Svn downloaded my colleague’s Vue last night. This morning, NPM install kept reporting errors. I was so angry that I directly copied the node in the previous file_ Modules, then continue NPM run Dev and report an error (as shown in the figure below):
I’ve been looking online and couldn’t find it. I also asked my colleagues. My colleagues said I might have a problem with NPM install. Continue to find the answer on Baidu CSDN!! Finally, the effort pays off. Now let’s show you my solution (below):
mainly look at points 1 and 2. First open your folder according to the directory 1, and then look at the prompt of 2 to find this one. My prompt is to tell me that I quoted a file I don’t have, and then comment it out. It’s OK to run smoothly
Author Archives: Robins
[Solved] TFrecords Create Datas Error: Number of int64 values != expected. Values size: 1 but output shape: [3]
1. For fixed length label and feature
Generate tfrecord data:
Multiple label samples, where the label contains 5
import os
import tensorflow as tf
import numpy as np
output_flie = str(os.path.dirname(os.getcwd()))+"/train.tfrecords"
with tf.python_io.TFRecordWriter(output_flie) as writer:
labels = np.array([[1,0,0,1,0],[0,1,0,0,1],[0,0,0,0,1],[1,0,0,0,0]])
features = np.array([[0,0,0,0,0,0],[1,1,1,1,1,2],[1,1,1,0,0,2],[0,0,0,0,1,9]])
for i in range(4):
label = labels[i]
feature = features[i]
example = tf.train.Example(features=tf.train.Features(feature={
"label": tf.train.Feature(int64_list=tf.train.Int64List(value=label)),
'feature': tf.train.Feature(int64_list=tf.train.Int64List(value=feature))
}))
writer.write(example.SerializeToString())Parse tfrecord data:
import os
import tensorflow as tf
import numpy as np
def read_tf(output_flie):
filename_queue = tf.train.string_input_producer([output_flie])
reader = tf.TFRecordReader()
_, serialized_example = reader.read(filename_queue)
result = tf.parse_single_example(serialized_example,
features={
'label': tf.FixedLenFeature([5], tf.int64),
'feature': tf.FixedLenFeature([6], tf.int64),
})
feature = result['feature']
label = result['label']
return feature, label
output_flie = str(os.path.dirname(os.getcwd())) + "/train.tfrecords"
feature, label = read_tf(output_flie)
imageBatch, labelBatch = tf.train.batch([feature, label], batch_size=2, capacity=3)
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
print(1)
images, labels = sess.run([imageBatch, labelBatch])
print(images)
print(labels)
coord.request_stop()
coord.join(threads)
Output:
1
('----images: ', array([[0, 0, 0, 0, 0, 0],
[1, 1, 1, 1, 1, 2]]))
('----labels:', array([[1, 0, 0, 1, 0],
[0, 1, 0, 0, 1]]))2. For variable length label and feature
Generate tfrecord
It is the same as the fixed length data generation method
import os
import tensorflow as tf
import numpy as np
train_TFfile = str(os.path.dirname(os.getcwd()))+"/hh.tfrecords"
writer = tf.python_io.TFRecordWriter(train_TFfile)
labels = [[1,2,3],[3,4],[5,2,6],[6,4,9],[9]]
features = [[2,5],[3],[5,8],[1,4],[5,9]]
for i in range(5):
label = labels[i]
print(label)
feature = features[i]
example = tf.train.Example(
features=tf.train.Features(
feature={'label': tf.train.Feature(int64_list=tf.train.Int64List(value=label)),
'feature': tf.train.Feature(int64_list=tf.train.Int64List(value=feature))}))
writer.write(example.SerializeToString())
writer.close()Parsing tfrecord
The main changes are:
tf.VarLenFeature(tf.int64)Unfinished to be continued
Common errors:
When the defined label dimension is different from the dimension during parsing, an error will be reported as follows:
Details of error reporting:
tensorflow.python.framework.errors_impl.InvalidArgumentError: Name: <unknown>, Key: label, Index: 0. Number of int64 values != expected. Values size: 1 but output shape: [3]The size of the label is 1, but when used, it exceeds 1
Solution: when generating tfrecord, the length of label should be the same as that during parsing.
[Solved] K8s cluster build error: error: kubectl get csr No resources found.
K8s cluster setup error: error: kubectl get CSR no resources found
Problem cause and solution test successful
problem
kubectl get csr
No resources found.
reason
because the original SSL certificate is invalid after restart, if it is not deleted, kubelet cannot communicate with the master even after restart
Solution:
cd /opt/kubernetes/ssl
ls
kubelet-client-2021-04-14-08-41-36.pem kubelet-client-current.pem kubelet.crt kubelet.key
# Delete all certificates
rm -rf *
# close or open the kubelet
systemctl stop kubelet
master01
kubectl delete clusterrolebinding kubelet-bootstrap
clusterrolebinding.rbac.authorization.k8s.io "kubelet-bootstrap" deleted
kubectl create clusterrolebinding kubelet-bootstrap --clusterrole=system:node-bootstrapper --user=kubelet-bootstrap
clusterrolebinding.rbac.authorization.k8s.io/kubelet-bootstrap created
node
#open kubelet
#node01
bash kubelet.sh 192.168.238.82
#node02
bash kubelet.sh 192.168.238.83
Test successful
master01
kubectl get csr
NAME AGE REQUESTOR CONDITION
node-csr-mJwuqA7DAf4UmB1InN_WEYhFWbQKOqUVXg9Bvc7Intk 4s kubelet-bootstrap Pending
node-csr-ydhzi9EG9M_Ozmbvep0ledwhTCanppStZoq7vuooTq8 11s kubelet-bootstrap Pending
Done!!!
[Solved] Error in registering Eureka for spring cloud micro service: classnotfoundexception: org.apache.http.conn.scheme.schemeregistry
1. Problem description
As mentioned above, it is normal to start the Eureka server alone. When you start the micro service module and register the service with Eureka, an error is reported.
My microservice module POM depends on the following:
<dependencies>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-netflix-eureka-client</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-web</artifactId>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
</dependency>
<dependency>
<groupId>org.mybatis.spring.boot</groupId>
<artifactId>mybatis-spring-boot-starter</artifactId>
<version>2.1.1</version>
</dependency>
</dependencies>
Microservice module configuration file:
eureka.client.service-url.defaultZone=http://localhost:8000/eureka
The total POM of the project is as follows:
<dependencies>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter</artifactId>
</dependency>
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-test</artifactId>
<scope>test</scope>
</dependency>
</dependencies>
<dependencyManagement>
<dependencies>
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-dependencies</artifactId>
<version>Greenwich.SR5</version>
<type>pom</type>
<scope>import</scope>
</dependency>
</dependencies>
</dependencyManagement>
2. Solution
See a similar problem on stack overflow:
It is speculated that there may also be a problem with the dependent package under D: \ D1 \ Java \ maven \ repo \ ORG \ Apache \ httpcomponents
According to the time of the file modification date, the following package should be called for the use of Eureka
Delete these folders and reintroduce the POM dependency of microservice module and Eureka server
Start the microservice here and the problem is solved
16:31:17.183- INFO 38700 --- [ main]com.netflix.discovery.DiscoveryClient :Getting all instance registry info from the eureka server
16:31:17.460- INFO 38700 --- [ main]com.netflix.discovery.DiscoveryClient :The response status is 200
16:31:17.462- INFO 38700 --- [ main]com.netflix.discovery.DiscoveryClient :Starting heartbeat executor: renew interval is: 30
16:31:17.465- INFO 38700 --- [ main]c.n.discovery.InstanceInfoReplicator :InstanceInfoReplicator onDemand update allowed rate per min is 4
16:31:17.470- INFO 38700 --- [ main]com.netflix.discovery.DiscoveryClient :Discovery Client initialized at timestamp 1628843477468 with initial instances count: 0
16:31:17.472- INFO 38700 --- [ main]o.s.c.n.e.s.EurekaServiceRegistry :Registering application COURSE-LIST with eureka with status UP
16:31:17.472- INFO 38700 --- [ main]com.netflix.discovery.DiscoveryClient :Saw local status change event StatusChangeEvent [timestamp=1628843477472, current=UP, previous=STARTING]
16:31:17.475- INFO 38700 --- [nfoReplicator-0]com.netflix.discovery.DiscoveryClient :DiscoveryClient_COURSE-LIST/LAPTOP-LMMPH4VI:course-list:8080: registering service...
16:31:17.523- INFO 38700 --- [ main]o.s.b.w.embedded.tomcat.TomcatWebServer :Tomcat started on port(s): 8080 (http) with context path ''
16:31:17.524- INFO 38700 --- [ main].s.c.n.e.s.EurekaAutoServiceRegistration :Updating port to 8080
16:31:17.567- INFO 38700 --- [nfoReplicator-0]com.netflix.discovery.DiscoveryClient :DiscoveryClient_COURSE-LIST/LAPTOP-LMMPH4VI:course-list:8080 - registration status: 204
16:31:19.133- INFO 38700 --- [ main]com.fanyu.course.CourseListApplication :Started CourseListApplication in 13.313 seconds (JVM running for 14.906)
[Gradle is Stucked in Building Runing] log Error: Timeout waiting to lock journal cache
Recently, gradle often uses the card build running
the Mac computer can see similar errors printed on the console. The win10 system doesn’t tell you and gets stuck silently.
* What went wrong:
Gradle could not start your build.
> Cannot create service of type BuildTreeActionExecutor using method LauncherServices$ToolingBuildTreeScopeServices.createActionExecutor() as there is a problem with parameter #1 of type List<BuildActionRunner>.
> Could not create service of type FileAccessTimeJournal using GradleUserHomeScopeServices.createFileAccessTimeJournal().
> Timeout waiting to lock journal cache (C:\Users\XXX\.gradle\caches\journal-1). It is currently in use by another Gradle instance.
Owner PID: 8128
Our PID: 14108
Owner Operation:
Our operation:
Lock file: C:\Users\XXX\.gradle\caches\journal-1\journal-1.lock
The log can be seen under the. Gradle/daemon directory of win10. By the way, gradle also dumps the memory. The MAC is not very large. It is estimated that the C disk will be full in a few days
check the 8128 process and find that it is a java program
reset gradle JDK version 11.0.11 in project structure
no jamming exception is found after reset.
DM Install Error: error while loading shared libraries: libdmnsort.so:
An error is reported when installing DM to initialize the database
error while loading shared libraries: libdmnsort.so: cannot open shared object file: no such file or directory
[root@localhost tmp]/opt/dmdbms/bin/dminit PATH=/opt/dmdbms/data
/opt/dmdbms/bin/dminit: error while loading shared libraries: libdmnsort.so: cannot open shared object file: No such file or directory
##but in /opt/dmdbms/bin there is libdmnsort.so
[dmdba@localhost ~]$ ll /opt/dmdbms/bin/libdmnsort.so
-rwxr-xr-x 1 dmdba dinstall 269865 8月 17 11:07 /opt/dmdbms/bin/libdmnsort.so
I’m impressed that I met you once before. The solution seems to be to go to the/opt/dmdbms/bin directory and find out the reason this time
After installing DM, these two lines will be automatically added to the environment variable of the home directory
[dmdba@localhost ~]$ cat .bash_profile
export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/opt/dmdbms/bin"
export DM_HOME="/opt/dmdbms"
I don’t know the reason this time. I didn’t read it after adding it, which led to
[dmdba@localhost ~]$ echo $LD_LIBRARY_PATH
Read. Bash again_Just a profile
[dmdba@localhost ~]$ source ~/.bash_profile
[dmdba@localhost ~]$ echo $LD_LIBRARY_PATH
:/opt/dmdbms/bin
[dmdba@localhost ~]$ /opt/dmdbms/bin/dminit
initdb V8
db version: 0x7000c
file dm.key not found, use default license!
License will expire on 2022-08-04
input system dir: ^C
[Solved] RK3399 Compile UBOOT Error: No rule to make target , needed by
When modifying UBOOT will not compile
make: *** No rule to make target , needed by ‘include/config/auto.confCommands:
cd a-firefly-rk3399-Industry/u-boot
make rk3399_defconfig
make ARCHV=aarch64 -j8
make: *** No rule to make target , needed by ‘include/config/auto.confCommands:
cd a-firefly-rk3399-Industry/u-boot
make rk3399_defconfig
make ARCHV=aarch64 -j8
Solution:
make distclean
[Solved] Gulp-sass Install Error: error: cannot find module ‘sass‘
The following errors are reported:
View the official gulp-sass Download document:
The following solutions are given:
To use gulp-sass, you have to download node-sass or dart sass, and then download gulp-sass;
Download node-sass using the following command:
npm install node-sass
Use the following command to download the Gup sass protest without error
npm install sass gulp-sass --save-devTo use gulp-sass, you must install both gulp-sass itself and a Sass compiler. gulp-sasssupports both Dart Sass and Node Sass, but Node Sass is deprecated. We recommend that you use Dart Sass for new projects, and migrate Node Sass projects to Dart Sass when possible.
Whichever compiler you choose, it’s best to install these as dev dependencies:
Then the sass module is introduced in gulpfile.js at
var sass = require(‘gulp-sass’)(require(‘sass’);
[Solved] Git submits locally to the remote warehouse Error: failed to push some refs to…
Today, a new project was created locally and a warehouse was built on the code cloud. You want to push it to the code cloud locally, but git push - U origin master , an error is reported:
! [rejected] master -> master (fetch first)
error: failed to push some refs to 'https://gitee.com/xxx/app.git'
hint: Updates were rejected because the remote contains work that you do
hint: not have locally. This is usually caused by another repository pushing
hint: to the same ref. You may want to first integrate the remote changes
hint: (e.g., 'git pull ...') before pushing again.
hint: See the 'Note about fast-forwards' in 'git push --help' for details.
After searching, use: git pull -- rebase origin master to solve the difference between
rebase and merge:
rebase puts the commit from your current branch at the end of the public branch, so it's called a rebase.
merge merges the public branch with your current commit to form a new commit
Python asynchronous co process crawler error: [aiohttp. Client]_ Exceptions: serverdisconnected error: Server Disconnected]
Background description:
I just started to contact crawlers, read online tutorials and began to learn a little bit. All the knowledge points are relatively shallow. If there are better methods, please comment and share.
The initial crawler is very simple: crawl the data list in a web page, and the format returned by the web page is also very simple. It is in the form of a dictionary, which can be directly accessed by saving it as a dictionary with . Json() .
At the beginning of contact with asynchronous collaborative process, after completing the exercise, try to transform the original crawler, resulting in an error.
Initial code:
async def download_page(url):
async with aiohttp.ClientSession() as session:
async with session.get(url) as resp:
await result = resp.text()
async def main(urls):
tasks = []
for url in urls:
tasks.append(asyncio.create_task(download_page(url))) # 我的python版本为3.9.6
await asyncio.await(tasks)
if __name__ == '__main__':
urls = [ url1, url2, …… ]
asyncio.run(main(urls))
This is the most basic asynchronous collaborative process framework. When the amount of data is small, it can basically meet the requirements. However, if the amount of data is slightly large, it will report errors. The error information I collected is as follows:
aiohttp.client_exceptions.ClientOSError: [WinError 64] The specified network name is no longer available.
Task exception was never retrieved
aiohttp.client_exceptions.ClientOSError: [WinError 121] The signal timeout has expired
Task exception was never retrieved
aiohttp.client_exceptions.ServerDisconnectedError: Server disconnected
Task exception was never retrieved
The general error message is that there is a problem with the network request and connection
as a beginner, I didn’t have more in-depth understanding of network connection, nor did I learn more in-depth asynchronous co process operation. Therefore, it is difficult to solve the problem of error reporting.
Solution:
The big problem with the above error reports is that each task creates a session. When too many sessions are created, an error will be reported.
Solution:
Try to create only one session
async def download_page(url，session):
async with session.get(url) as resp:
await result = resp.text()
async def main(urls):
tasks = []
async with aiohttp.ClientSession() as session: # The session will be created in the main function, and the session will be passed to the download_page function as a variable.
for url in urls:
tasks.append(asyncio.create_task(download_page(url,session)))
#My python version is 3.9.6, python version 3.8 and above, if you need to create asynchronous tasks, you need to create them via asyncio.create_task(), otherwise it will run normally but will give a warning message await asyncio.await(tasks)
if __name__ == '__main__':
urls = [ url1, url2, …… ]
asyncio.run(main(urls))
In this way, the problem of connection error can be solved to a certain extent when crawling a large amount of data.
Sentiment: in the process of programming, thinking should be more flexible. A little change may improve the efficiency a lot.
[Solved] ESP32 Error: error: expected initializer before ‘__result_use_check‘
report errors:
A higher version of esp-idf was used before, but now a lower version of esp-idf should be used. There is an error in compiling after switching versions.
Execute make or make all
/home/pjw/.espressif/tools/xtensa-esp32-elf/esp-2020r3-8.4.0/xtensa-esp32-elf/xtensa-esp32-elf/sys-include/stdlib.h:155:44: error: expected initializer before '__result_use_check'
void *reallocarray(void *, size_t, size_t) __result_use_check __alloc_size(2)
^~~~~~~~~~~~~~~~~~
/home/pjw/.espressif/tools/xtensa-esp32-elf/esp-2020r3-8.4.0/xtensa-esp32-elf/xtensa-esp32-elf/sys-include/stdlib.h:340:52: error: expected initializer before '__alloc_align'
void * aligned_alloc(size_t, size_t) __malloc_like __alloc_align(1)
Run make -j16
/home/pjw/ESP32/esp-mdf/esp-idf/components/newlib/include/stdio.h:282:12: error: 'vfiprintf' was not declared in this scope
int _EXFUN(vfiprintf, (FILE *, const char *, __VALIST)
^~~~~~~~~
/home/pjw/ESP32/esp-mdf/esp-idf/components/newlib/include/stdio.h:282:29: error: expected primary-expression before '*' token
int _EXFUN(vfiprintf, (FILE *, const char *, __VALIST)
....
a lot of errors
analysis:
ESP idf expected initializer before ‘__ result_ use_ Check ‘error repair
the first part of the compilation information is as follows:
App "get-started" version: 237cc099-dirty
WARNING: Toolchain version is not supported: esp-2020r3
Expected to see version: crosstool-ng-1.22.0-97-gc752ad5
Please check ESP-IDF setup instructions and update the toolchain, or proceed at your own risk.
WARNING: Compiler version is not supported: 8.2.0
Expected to see version(s): 5.2.0
Please check ESP-IDF setup instructions and update the toolchain, or proceed at your own risk.
From the information point of view, the version of the compiled tool chain is incorrect
the esp-2020r3 version of tool chain is not supported. Use the crosstool-ng-1.22.0-97-gc752ad5 version
the 8.2.0 compiler is not supported. Use the 5.2.0 version.
solve:
After executing . Install. Sh in ESP IDF , the tool chain and compiler have been downloaded to ~ /. Espressif/tools/xtensa-esp32-elf .
So just modify the environment variables
the original export path = ~ /. Espressif/tools/xtensa-esp32-elf/esp-2020r3-8.4.0/xtensa-esp32-elf/bin: $path
modification:
vim ~/.bashrc
# Delete the previous compilation chain environment variables
#export PATH=~/.espressif/tools/xtensa-esp32-elf/esp-2020r3-8.4.0/xtensa-esp32-elf/bin:$PATH
# Add environment variables
export PATH=~/.espressif/tools/xtensa-esp32-elf/1.22.0-97-gc752ad5-5.2.0/xtensa-esp32-elf/bin:$PATH
source ~/.bashrc
P.S.
ESP-IDF release/v3.3 use 1.22.0-97-gc752ad5-5.2.0 version
ESP-IDF release/v4.0 use esp-2019r2-8.2.0 version
ESP-IDF release/v4.2 use esp-2020r3-8.4.0 version
ESP-IDF release/v4.3 use esp-2021r1-8.4.0 version
[Solved] Consul Error: github.com/boltdb/bolt github.com/boltdb/bolt github.com/hashicorp/raft-boltdb
Consumer startup error:
BootstrapExpect is set to 1; this is the same as Bootstrap mode.
bootstrap = true: do not enable unless necessary
==> Starting Consul agent...
Version: 'v1.5.3'
Node ID: '63816065-24d9-8715-0986-cb25587fb459'
Node name: 'node0'
Datacenter: 'dc1' (Segment: '<all>')
Server: true (Bootstrap: true)
Client Addr: [192.168.8.136] (HTTP: 8500, HTTPS: -1, gRPC: -1, DNS: 8600)
Cluster Addr: 192.168.8.136 (LAN: 8301, WAN: 8302)
Encrypt: Gossip: false, TLS-Outgoing: false, TLS-Incoming: false, Auto-Encrypt-TLS: false
==> Log data will now stream in as it occurs:
panic: cannot free page 0 or 1: 0
goroutine 1 [running]:
github.com/boltdb/bolt.(*freelist).free(0xc00080f950, 0xbbdd, 0x7f9cd5354000)
/go/pkg/mod/github.com/boltdb/[email protected]/freelist.go:113 +0x336
github.com/boltdb/bolt.(*Tx).Commit(0xc0001ea7e0, 0x4f2d0f4, 0x4)
/go/pkg/mod/github.com/boltdb/[email protected]/tx.go:176 +0x1b7
github.com/hashicorp/raft-boltdb.(*BoltStore).initialize(0xc000248660, 0x0, 0x0)
/go/pkg/mod/github.com/hashicorp/[email protected]/bolt_store.go:105 +0x137
github.com/hashicorp/raft-boltdb.New(0xc00017fc80, 0x17, 0x0, 0xc00017fc00, 0x17, 0x0, 0x10e7fb3900)
/go/pkg/mod/github.com/hashicorp/[email protected]/bolt_store.go:81 +0xfe
github.com/hashicorp/raft-boltdb.NewBoltStore(...)
/go/pkg/mod/github.com/hashicorp/[email protected]/bolt_store.go:60
github.com/hashicorp/consul/agent/consul.(*Server).setupRaft(0xc0006a2380, 0x0, 0x0)
/home/circleci/project/consul/agent/consul/server.go:627 +0xa36
github.com/hashicorp/consul/agent/consul.NewServerLogger(0xc0006a2000, 0xc0000a0a50, 0xc0006b0680, 0xc0000a0c30, 0x0, 0x0, 0x0)
/home/circleci/project/consul/agent/consul/server.go:428 +0xafe
github.com/hashicorp/consul/agent.(*Agent).Start(0xc0000b5680, 0x0, 0x0)
/home/circleci/project/consul/agent/agent.go:411 +0x56e
github.com/hashicorp/consul/command/agent.(*cmd).run(0xc0004e9500, 0xc00004c0e0, 0xa, 0xa, 0x0)
/home/circleci/project/consul/command/agent/agent.go:280 +0xf5b
github.com/hashicorp/consul/command/agent.(*cmd).Run(0xc0004e9500, 0xc00004c0e0, 0xa, 0xa, 0xc0004e4ca0)
/home/circleci/project/consul/command/agent/agent.go:75 +0x4d
github.com/mitchellh/cli.(*CLI).Run(0xc0003b3cc0, 0xc0003b3cc0, 0x80, 0xc0004e51e0)
/go/pkg/mod/github.com/mitchellh/[email protected]/cli.go:255 +0x1f1
main.realMain(0xc000094058)
/home/circleci/project/consul/main.go:53 +0x393
main.main()
/home/circleci/project/consul/main.go:20 +0x22
Solution reference: https://github.com/hashicorp/consul/issues/2933
Solution:
find raft. DB on the server where consumer is deployed; Use RM - f to delete all raft. DB ; Restart consumer