<jsp:param name="menuType" value="labelType"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.labeltype_configuration"/>

        <jsp:param name="menuType" value="dataConfig"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.data_crawling_title_details"/>

        <jsp:param name="menuType" value="design"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.design_configuration"/>
                        </h1>

import org.apache.maven.api.annotations.Nonnull;
import org.apache.maven.api.annotations.Nullable;
import org.apache.maven.api.annotations.Provider;
import org.apache.maven.api.annotations.ThreadSafe;

/**
 * A container for data that is specific to a session.
 * All components may use this storage to associate arbitrary data with a session.
 * <p>

                    : Map.of();
        } catch (LookupException e) {
            throw new IllegalStateException("Unable to lookup lifecycles from the plexus container", e);
        }
    }

    public String getLifecyclePhaseList() {
        return getLifeCycles().stream().flatMap(l -> l.getPhases().stream()).collect(Collectors.joining(", "));
    }

# different compilation methods. E.g. for a PR to test a new CUDA version, set
# the CACHEBUSTER to the PR number.
build --action_env=CACHEBUSTER=20220325

# Use Python 3.X as installed in container image
build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
build --python_path="/usr/local/bin/python3"

# Build TensorFlow v2
build --define=tf_api_version=2 --action_env=TF2_BEHAVIOR=1

        <jsp:param name="menuType" value="scheduler"/>
    </jsp:include>
    <div class="content-wrapper">
        <div class="content-header">
            <div class="container-fluid">
                <div class="row mb-2">
                    <div class="col-sm-6">
                        <h1>
                            <la:message key="labels.scheduledjob_title_details"/>

// graph_def.library().gradient()
std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def);

// Returns a sorted vector of names contained in `grad_def`
std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def);

class CSession {
 public:
  CSession(TF_Graph* graph, TF_Status* s, bool use_XLA = false);

import logging
import subprocess
import sys
from collections import Counter, defaultdict
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any, Container, DefaultDict, Dict, List, Set, Union

import httpx
import yaml
from github import Github
from pydantic import BaseModel, SecretStr
from pydantic_settings import BaseSettings

github_graphql_url = "https://api.github.com/graphql"

/// info

如果你使用 Kubernetes，这可能是 <a href="https://kubernetes.io/docs/concepts/workloads/pods/init-containers/" class="external-link" target="_blank">Init Container</a>。

///

如果在你的用例中，运行前面的步骤**并行多次**没有问题（例如，如果你没有运行数据库迁移，而只是检查数据库是否已准备好），那么你也可以将它们放在开始主进程之前在每个容器中。

### 单容器