[[ ! -s $BATS_TEST_TMPDIR/out ]]
}

@test "Pip package doesn't depend on CUDA for static builds (i.e. Windows)" {
  bazel cquery \
    --experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --define framework_shared_object=false \
    "somepath(//tensorflow/tools/pip_package:build_pip_package, " \
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\

  // driver can be mounted separately with different `-o context` options. This is
  // typical for storage backends that provide volumes as filesystems on block
  // devices or as independent shared volumes.
  // Kubernetes will call NodeStage / NodePublish with "-o context=xyz" mount
  // option when mounting a ReadWriteOncePod volume used in Pod that has

load("//tensorflow:tensorflow.bzl", "get_win_copts", "tf_cc_shared_object", "tf_cc_test")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

# Filesystem implementation for GCS environments
tf_cc_shared_object(
    name = "gcs_filesystem",
    framework_so = [],
    linkstatic = False,

	// and we harm no one by doing so.
	copiedFiles, err := copyBinaries(in.cfg.CNIBinSourceDir, in.cfg.CNIBinTargetDirs)
	if err != nil {
		cniInstalls.With(resultLabel.Value(resultCopyBinariesFailure)).Increment()
		return copiedFiles, fmt.Errorf("copy binaries: %v", err)
	}

	// Install kubeconfig (if needed) - we write/update this in the shared node CNI netdir,

dependencies {
    implementation("gradlebuild:basics")

    implementation(project(":dependency-modules"))
    implementation(project(":jvm"))
    implementation(project(":kotlin-dsl-shared-runtime"))

    implementation("org.gradle.kotlin:gradle-kotlin-dsl-conventions")
    implementation(kotlin("gradle-plugin"))
    implementation(kotlin("sam-with-receiver"))
    implementation("org.ow2.asm:asm")

)

# Crosses between framework_shared_object and a bunch of other configurations
# due to limitations in nested select() statements.
config_setting(
    name = "framework_shared_object",
    define_values = {"framework_shared_object": "true"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "macos_x86_64_with_framework_shared_object",
    define_values = {

   * the internal list.
   */
  @JvmStatic
  fun fragmentBuffer(buffer: Buffer): Buffer {
    // Write each byte into a new buffer, then clone it so that the segments are shared.
    // Shared segments cannot be compacted so we'll get a long chain of short segments.
    val result = Buffer()
    while (!buffer.exhausted()) {
      val box = Buffer()
      box.write(buffer, 1)

Now, let's imagine your organization gave you the `app/internal/admin.py` file.

It contains an `APIRouter` with some admin *path operations* that your organization shares between several projects.

For this example it will be super simple. But let's say that because it is shared with other projects in the organization, we cannot modify it and add a `prefix`, `dependencies`, `tags`, etc. directly to the `APIRouter`:

  AbstractFunctionKind getKind() const { return kind_; }

  // Returns the AbstractFunction as a FunctionDef.
  virtual Status GetFunctionDef(const FunctionDef**) = 0;

  // Returns a shared reference to the wrapped function.
  virtual absl::StatusOr<core::RefCountPtr<FunctionRecord>>
  GetFunctionRecord() = 0;

 private:
  const AbstractFunctionKind kind_;
};

using AbstractFunctionPtr =

			},
		},
		Relation{
			Name: "SharedTags", Type: schema.Many2Many, Schema: "Blog", FieldSchema: "Tag",
			JoinTable: JoinTable{Name: "shared_blog_tags", Table: "shared_blog_tags"},
			References: []Reference{
				{"ID", "Blog", "BlogID", "shared_blog_tags", "", true},
				{"ID", "Tag", "TagID", "shared_blog_tags", "", false},
			},
		},
		Relation{
			Name: "LocaleTags", Type: schema.Many2Many, Schema: "Blog", FieldSchema: "Tag",