我想学习如何在每次保存后自动优化导入,就像我们做Eclipse(保存操作)一样.
file x.java is too large for IntelliJ Idea editor尝试打开为Axis 2生成的Web服务存根类后获取" ".
我看到一个关于这个问题的帖子说改变了
idea.max.intellisense.filesize=2500
在idea.properties.
但是这个技巧对我来说不起作用,尽管我增加了足够的价值.此外,我试图注释掉它以禁用此功能; 但它也不起作用..
我正面临Spring Data MongoDB Criteria API orOperator问题.
这是不规则动词的查询结果:( 终端输出)
> db.verb.find({'v2':'wrote'});
{ "_id" : ObjectId("5161a8adba8c6390849da453"), "v1" : "write", "v2" : "wrote", "v3" : "written" }
我使用Spring Data MongoDB Criteria API通过它们v1或v2值查询动词:
Criteria criteriaV1 = Criteria.where("v1").is(verb);
Criteria criteriaV2 = Criteria.where("v2").is(verb);
Query query = new Query(criteriaV1.orOperator(criteriaV2));
List<Verb> verbList = mongoTemplate.find(query, Verb.class)
但不幸的verbList是没有任何项目.
在持久化我的模型对象时,我面临着UTF-8编码问题.土耳其语' ı '是一封信.还有一些其他土耳其字符包含在UTF-8编码中.虽然我坚持我的模型对象,但所有' ı '字符都被保留为' ？'到DB.我在Ubuntu Linux 64位操作系统上使用MySQL 5.5.此外,我已经将hibernate&c3p0连接编码属性设置为UTF-8.当我调试时,来自客户端的数据是真的.
这是我的配置,如果有人可以帮助我,我会很高兴.
提前致谢.
Spring&Hibernate配置
<bean id="sessionFactory" class="org.springframework.orm.hibernate4.LocalSessionFactoryBean">
<property name="dataSource"><ref local="dataSource"/></property>
<property name="packagesToScan" value="com.tk.dms.model" />
<property name="hibernateProperties">
<props>
<prop key="hibernate.show_sql">true</prop>
<prop key="hibernate.use_sql_comments">true</prop>
<prop key="hibernate.format_sql">false</prop>
<prop key="hibernate.hbm2ddl.auto">update</prop>
<prop key="hibernate.generate_statistics">true</prop>
<prop key="hibernate.dialect">org.hibernate.dialect.MySQL5InnoDBDialect</prop>
<prop key="hibernate.connection.characterEncoding">UTF-8</prop>
<prop key="hibernate.connection.useUnicode">true</prop>
<!-- c3p0 properties -->
<prop key="hibernate.c3p0.min_size">2</prop>
<prop key="hibernate.c3p0.max_size">50</prop>
<prop key="hibernate.c3p0.maxPoolSize">50</prop>
<prop key="hibernate.c3p0.minPoolSize">2</prop>
<prop key="hibernate.c3p0.initialPoolSize">2</prop>
<prop key="hibernate.c3p0.timeout">300</prop>
<prop key="hibernate.c3p0.max_statements">50</prop>
</props>
</property>
</bean>
尽管如此我已经定义了相关的依赖项,如下所示,java.lang.ClassNotFoundException: com.sun.xml.internal.ws.spi.ProviderImpl当我的应用程序调用Web服务时获取异常.
<dependency>
<groupId>javax.xml.ws</groupId>
<artifactId>jaxws-api</artifactId>
<version>2.2.10</version>
</dependency>
<dependency>
<groupId>com.sun.xml.ws</groupId>
<artifactId>jaxws-rt</artifactId>
<version>2.2.10</version>
<type>pom</type>
</dependency>
ps servlet容器是Apache Tomcat 9.0.4.
ps Java版:9.0.1.
当forward我的神经网络的功能（训练阶段完成后）正在执行时，我遇到RuntimeError: Expected object of backend CUDA but got backend CPU for argument #4 'mat1'.错误跟踪表明错误是由于调用output = self.layer1(x)命令而发生的。我试图将张量的所有数据移动到我的 GPU。似乎我也想念一些要移动的东西。
这是我尝试过的代码：
use_cuda = torch.cuda.is_available()
device = torch.device('cuda:0' if use_cuda else 'cpu')
class NeuralNet(nn.Module):
def __init__(self, input_size, hidden_size, output_size):
super(NeuralNet, self).__init__()
self.layer1 = nn.Linear(input_size, hidden_size).cuda(device)
self.layer2 = nn.Linear(hidden_size, output_size).cuda(device)
self.relu = nn.ReLU().cuda(device)
def forward(self, x):
x.cuda(device)
output = self.layer1(x) # throws the error
output = self.relu(output)
output = self.layer2(output)
return output
def main():
transform = transforms.Compose([
transforms.ToTensor()
]) …尽管我遵守了规则,但我收到" 无法加载类"org.slf4j.impl.StaticLoggerBinder "错误:
放置一个(也是唯一一个)slf4j-nop.jar,slf4j-simple.jar,slf4j-log4j12.jar,slf4j-jdk14.jar或logback-classic.jar
如果有人可以帮助我,我会很高兴,在此先感谢..
这是我的依赖:
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
<version>${slf4j.version}</version>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
<version>${slf4j.version}</version>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
<version>1.2.15</version>
<exclusions>
<exclusion>
<groupId>com.sun.jmx</groupId>
<artifactId>jmxri</artifactId>
</exclusion>
<exclusion>
<groupId>com.sun.jdmk</groupId>
<artifactId>jmxtools</artifactId>
</exclusion>
<exclusion>
<groupId>javax.jms</groupId>
<artifactId>jms</artifactId>
</exclusion>
</exclusions>
</dependency>
这是maven依赖树的输出:
[INFO] com.tk.sample:ext4:jar:1.0
[INFO] +- org.slf4j:slf4j-api:jar:1.6.1:compile
[INFO] +- org.slf4j:slf4j-log4j12:jar:1.6.1:compile
[INFO] +- log4j:log4j:jar:1.2.15:compile
[INFO] | \- javax.mail:mail:jar:1.4:compile
[INFO] | \- javax.activation:activation:jar:1.1:compile
[INFO] +- commons-lang:commons-lang:jar:2.5:compile
[INFO] +- junit:junit:jar:4.8.2:test (scope not updated to compile)
[INFO] +- org.easymock:easymock:jar:3.0:test
[INFO] | \- org.objenesis:objenesis:jar:1.2:test
[INFO] +- javax.servlet:servlet-api:jar:2.5:provided
[INFO] +- taglibs:standard:jar:1.1.2:compile
[INFO] …我需要在内存中创建后将iTextPDF Document文件转换为byte [].我已经测试过,我没有正确创建PDF的问题.问题是如何将其转换为字节数组以存储在DB中.
这是我的代码:
Document generatedDocument = reportService.generateRequestForm(scdUser, jsonObject, 0, null);
reportService.generateRequestForm(scdUser, jsonObject, 0, null);
ByteArrayOutputStream baos = new ByteArrayOutputStream();
PdfWriter pdfWriter = PdfWriter.getInstance(generatedDocument, baos);
generatedDocument.open();
document.setDocument(baos.toByteArray()); // stores as blob
我在数据库blob列中获得null值.
这是我的Document域对象:
文档域对象
@Entity
@Table(name = "document")
public class Document implements java.io.Serializable {
@Id
@GeneratedValue(strategy = GenerationType.AUTO)
@Column(name = "document_id", nullable = false)
private int documentId;
@Column(name = "document_name", nullable = false, length = 65535)
private String documentName;
@Column(name …我得到的错误TypeError: pic should be PIL Image or ndarray. Got <class 'numpy.ndarray'>，当我尝试加载非图像数据集通过DataLoader。的版本torch和torchvision是1.0.1，和0.2.2.post3分别。Python 的版本3.7.1在Windows 10机器上。
这是代码：
class AndroDataset(Dataset):
def __init__(self, csv_path):
self.transform = transforms.Compose([transforms.ToTensor()])
csv_data = pd.read_csv(csv_path)
self.csv_path = csv_path
self.features = []
self.classes = []
self.features.append(csv_data.iloc[:, :-1].values)
self.classes.append(csv_data.iloc[:, -1].values)
def __getitem__(self, index):
# the error occurs here
return self.transform(self.features[index]), self.transform(self.classes[index])
def __len__(self):
return len(self.features)
我设置了加载器：
training_data = AndroDataset('android.csv')
train_loader = DataLoader(dataset=training_data, batch_size=batch_size, shuffle=True) …由于标题清楚地描述了我遇到的问题，因此Pipfile.lock当我执行推荐的命令时出现以下错误时没有生成pipenv lock --clear：
ERROR: ERROR: Could not find a version that matches keras-nightly~=2.5.0.dev
Skipped pre-versions: 2.5.0.dev2021020510, 2.5.0.dev2021020600, 2.5.0.dev2021020700, 2.5.0.dev2021020800, 2.5.0.dev2021020900, 2.5.0.dev2021021000, 2.5.0.dev2021021100, 2.5.0.dev2021021200, 2.5.0.dev2021021300, 2.5.0.dev2021021400, 2.5.0.dev2021021500, 2.5.0.dev2021021600, 2.5.0.dev2021021700, 2.5.0.dev2021021800, 2.5.0.dev2021021900, 2.5.0.dev2021022000, 2.5.0.dev2021022100, 2.5.0.dev2021022200, 2.5.0.dev2021022300, 2.5.0.dev2021022317, 2.5.0.dev2021022400, 2.5.0.dev2021022411, 2.5.0.dev2021022500, 2.5.0.dev2021022600, 2.5.0.dev2021022700, 2.5.0.dev2021022800, 2.5.0.dev2021030100, 2.5.0.dev2021030200, 2.5.0.dev2021030300, 2.5.0.dev2021030400, 2.5.0.dev2021030500, 2.5.0.dev2021030600, 2.5.0.dev2021030700, 2.5.0.dev2021030800, 2.5.0.dev2021030900, 2.5.0.dev2021031000, 2.5.0.dev2021031100, 2.5.0.dev2021031200, 2.5.0.dev2021031300, 2.5.0.dev2021031400, 2.5.0.dev2021031500, 2.5.0.dev2021031600, 2.5.0.dev2021031700, 2.5.0.dev2021031800, 2.5.0.dev2021032213, 2.5.0.dev2021032300, 2.5.0.dev2021032413, 2.5.0.dev2021032500, 2.5.0.dev2021032600, 2.5.0.dev2021032610, 2.5.0.dev2021032700, 2.5.0.dev2021032800, 2.5.0.dev2021032900, 2.6.0.dev2021033000, 2.6.0.dev2021033100, 2.6.0.dev2021040100, 2.6.0.dev2021040200, 2.6.0.dev2021040300, 2.6.0.dev2021040400, 2.6.0.dev2021040500, 2.6.0.dev2021040600, …