Your version is: java version "1.6.0_24". The correct version is: Java SE 1.6.

最新推荐文章于 2024-02-26 19:20:42 发布
最新推荐文章于 2024-02-26 19:20:42 发布
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分类专栏： 资料_转载 文章标签： java se ubuntu
本文详细介绍了如何解决Android编译过程中遇到的错误，即使用不正确的Java版本。通过检查和更正Java SDK版本，确保了Android项目的顺利编译。包括在Ubuntu 12.04上安装最新版Sun JDK的步骤。

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Wrong Java Version

I have the Java 6 OpenJDK, version 1.6.0_24. This meets the android Java requirement for 1.6.0, but I found (later in the build process) that Android really needs to be built by Sun’s Java SDK. In the meantime, the _24 suffix doesn’t check out in Android’s makefile, which produces the error  You are attempting to build with the incorrect version of java before exiting:

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Checking build tools versions...
************************************************************
You are attempting to build with the incorrect version
of java.
Your version is: java version "1.6.0_24".
The correct version is: Java SE 1.6.
Please follow the machine setup instructions at
    http://source.android.com/source/download.html
************************************************************
build/core/main.mk:131: *** stop.  Stop.

你可能之前安装过jdk1.6.0_33或其他版本，此时查看jdk 版本，

$ java -version
java version "1.6.0_24"
OpenJDK Runtime Environment (IcedTea6 1.11.5) (6b24-1.11.5-0ubuntu1~12.04.1)
OpenJDK 64-Bit Server VM (build 20.0-b12, mixed mode)

发现版本变成了OpenJDK，下文红色部分可以将更正jdk版本，使编译通过

make will display the error message, but continue compiling. However, compiling with OpenJDK will probably create problems later in the build process(in out/target/common/obj/APPS/CtsVerifier_intermediates/classes-full-debug.jar). To fix the problems, Sun’s Java SDK will need to be installed.

Installing the Sun Java 6 JDK in Ubuntu 12.04

To fix the make: *** [out/target/common/obj/APPS/CtsVerifier_intermediates/classes-full-debug.jar] Error 41, get the most recent Sun JDK from here. Once you’ve downloaded it, install it and run update-alternatives so your system uses the Sun JDK:

zhoulc@zhoulc-PC:~/work/tools $ chmod +x jdk-6u33-linux-x64.bin
zhoulc@zhoulc-PC:~/work/tools $ sudo ./jdk-6u33-linux-x64.bin

zhoulc@zhoulc-PC:~/work/tools$ sudo mv jdk1.6.0_33/ /usr/lib/jvm/
zhoulc@zhoulc-PC:~/work/tools$ sudo update-alternatives --install /usr/bin/java java /usr/lib/jvm/jdk1.6.0_33/bin/java 1
zhoulc@zhoulc-PC:~/work/tools$ sudo update-alternatives --install /usr/bin/javac javac /usr/lib/jvm/jdk1.6.0_33/bin/javac 1
zhoulc@zhoulc-PC:~/work/tools$ sudo update-alternatives --install /usr/bin/javaws javaws /usr/lib/jvm/jdk1.6.0_33/bin/javaws 1
zhoulc@zhoulc-PC:~/work/tools$ sudo update-alternatives --config java
There are 2 choices for the alternative java (providing /usr/bin/java).

  Selection    Path                                            Priority   Status
------------------------------------------------------------
* 0            /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/java   1061      auto mode
  1            /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/java   1061      manual mode
  2            /usr/lib/jvm/jdk1.6.0_33/bin/java                1         manual mode

Press enter to keep the current choice[*], or type selection number: 2
update-alternatives: using /usr/lib/jvm/jdk1.6.0_33/bin/java to provide /usr/bin/java (java) in manual mode.
zhoulc@zhoulc-PC:~/work/tools$ sudo update-alternatives --config javac
There are 2 choices for the alternative javac (providing /usr/bin/javac).

  Selection    Path                                         Priority   Status
------------------------------------------------------------
* 0            /usr/lib/jvm/java-6-openjdk-amd64/bin/javac   1061      auto mode
  1            /usr/lib/jvm/java-6-openjdk-amd64/bin/javac   1061      manual mode
  2            /usr/lib/jvm/jdk1.6.0_33/bin/javac            1         manual mode

Press enter to keep the current choice[*], or type selection number: 2
update-alternatives: using /usr/lib/jvm/jdk1.6.0_33/bin/javac to provide /usr/bin/javac (javac) in manual mode.
zhoulc@zhoulc-PC:~/work/tools$ sudo update-alternatives --config javaws
There are 3 choices for the alternative javaws (providing /usr/bin/javaws).

  Selection    Path                                              Priority   Status
------------------------------------------------------------
* 0            /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/javaws   1061      auto mode
  1            /usr/lib/jvm/java-6-openjdk-amd64/jre/bin/javaws   1061      manual mode
  2            /usr/lib/jvm/java-7-openjdk-amd64/jre/bin/javaws   1060      manual mode
  3            /usr/lib/jvm/jdk1.6.0_33/bin/javaws                1         manual mode

Press enter to keep the current choice[*], or type selection number: 3
update-alternatives: using /usr/lib/jvm/jdk1.6.0_33/bin/javaws to provide /usr/bin/javaws (javaws) in manual mode.
zhoulc@zhoulc-PC:~/work/tools$


To verify that the installation was successful, check Java’s version. It should now show that the Sun JDK is running instead of IcedTea:

zhoulc@zhoulc-PC:~/work/tools $ java -version
java version "1.6.0_33"
Java(TM) SE Runtime Environment (build 1.6.0_33-b04)
Java HotSpot(TM) 64-Bit Server VM (build 20.8-b03, mixed mode)

To revert the changes after Android has been compiled, run update-alternatives to switch back to OpenJDK.

Oracle EBS R12 整合ADF
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环境： ADF version: 11.1.1.6.0 Oracle EBS version: R12.2.3 程序的目的在于取得 EBS 登入时的用户相关信息。整个程序架构如下图： ADF 的程序面:Step 01: 在 ViewController 依序建立 Java Class：ConnectionProvider、EBizUtil、EBSWrapperFilter、以及存取用户信息的 ...
jdk1.6.0_24.tar.gz
04-12
jdk1.6 x64比较老的版本。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。
Your version is: java version "1.6.0_23". The correct version is: Java SE 1.6. 解决方法
ldinvicible的专栏
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转载自:http://blog.csdn.net/suwenqiang2011/article/details/7765914 图文说明" name="image_operate_51841324015679350" alt="(原创)编译Android源代码时遇到的问题（一） 图文说明" src="http://s3.sinaimg.cn/middle/6c0b2827tb42ce4ba528
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遇到的问题：Your version is: java version "1.6.0_27".The correct version is: Java SE 1.6. 解决方法：sudo add-apt-repository ppa:webupd8team/javasudo apt-get updatesudo apt-get install oracle-java6-installer
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micro9981的专栏
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原来编译android 2.3时用sudo apt-get install default-jdk安装jdk，android 2.3可以编译通过。今天编译android 4.0.3时提示如下错误：You are attempting to build with the incorrect versionof java. Your version is: java version "1.6.0_2...
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官方下载需要登录，此处用于保存方便下载，也可以方便给其他用户下载，此包为正版，版权为oracle所有。 JDK Windows jdk1.6.0_24版本 64位解压版 解压即用，不需要安装！
using yaml rules: yaml.safe_load() failed mapping values are not allowed here in "<unicode string>", line 7, column 20: Commit Version: 1.6.0-4-g7f85cfe Build Versio ...
03-31
fixed_file.write(correct_yaml_content.strip()) ``` 以上脚本展示了如何安全地打开一个 YAML 配置文件，并尝试将其内容转化为字典形式存储于变量之中。同时提供了简单的示范说明怎样构建合乎规范的新版 YAML ...
a1@1:~ $ sudo apt install -y code Reading package lists... Done Building dependency tree... Done Reading state information... Done code:arm64 is already the newest version (1.86.2-1707853305). You might want to run 'apt --fix-broken install' to correct these. The following packages have unmet dependencies: code:arm64 : Depends: libasound2:arm64 (>= 1.0.17) but it is not installable Depends: libatk-bridge2.0-0:arm64 (>= 2.5.3) but it is not installable Depends: libatk1.0-0:arm64 (>= 2.2.0) but it is not installable Depends: libatspi2.0-0:arm64 (>= 2.9.90) but it is not installable Depends: libc6:arm64 (>= 2.17) but it is not installable Depends: libc6:arm64 (>= 2.28) but it is not installable Depends: libcairo2:arm64 (>= 1.6.0) but it is not installable Depends: libcurl3-gnutls:arm64 but it is not installable or libcurl3-nss:arm64 but it is not installable or libcurl4:arm64 but it is not installable or libcurl3:arm64 but it is not installable Depends: libdbus-1-3:arm64 (>= 1.9.14) but it is not installable Depends: libdrm2:arm64 (>= 2.4.75) but it is not installable Depends: libexpat1:arm64 (>= 2.1~beta3) but it is not installable Depends: libgbm1:arm64 (>= 17.1.0~rc2) but it is not installable Depends: libglib2.0-0:arm64 (>= 2.37.3) but it is not installable Depends: libgssapi-krb5-2:arm64 (>= 1.17) but it is not installable Depends: libgtk-3-0:arm64 (>= 3.9.10) but it is not installable Depends: libgtk-3-0:arm64 (>= 3.9.10) but it is not installable or libgtk-4-1:arm64 but it is not installable Depends: libkrb5-3:arm64 (>= 1.6.dfsg.2) but it is not installable Depends: libnspr4:arm64 (>= 2:4.9-2~) but it is not installable Depends: libnss3:arm64 (>= 2:3.30) but it is not installable Depends: libnss3:arm64 (>= 3.26) but it is not installable Depends: libpango-1.0-0:arm64 (>= 1.14.0) but it is not installable Depends: libstdc++6:arm64 (>= 4.1.1) but it is not installable Depends: libstdc++6:arm64 (>= 5) but it is not installable Depends: libstdc++6:arm64 (>= 5.2) but it is not installable Depends: libstdc++6:arm64 (>= 6) but it is not installable Depends: libx11-6:arm64 but it is not installable Depends: libx11-6:arm64 (>= 2:1.4.99.1) but it is not installable Depends: libxcb1:arm64 (>= 1.9.2) but it is not installable Depends: libxcomposite1:arm64 (>= 1:0.4.4-1) but it is not installable Depends: libxdamage1:arm64 (>= 1:1.1) but it is not installable Depends: libxext6:arm64 but it is not installable Depends: libxfixes3:arm64 but it is not installable Depends: libxkbcommon0:arm64 (>= 0.5.0) but it is not installable Depends: libxkbfile1:arm64 (>= 1:1.1.0) but it is not installable Depends: libxrandr2:arm64 but it is not installable Recommends: libvulkan1:arm64 but it is not installable E: Unmet dependencies. Try 'apt --fix-broken install' with no packages (or specify a solution).
最新发布
07-18
code --version ``` 或通过图形界面启动VS Code。 ### 注意事项 - 树莓派5的Raspberry Pi OS应使用64位版本，以确保兼容性。 - 如果使用32位系统，需要将上述步骤中的`arm64`改为`armhf`（但VS Code官方推荐64位）...
import torch import numpy as np from matplotlib import pyplot as plt from torch.utils.data import DataLoader from torchvision import transforms from torchvision import datasets import torch.nn.functional as F “”" 卷积运算 使用mnist数据集，和10-4，11类似的，只是这里：1.输出训练轮的acc 2.模型上使用torch.nn.Sequential “”" Super parameter ------------------------------------------------------------------------------------ batch_size = 64 learning_rate = 0.01 momentum = 0.5 EPOCH = 10 Prepare dataset ------------------------------------------------------------------------------------ transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))]) softmax归一化指数函数(https://blog.csdn.net/lz_peter/article/details/84574716),其中0.1307是mean均值和0.3081是std标准差 train_dataset = datasets.MNIST(root=‘./data/mnist’, train=True, transform=transform) # 本地没有就加上download=True test_dataset = datasets.MNIST(root=‘./data/mnist’, train=False, transform=transform) # train=True训练集，=False测试集 train_loader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True) test_loader = DataLoader(test_dataset, batch_size=batch_size, shuffle=False) fig = plt.figure() for i in range(12): plt.subplot(3, 4, i+1) plt.tight_layout() plt.imshow(train_dataset.train_data[i], cmap=‘gray’, interpolation=‘none’) plt.title(“Labels: {}”.format(train_dataset.train_labels[i])) plt.xticks([]) plt.yticks([]) plt.show() 训练集乱序，测试集有序 Design model using class ------------------------------------------------------------------------------ class Net(torch.nn.Module): def init(self): super(Net, self).init() self.conv1 = torch.nn.Sequential( torch.nn.Conv2d(1, 10, kernel_size=5), torch.nn.ReLU(), torch.nn.MaxPool2d(kernel_size=2), ) self.conv2 = torch.nn.Sequential( torch.nn.Conv2d(10, 20, kernel_size=5), torch.nn.ReLU(), torch.nn.MaxPool2d(kernel_size=2), ) self.fc = torch.nn.Sequential( torch.nn.Linear(320, 50), torch.nn.Linear(50, 10), ) def forward(self, x): batch_size = x.size(0) x = self.conv1(x) # 一层卷积层,一层池化层,一层激活层(图是先卷积后激活再池化，差别不大) x = self.conv2(x) # 再来一次 x = x.view(batch_size, -1) # flatten 变成全连接网络需要的输入 (batch, 20,4,4) ==> (batch,320), -1 此处自动算出的是320 x = self.fc(x) return x # 最后输出的是维度为10的，也就是（对应数学符号的0~9） model = Net() Construct loss and optimizer ------------------------------------------------------------------------------ criterion = torch.nn.CrossEntropyLoss() # 交叉熵损失 optimizer = torch.optim.SGD(model.parameters(), lr=learning_rate, momentum=momentum) # lr学习率，momentum冲量 Train and Test CLASS -------------------------------------------------------------------------------------- 把单独的一轮一环封装在函数类里 def train(epoch): running_loss = 0.0 # 这整个epoch的loss清零 running_total = 0 running_correct = 0 for batch_idx, data in enumerate(train_loader, 0): inputs, target = data optimizer.zero_grad() # forward + backward + update outputs = model(inputs) loss = criterion(outputs, target) loss.backward() optimizer.step() # 把运行中的loss累加起来，为了下面300次一除 running_loss += loss.item() # 把运行中的准确率acc算出来 _, predicted = torch.max(outputs.data, dim=1) running_total += inputs.shape[0] running_correct += (predicted == target).sum().item() if batch_idx % 300 == 299: # 不想要每一次都出loss，浪费时间，选择每300次出一个平均损失,和准确率 print('[%d, %5d]: loss: %.3f , acc: %.2f %%' % (epoch + 1, batch_idx + 1, running_loss / 300, 100 * running_correct / running_total)) running_loss = 0.0 # 这小批300的loss清零 running_total = 0 running_correct = 0 # 这小批300的acc清零 #保存模型 torch.save(model.state_dict(), ‘./model_Mnist.pth’) torch.save(optimizer.state_dict(), ‘./optimizer_Mnist.pth’) def test(): correct = 0 total = 0 with torch.no_grad(): # 测试集不用算梯度 for data in test_loader: images, labels = data outputs = model(images) _, predicted = torch.max(outputs.data, dim=1) # dim = 1 列是第0个维度，行是第1个维度，沿着行(第1个维度)去找1.最大值和2.最大值的下标 total += labels.size(0) # 张量之间的比较运算 correct += (predicted == labels).sum().item() acc = correct / total print('[%d / %d]: Accuracy on test set: %.1f %% ’ % (epoch+1, EPOCH, 100 * acc)) # 求测试的准确率，正确数/总数 return acc Start train and Test -------------------------------------------------------------------------------------- if name == ‘main’: acc_list_test = [] for epoch in range(EPOCH): train(epoch) # if epoch % 10 == 9: #每训练10轮 测试1次 acc_test = test() acc_list_test.append(acc_test) plt.plot(acc_list_test) plt.xlabel('Epoch') plt.ylabel('Accuracy On TestSet') plt.show() 在原始训练代码文件末尾追加以下内容（确保Net类已定义） import torch import onnx import onnxruntime as ort 模型定义必须与训练时完全一致（此处直接使用原文件中的Net类） class Net(torch.nn.Module): def init(self): super(Net, self).init() self.conv1 = torch.nn.Sequential( torch.nn.Conv2d(1, 10, kernel_size=5), torch.nn.ReLU(), torch.nn.MaxPool2d(kernel_size=2), ) self.conv2 = torch.nn.Sequential( torch.nn.Conv2d(10, 20, kernel_size=5), torch.nn.ReLU(), torch.nn.MaxPool2d(kernel_size=2), ) self.fc = torch.nn.Sequential( torch.nn.Linear(320, 50), torch.nn.Linear(50, 10), ) def forward(self, x): batch_size = x.size(0) x = self.conv1(x) x = self.conv2(x) x = x.view(batch_size, -1) x = self.fc(x) return x 导出配置 ------------------------------------------------------------------ PTH_PATH = ‘./model_Mnist.pth’ ONNX_PATH = ‘./model_Mnist.onnx’ 初始化并加载模型 model = Net() model.load_state_dict(torch.load(PTH_PATH)) model.eval() 创建符合MNIST输入的虚拟数据（1,1,28,28） dummy_input = torch.randn(1, 1, 28, 28) 执行导出 torch.onnx.export( model, dummy_input, ONNX_PATH, input_names=[“input”], output_names=[“output”], opset_version=13, dynamic_axes={ ‘input’: {0: ‘batch_size’}, ‘output’: {0: ‘batch_size’} } ) 验证导出结果 ------------------------------------------------------------- def validate_onnx(): # 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Build model print('--> Building model') ret = rknn.build(do_quantization=False) # No quantization if ret != 0: print('Build model failed!') exit(ret) print('done') # Export rknn model print('--> Export rknn model') ret = rknn.export_rknn(RKNN_MODEL) if ret != 0: print('Export rknn model failed!') exit(ret) print('done') # Init runtime environment print('--> Init runtime environment') ret = rknn.init_runtime() # target = 'rk3588' if ret != 0: print('Init runtime environment failed!') exit(ret) print('done') # Inference print('--> Running model')
05-30
好的，我需要帮用户将他们的ONNX模型转换为RKNN模型，特别是在Ubuntu上使用rknn-toolkit1.6.0版本。首先，我得回顾用户提供的代码结构和需求。用户现有的代码是用PyTorch训练了一个MNIST模型，并导出为ONNX。现在...
Plugin execution not covered by lifecycle configuration: org.simplify4u.plugins:pgpverify-maven-plug
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Plugin execution not covered by lifecycle configuration: org.simplify4u.plugins:pgpverify-maven-plugin:1.17.0:check (execution: default, phase: validate)
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ibm_javaibm_javaibm_javaibm_javaibm_javaibm_javaibm_java
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启动。Eclipse 启动关闭。 当jvm crash掉之后，是在Eclipse下生成一个hs_err_pid**.log文件的，于是找到那个文件，下面是分析过程， 这个文件有几部分内容，首先是头部信息，头信息包含了出错的大体信息和位置。 # # A fatal error has been detected by the Java Runtime Environment: # #  S
JDK version
weixin_34315189的博客
05-12 242
Java 1.2 uses major version 46 Java 1.3 uses major version 47 Java 1.4 uses major version 48 Java 5 uses major version 49 Java 6 uses major version 50 Java 7 uses major version 51 Java 8 uses ...
eclipseme.feature_1.6.0_site.zip：Eclipse J2ME插件安装与配置指南
eclipseme.feature_1.6.0_site.zip 是 Eclipse IDE 的一个插件包，主要用于支持 J2ME (Java 2 Platform, Micro Edition) 开发。J2ME 是针对嵌入式设备和移动电话等移动设备的一套Java平台，它允许开发者为这些小型...
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