text(
        "profiler",
        defaultProfiler,
        display = ParameterDisplay.PROMPT,
        allowEmpty = false,
        description =
            "Command line option for the performance test task to enable profiling. " +
                "For example `async-profiler`, `async-profiler-heap`, `async-profiler-all` or `jfr`. Use `none` for benchmarking only.",
    )
}

                    val arch = if (os == Os.MACOS) Arch.AARCH64 else Arch.AMD64
                    if (os == Os.WINDOWS) {
                        listOf("jprofiler")
                    } else {
                        listOf("async-profiler", "async-profiler-heap")
                    }.map { FlameGraphGenerationBuildSpec(scenario, os, arch, it) }
                }
            }

                    "Flame graphs with $profiler for ${performanceScenario.scenario.scenario} | ${performanceScenario.testProject} " +
                        "on ${os.asName()} (bucket $bucketIndex)",
                performanceSubProject = "performance",
                bucketIndex = bucketIndex,
                extraParameters =

        "//tensorflow/core/platform:stringpiece",
        "//tensorflow/core/platform:types",
        "//tensorflow/core/profiler/internal:print_model_analysis",
        "//tensorflow/core/profiler/lib:traceme",
        "//tensorflow/core/profiler/rpc/client:profiler_client_impl",
        "//tensorflow/core/profiler/rpc:profiler_server_impl",
        "//tensorflow/core/util:managed_stack_trace",
        "//tensorflow/core:all_kernels",

    analyzing input pipeline performance with TF Profiler.

*   [`tf.distribute.TPUStrategy`](https://www.tensorflow.org/api_docs/python/tf/distribute/TPUStrategy)
    is now a stable API and no longer considered experimental for TensorFlow.
    (earlier `tf.distribute.experimental.TPUStrategy`).

*   [TF Profiler](https://www.tensorflow.org/guide/profiler) introduces two new
    tools: a memory profiler to visualize your model’s memory usage over time

if [[ `uname -s | grep -P '^MSYS_NT'` ]]; then
  PROFILE_JSON_PATH=$(replace_drive_letter_with_prefix "$TFCI_OUTPUT_WIN_DOCKER_DIR")
  PROFILE_JSON_PATH="$PROFILE_JSON_PATH/profile.json.gz"
else
  PROFILE_JSON_PATH="$TFCI_OUTPUT_DIR/profile.json.gz"
fi

# TODO(b/361369076) Remove the following block after TF NumPy 1 is dropped
# Move hermetic requirement lock files for NumPy 1 to the root

        androidHome = "/opt/android/sdk",
        jprofilerHome = "/opt/jprofiler/jprofiler11.1.4",
    ),
    ALPINE(
        "Linux",
        androidHome = "/not/supported",
        jprofilerHome = "/not/supported",
    ),
    WINDOWS(
        "Windows",
        androidHome = """C:\Program Files\android\sdk""",
        jprofilerHome = """C:\Program Files\jprofiler\jprofiler11.1.4""",
        perfTestWorkingDir = "P:/",
    ),

import java.util.ArrayList;
import java.util.List;

import org.codelibs.core.io.ResourceUtil;

public class ProfileUtil {
    private static final String SPRING_PROFILES_ACTIVE = "spring.profiles.active";

    public static void setup() {
        final List<String> list = new ArrayList<String>();

        final String values = System.getProperty(SPRING_PROFILES_ACTIVE);
        if (values != null) {

            applyDefaultSettings(artifactRuleOverride = "")

            params {
                // Disable jdk-provider-plugin, otherwise the JAVA_HOME will be overwritten
                // https://github.com/gradle/teamcity-jdk-provider-plugin/blob/main/teamcity-jdk-provider-plugin-agent/src/main/kotlin/org/gradle/teamcity_jdk_provider_plugin/JdkProviderAgentLifecycleListener.kt#L22

<component name="InspectionProjectProfileManager">
  <profile version="1.0">
    <option name="myName" value="Gradle" />
    <inspection_tool class="21f28a86-2ba8-3048-9ce1-b6f10d4d4a12" enabled="true" level="WEAK WARNING" enabled_by_default="true" editorAttributes="INFO_ATTRIBUTES" />
    <inspection_tool class="73cd39e8-e54e-3a38-ad1b-b883fff4b1eb" enabled="true" level="WEAK WARNING" enabled_by_default="true" editorAttributes="INFO_ATTRIBUTES" />