我使用顶点AI管道来定制培训表格数据。
我运行下面的python代码。创建,使用生成的json运行管道。在培训开始时发生以下错误。
为什么将表格数据集作为图像数据集处理?怎么啦?
环境
kfp==1.6.2kfp-pipeline-spec==0.1.7kfp-server-api==1.6.0 Python 3.7.3
错误消息
ValueError: ImageDataset class can not be used to retrieve dataset resource projects/nnnnnnnnnnnn/locations/us-central1/datasets/3781
当我运行python manage.py收藏品时,我得到:
Traceback (most recent call last):
File "manage.py", line 10, in <module>
execute_from_command_line(sys.argv)
File "/Users/fceruti/Development/Arriendas.cl/venv/lib/python2.7/site-packages/django/core/management/__init__.py", line 443, in e
我正在尝试使用django-pipeline编译一些.less文件。当我运行collectstatic时,所有内容都被正确地复制了,然后我得到了这个错误:
Traceback (most recent call last):
File "manage.py", line 35, in <module>
execute_manager(settings)
File ".../lib/python2.7/site-packages/django/core/management/__init__.py", line 459, in exec
如果我单击"Run 'Unittest for ..“在PyCharm中,它打印:
Launching unittests with arguments python -m unittest /home/sfalk/workspace/git/m-search/python/tests/cluster/pipeline/preprocessing.py in /home/sfalk/workspace/git/m-search/python/tests/cluster/pipeline
和报告
没有发现任何测试。
但是,如果我复制了PyCharm声称运行的这一行,即
p
我正在尝试使用python code.My代码中的kafka.ReadFromKafka()方法读取kafka主题中的数据,如下所示:
from apache_beam.io.external import kafka
import apache_beam as beam
options = PipelineOptions()
with beam.Pipeline(options=options) as p:
plants = (
p
| 'read' >> kafka.ReadFromKafka({
我正在尝试将通过Microsoft Azure Active Directory使用social_django进行身份验证的用户添加到用户组。这是我的pipleline.py
from django.db.models import signals
from django.dispatch import Signal
from social.pipeline.user import *
from django.contrib.auth.models import User, Group
from social.utils import module_member
def new_user