我正在尝试在烧瓶中创建一个cookie.手册中的部分示例是:
resp = make_response(render_template(...))
resp.set_cookie(’username’, ’the username’)
所以我把它实现为
resp = render_template('show_entries.html', AO_sInteger = session.get('AO_sInteger'))
resp.set_cookie('AO_sInteger', AO_sInteger)
然后系统返回错误:
File "...\Flaskr101.py", line 19, in add_entry
resp.set_cookie('AO_sInteger', AO_sInteger)
AttributeError: 'unicode' object has no attribute 'set_cookie'
我该如何解决这个问题？
我有一个像这样的QML textInput元素:
TextBox.qml
FocusScope {
id: focusScope
property int fontSize: focusScope.height -30
property int textBoxWidth: parent.width * 0.8
property int textBoxHeight: 45
property string placeHolder: 'Type something...'
property bool isUserInTheMiddleOfEntringText: false
width: textBoxWidth
height: textBoxHeight
Rectangle {
width: parent.width
height: parent.height
border.color:'blue'
border.width: 3
radius: 0
MouseArea {
anchors.fill: parent
onClicked: {
focusScope.focus = true
textInput.openSoftwareInputPanel()
}
}
}
Text {
id: typeSomething
anchors.fill: parent; anchors.rightMargin: 8
verticalAlignment: Text.AlignVCenter
text: placeHolder
color: 'red'
font.italic: true
font.pointSize: fontSize
MouseArea {
anchors.fill: …我是一个错误相同此questuion。作为此问题的答案，我正在尝试为PUT索引映射设置正确的url，但不适用于我的实例：
$ cat mapping.json | http PUT myhost:9200/acastest/_mapping
结果：
HTTP/1.1 400 Bad Request
Content-Length: 247
Content-Type: application/json; charset=UTF-8
{
"error": {
"reason": "Validation Failed: 1: mapping type is missing;",
"root_cause": [
{
"reason": "Validation Failed: 1: mapping type is missing;",
"type": "action_request_validation_exception"
}
],
"type": "action_request_validation_exception"
},
"status": 400
}
并尝试与此：
$ cat mapping.json | http PUT myhost:9200/acastest/articles/_mapping
结果：
HTTP/1.1 400 Bad Request
Content-Length: 3969
Content-Type: application/json; charset=UTF-8
{
"error": {
"reason": "Root mapping definition has unsupported parameters: …我使用from python 2.7和pacmanpackage manager,并用它安装sclearn.但是当我有一个ImportError:
>>> from sklearn.feature_extraction.text import TfidfVectorizer
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
ImportError: No module named sklearn.feature_extraction.text
我怎么能解决这个错误？
我在服务器中运行代码时遇到此错误,我的环境是debian,并且 Python2.7.3
Traceback (most recent call last):
File "fetcher.py", line 4, in <module>
import mirad.fetcher_tasks as tasks
File "/home/mirad/backend/mirad/fetcher_tasks.py", line 75, in <module>
redis_keys = r.keys('*')
File "/home/mirad/backend/venv/local/lib/python2.7/site-packages/redis/client.py", line 863, in keys
return self.execute_command('KEYS', pattern)
File "/home/mirad/backend/venv/local/lib/python2.7/site-packages/redis/client.py", line 534, in execute_command
connection.send_command(*args)
File "/home/mirad/backend/venv/local/lib/python2.7/site-packages/redis/connection.py", line 532, in send_command
self.send_packed_command(self.pack_command(*args))
File "/home/mirad/backend/venv/local/lib/python2.7/site-packages/redis/connection.py", line 508, in send_packed_command
self.connect()
File "/home/mirad/backend/venv/local/lib/python2.7/site-packages/redis/connection.py", line 412, in connect
raise ConnectionError(self._error_message(e))
redis.exceptions.ConnectionError: Error -2 connecting to localhost:6379. Name or service not known.
当我运行redis-cli它正常工作没有任何错误:
$ redis-cli …由于支持不同的硬件架构（ARMv7、ARMv8、X86 等） ，Hello World 示例的 React Native APK 大小约为 20M（在最近的版本中），而同一应用程序的 Flutter APK 大小约为 7M。
大小差异的原因是什么？Flutter支持所有硬件架构吗？
我在里面使用django和elasticseach搜索引擎,一切顺利,但最近有这个错误,当我想要更改数据库中的所有内容时,例如当我不想从django admin创建新用户时出现此错误:
Environment:
Request Method: POST
Request URL: http://localhost:8000/admin/auth/user/add/
Django Version: 1.5.1
Python Version: 2.7.3
Installed Applications:
('django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.sites',
'django.contrib.messages',
'django.contrib.staticfiles',
'django.contrib.comments',
'gunicorn',
'django.contrib.admin',
'djangoratings',
'taggit',
'bootstrap_toolkit',
'mptt',
'postman',
'redisboard',
'django_extensions',
'avatar',
'sorl.thumbnail',
'dajaxice',
'dajax',
'endless_pagination',
'easy_pjax',
'debug_toolbar',
'django_nose',
'haystack',
'queued_search',
'saved_searches',
'darkoob.book',
'darkoob.social',
'darkoob.search',
'darkoob.group',
'darkoob.post',
'darkoob.comments',
'darkoob.migration',
'allauth',
'allauth.account',
'allauth.socialaccount',
'allauth.socialaccount.providers.facebook',
'allauth.socialaccount.providers.google',
'allauth.socialaccount.providers.openid',
'allauth.socialaccount.providers.twitter')
Installed Middleware:
('django.middleware.common.CommonMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
'debug_toolbar.middleware.DebugToolbarMiddleware')
Traceback:
File "/usr/local/lib/python2.7/dist-packages/django/core/handlers/base.py" in get_response
115. response = callback(request, *callback_args, **callback_kwargs)
File "/usr/local/lib/python2.7/dist-packages/django/contrib/admin/options.py" …我需要一个算法来计算FIRST和FOLLOW设置语法.
是否有简单的算法或简单的代码来计算这些？
我的任务平均需要20秒.我想为此任务设置软超时和超时.我这样定义:
@app.task(ignore_result=True, timeout=100, soft_timeout=50)
def MYTASK(SOMEPARAMS):
# MYTASK
但它确实不起作用.我用这个参数测试它:
@app.task(ignore_result=True, timeout=1, soft_timeout=1)
def MYTASK(SOMEPARAMS):
# MYTASK
但我的任务正常工作,它们需要超过1秒的时间,而它永远不应该完成.
为什么超时不起作用？
编辑:当我在日志中使用1秒超时时,我看到这样的打印:
[2014-08-22 12:51:00,003: INFO/MainProcess] Task MYTASK[56002e72-a093-46c6-86cd-4c7b7e6ea7c3] succeeded in 15.549023876s: None
我使用 Friends Dialogues 作为数据集来训练使用 GPT-2 进行对话式 AI，但是，它显示我内存不足。我知道这个问题已经在 StackOverflow 上得到解决，但我无法弄清楚 NLP 任务的优化。
我尝试将批量大小设置为 50（我的数据集大约有 60k 行）。我一直在关注有关在自定义数据集上重新训练 GPT-2 的教程。
我的系统规格是： 操作系统：Windows 10 RAM：16 GB CPU：i7 第 8 代 GPU：4GB Nvidia GTX 1050Ti
这是整个错误信息
Resource exhausted: OOM when allocating tensor with shape[51200,2304] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
Traceback (most recent call last):
File "C:\Users\bhave\AppData\Local\conda\conda\envs\tf_gpu\lib\site-packages\tensorflow\python\client\session.py", line 1334, in _do_call
return fn(*args)
File "C:\Users\bhave\AppData\Local\conda\conda\envs\tf_gpu\lib\site-packages\tensorflow\python\client\session.py", line 1319, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "C:\Users\bhave\AppData\Local\conda\conda\envs\tf_gpu\lib\site-packages\tensorflow\python\client\session.py", line 1407, in _call_tf_sessionrun
run_metadata) …