],
)

cc_library(
    name = "gcs_helper",
    srcs = ["gcs_helper.cc"],
    hdrs = ["gcs_helper.h"],
    linkstatic = 1,
    deps = [
        "//tensorflow/c:env",
    ],
)

cc_library(
    name = "cleanup",
    hdrs = ["cleanup.h"],
)

cc_library(
    name = "ram_file_block_cache",
    srcs = ["ram_file_block_cache.cc"],
    hdrs = ["ram_file_block_cache.h"],
    deps = [

    ],
)

cc_library(
    name = "size_utils",
    srcs = [
        "utils/size_utils.cc",
    ],
    hdrs = [
        "utils/size_utils.h",
    ],
    deps = [
        "@llvm-project//mlir:IR",
    ],
)

tf_cc_test(
    name = "size_utils_test",
    size = "small",
    srcs = ["utils/size_utils_test.cc"],
    deps = [
        ":size_utils",

				drawPaletted(dst0, r, src, sp, false)
				return
			}
		}
	case *image.NRGBA:
		if op == Src && mask == nil {
			if src0, ok := src.(*image.NRGBA); ok {
				d0 := dst0.PixOffset(r.Min.X, r.Min.Y)
				s0 := src0.PixOffset(sp.X, sp.Y)
				drawCopySrc(
					dst0.Pix[d0:], dst0.Stride, r, src0.Pix[s0:], src0.Stride, sp, 4*r.Dx())
				return
			}
		}
	case *image.NRGBA64:

// tag::simple-params[]
val collection: FileCollection = layout.files(
    "src/file1.txt",
    File("src/file2.txt"),
    listOf("src/file3.csv", "src/file4.csv"),
    Paths.get("src", "file5.txt")
)
// end::simple-params[]

file("src").mkdirs()
file("src/dir1").mkdirs()
file("src/file1.txt").mkdirs()
file("src2").mkdirs()
file("src2/dir1").mkdirs()
file("src2/dir2").mkdirs()

// tag::closure[]
tasks.register("list") {

        "//platforms/darwinn/compiler:__subpackages__",
        "//tensorflow:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "quantization_lib",
    srcs = [
        "quantization_driver.cc",
        "quantization_interface.cc.inc",
        "quantization_utils.cc",
    ],
    hdrs = [
        "quantization_driver.h",
        "quantization_interface.h.inc",

    ],
)

cc_library(
    name = "legalize_utils",
    srcs = ["utils.cc"],
    hdrs = ["utils.h"],
    deps = [
        "@llvm-project//llvm:Support",
        "@llvm-project//mlir:IR",
        "@local_xla//xla/mlir_hlo",
    ],
)

cc_library(
    name = "test_utils",
    testonly = True,
    srcs = ["test_utils.cc"],
    hdrs = ["test_utils.h"],
    deps = [

        ":xla_cluster_formation",
        "@llvm-project//mlir:FuncDialect",
        "@llvm-project//mlir:IR",
        "@llvm-project//mlir:Pass",
    ],
)

cc_library(
    name = "verify_clustering_pass",
    srcs = [
        "verify_clustering_pass.cc",
    ],
    deps = [
        ":clustering_passes_inc_gen",
        "//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/compiler/mlir/tensorflow:attribute_utils",

tf_py_strict_test(
    name = "pywrap_quantize_model_test",
    srcs = [
        "pywrap_quantize_model_test.py",
    ],
    deps = [
        ":py_function_lib_py",
        ":pywrap_quantize_model",
        "//tensorflow:tensorflow_py",
        "//tensorflow/python/platform:client_testlib",
    ],
)

pytype_strict_library(
    name = "save_model",
    srcs = [
        "save_model.py",
    ],
    deps = [

    default_visibility = [
        "//tensorflow/compiler/mlir/quantization:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "mlir_dump",
    srcs = ["mlir_dump.cc"],
    hdrs = ["mlir_dump.h"],
    compatible_with = get_compatible_with_portable(),
    deps = [
        "@com_google_absl//absl/log",
        "@com_google_absl//absl/memory",

    default_visibility = [
        "//tensorflow/compiler/mlir/tf2xla/internal:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "dialect_detection_utils",
    srcs = [
        "dialect_detection_utils.cc",
    ],
    hdrs = [
        "dialect_detection_utils.h",
    ],
    deps = [
        "//tensorflow/compiler/mlir/tensorflow",
        "//tensorflow/core:framework",