licenses = ["notice"],
)

filegroup(
    name = "srcs_no_runtime",
    srcs = [
        "framework/gradients.h",
        "framework/ops.h",
        "framework/scope.h",
        "framework/scope_internal.h",
        "//tensorflow/cc/saved_model:loader.h",
    ],
)

filegroup(
    name = "srcs",
    srcs = [
        "framework/gradients.h",
        "framework/ops.h",
        "framework/scope.h",

package(default_visibility = ["//visibility:public"])

filegroup(
    name = "gcc",
    srcs = glob(["bin/*-gcc"]),
)

filegroup(
    name = "ar",
    srcs = glob(["bin/*-ar"]),
)

filegroup(
    name = "ld",
    srcs = glob(["bin/*-ld"]),
)

filegroup(
    name = "nm",
    srcs = glob(["bin/*-nm"]),
)

filegroup(
    name = "objcopy",
    srcs = glob(["bin/*-objcopy"]),
)

filegroup(
    name = "objdump",

    public OrSpec() {
        super();
    }

    public OrSpec(Spec<? super T>... specs) {
        super(specs);
    }

    public OrSpec(Iterable<? extends Spec<? super T>> specs) {
        super(specs);
    }

    @Override
    public boolean isSatisfiedBy(T object) {
        Spec<? super T>[] specs = getSpecsArray();
        if (specs.length == 0) {
            return true;
        }

        Specs.intersect([spec1, Specs.satisfyAll(), spec2]).specs == [spec1, spec2]
        Specs.intersect(spec1, Specs.satisfyAll()) == spec1
        Specs.intersect([spec1, Specs.satisfyAll()]) == spec1
        Specs.intersect(spec1, Specs.satisfyAll(), Specs.satisfyAll()) == spec1
        Specs.intersect([spec1, Specs.satisfyAll(), Specs.satisfyAll()]) == spec1
    }

        return doIntersect(specs);
    }

    private ExcludeSpec doUnion(Set<ExcludeSpec> specs) {
        specs = simplifySet(ExcludeAllOf.class, specs);
        FlattenOperationResult flattened = flatten(ExcludeAnyOf.class, specs, ExcludeEverything.class::isInstance, ExcludeNothing.class::isInstance);
        if (flattened.fastExit) {
            return everything();
        }

filegroup(
    name = "lib_headers",
    srcs = ["parallel_device_lib.h"],
)

filegroup(
    name = "lib_sources",
    srcs = ["parallel_device_lib.cc"],
)

filegroup(
    name = "device_headers",
    srcs = ["parallel_device.h"],
)

filegroup(
    name = "device_sources",
    srcs = ["parallel_device.cc"],
)

filegroup(
    name = "headers",
    srcs = [
        ":device_headers",

        "@absl_py//absl:app",
        "@absl_py//absl/flags",
    ],
)

filegroup(
    name = "testdata",
    srcs = glob([
        "tests/testdata/**",
    ]),
)

tf_cc_test(
    name = "libtf_object_test",
    size = "medium",
    srcs = ["tests/object_test.cc"],
    deps = [
        ":libtf",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",

import org.gradle.api.internal.artifacts.ivyservice.resolveengine.excludes.specs.ExcludeEverything;
import org.gradle.api.internal.artifacts.ivyservice.resolveengine.excludes.specs.ExcludeNothing;
import org.gradle.api.internal.artifacts.ivyservice.resolveengine.excludes.specs.ExcludeSpec;
import org.gradle.api.internal.artifacts.ivyservice.resolveengine.excludes.specs.GroupExclude;

			return conf
		}
		db := trimSpace(line[:colon])
		srcs := line[colon+1:]
		for {
			srcs = trimSpace(srcs)
			if len(srcs) == 0 {
				break
			}
			sp := bytealg.IndexByteString(srcs, ' ')
			var src string
			if sp == -1 {
				src = srcs
				srcs = "" // done
			} else {
				src = srcs[:sp]
				srcs = trimSpace(srcs[sp+1:])
			}
			var criteria []nssCriterion

pytype_strict_library(
    name = "calibration_algorithm",
    srcs = ["calibration_algorithm.py"],
    deps = [
        ":calibration_statistics_proto_py",
        "//tensorflow/compiler/mlir/quantization/stablehlo:quantization_config_proto_py",
        "//third_party/py/numpy",
    ],
)

pytype_strict_contrib_test(
    name = "calibration_algorithm_test",
    srcs = ["calibration_algorithm_test.py"],
    deps = [