tbl_outs = [
        (
            ["-gen-op-decls"],
            "ir/tfr_ops.h.inc",
        ),
        (
            ["-gen-op-defs"],
            "ir/tfr_ops.cc.inc",
        ),
    ],
    tblgen = "@llvm-project//mlir:mlir-tblgen",
    td_file = "ir/tfr_ops.td",
    deps = [
        ":tfr_ops_td_files",
    ],
)

gentbl_cc_library(
    name = "tfr_decompose_inc_gen",

	klogLevel = 5

	// noshell holds a path to a binary to disable shell login.
	noshell = "/bin/false"

	// These are constants for the default system paths on Linux.
	fileEtcLoginDefs = "/etc/login.defs"
	fileEtcPasswd    = "/etc/passwd"
	fileEtcGroup     = "/etc/group"
)

var (
	// these entries hold the users and groups to create as defined in:

// "__imp_XXX" a references to "XXX", however this doesn't work well
// with more modern compilers, where you can sometimes see import
// symbols that are defs (as opposed to external refs).
//
// The main actions taken below are to search for references to
// SDYNIMPORT symbols in host object text/data sections and flag the
// symbols for later fixup. When we see a reference to an import

    linkshared = 1,
    linkstatic = 1,
    deps = tf_custom_op_library_additional_deps_impl(),
)

# Get a DEF file generated by parsing all object files
# of tf_custom_op_library_additional_deps.so
filegroup(
    name = "tensorflow_def_file",
    srcs = [":tf_custom_op_library_additional_deps.dll"],
    output_group = "def_file",
)

# Filter the DEF file to reduce the number of symbols to 64K or less.

        (
            ["-gen-op-decls"],
            "passes/tf_quant_ops.h.inc",
        ),
        (
            ["-gen-op-defs"],
            "passes/tf_quant_ops.cc.inc",
        ),
    ],
    tblgen = "@llvm-project//mlir:mlir-tblgen",
    td_file = "passes/tf_quant_ops.td",
    deps = [
        ":quant_td_files",
    ],
)

gentbl_cc_library(
    name = "optimize_inc_gen",

	// Is this a block of known links? Handle.
	var defs []*LinkDef
	for _, line := range lines {
		def, ok := parseLink(line)
		if !ok {
			goto NoDefs
		}
		defs = append(defs, def)
	}
	for _, def := range defs {
		d.Links = append(d.Links, def)
		if d.links[def.Text] == nil {
			d.links[def.Text] = def
		}
	}
	return nil
NoDefs:

#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/ops/array_ops.h"
#include "tensorflow/cc/ops/resource_variable_ops.h"
#include "tensorflow/cc/ops/standard_ops.h"
#include "tensorflow/compiler/jit/defs.h"
#include "tensorflow/compiler/jit/encapsulate_subgraphs_pass.h"
#include "tensorflow/compiler/jit/node_matchers.h"
#include "tensorflow/compiler/jit/test_util.h"
#include "tensorflow/core/common_runtime/device_factory.h"

        }
      }
    }

    NodeDef def;
    def.set_name(launch->name());
    MergeDebugInfo(NodeDebugInfo(launch->def()), &def);

    // Target the XLA CPU/GPU backends.
    VLOG(2) << "Replacing with XlaLaunch";
    VLOG(2) << "Device is " << launch->requested_device();
    def.set_op("XlaLaunch");
    def.set_device(launch->requested_device());

  //  in TensorFlow op def but it could have an empty value to represent missing
  //  functions. This value can't be represented using MLIR SymbolRefAttr and
  //  instead uses optional symbol ref attribute.
  //
  // TODO(b/182315488): Remove custom handling by finding a better
  // representation in MLIR for empty function names. One option could be to use

		return
	}
	id, isId := e.(*ast.Ident)
	if isId && id.Name == "_" {
		return
	}

	var typ types.Type
	if rtok == token.DEFINE {
		if !isId {
			return
		}
		obj := pass.TypesInfo.Defs[id]
		if obj == nil {
			return
		}
		typ = obj.Type()
	} else {
		typ = pass.TypesInfo.Types[e].Type
	}

	if typ == nil {
		return
	}