzzingIsOk(const OpInfo& op_info);

}  // namespace cc_op
}  // namespace tensorflow

#include "tensorflow/core/platform/statusor.h"
#include "tensorflow/core/platform/str_util.h"
#include "tensorflow/core/platform/types.h"
#include "tsl/platform/status.h"

namespace tensorflow {
namespace cc_op {
namespace {

void WriteAllFuzzers(string root_location, std::vector<string> api_def_dirs,
                     std::vector<string> op_names) {
  OpList ops;
  absl::StatusOr<ApiDefMap> api_def_map =

#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace cc_op {
/// Result is written to files dot_h and dot_cc.
void WriteCCOps(const OpList& ops, const ApiDefMap& api_def_map,
                const string& dot_h_fname, const string& dot_cc_fname);

}  // namespace cc_op
}  // namespace tensorflow

        return true;
      }

      // Check if the preceding op is a quantized same-scale op.
      if (llvm::isa<quantfork::StorageCastOp>(preceding_op)) {
        auto sc_op = llvm::cast<quantfork::StorageCastOp>(preceding_op);
        auto sc_arg_type = sc_op.getArg().getType().dyn_cast<TensorType>();
        if (sc_arg_type.getElementType().isInteger(8)) {
          return true;
        }
      }
    }

    TFL::FullyConnectedOp fc_op, PatternRewriter& rewriter) const {
  // We have to know the shape of the input.
  auto input = fc_op.getInput();
  auto input_type = mlir::dyn_cast_or_null<RankedTensorType>(input.getType());
  if (!input_type || !input_type.hasStaticShape()) return failure();

  // We have to know the shape of the weight.
  auto weight = fc_op.getFilter();

  "ArrayRef<APInt>{$0.getValue(), $0.getValue()})">;

def BatchToSpaceToBatchToSpaceND : Pat<
  (TF_BatchToSpaceOp:$src $input, $crops, $block_size),
  (TF_BatchToSpaceNDOp:$dest $input,
    (TF_ConstOp (BatchToSpaceBlockSizeToBlockShape $block_size)), $crops),
  [(IsRank4Tensor $input), (IsRank2Tensor $crops)], [(CopyAttrs $src, $dest)]>;

//===----------------------------------------------------------------------===//

gentbl_cc_library(
    name = "tf_ops_inc_gen",
    tbl_outs = [
        (
            ["-gen-op-decls"],
            "tf_ops.h.inc",
        ),
        (
            ["-gen-op-defs"],
            "tf_ops.cpp.inc",
        ),
    ],
    tblgen = "@llvm-project//mlir:mlir-tblgen",
    td_file = "tf_ops.td",
    deps = [":tf_mlrt_td_files"],
)

cc_library(
    name = "tf_mlrt_ops",

        "//tensorflow/cc:cc_ops",
        "//tensorflow/cc:cc_ops_internal",
        "//tensorflow/cc:function_ops",
        "//tensorflow/cc:functional_ops",
        "//tensorflow/cc:ops",
        "//tensorflow/cc:resource_variable_ops",
        "//tensorflow/cc:sendrecv_ops",
        "//tensorflow/compiler/jit/kernels:xla_ops",
        "//tensorflow/compiler/tf2xla:xla_compiler",

      ('none', None, False, False, quant_opts_pb2.TF, False, 'SAME'),
      ('relu', nn_ops.relu, False, False, quant_opts_pb2.TF, False, 'SAME'),
      ('relu6', nn_ops.relu6, False, False, quant_opts_pb2.TF, False, 'SAME'),
      ('with_bias', None, True, False, quant_opts_pb2.TF, False, 'SAME'),
      (
          'with_bias_and_relu',
          nn_ops.relu,
          True,
          False,
          quant_opts_pb2.TF,

#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {
namespace cc_op {

absl::StatusOr<ApiDefMap> LoadOpsAndApiDefs(
    OpList& ops, bool include_internal,
    const std::vector<string>& api_def_dirs);

// Converts:
//   bazel-out/.../(bin|genfiles)/(external/YYY/)?XX
// to: XX.