pipeline

问题 Documentation is spread out and it's a bit hard grasp how to make use of the pipeline concept in circle ci language? Also what's the point of pipelines and pipeline variables? The following docs were useful but were far from enough for me to figure out how they actually work: https://circleci.com/docs/2.0/pipelines https://circleci.com/docs/2.0/build-processing (Enabling pipelines) https://circleci.com/docs/2.0/pipeline-variables/#conditional-workflows (Pipeline variables and conditional

问题 Documentation is spread out and it's a bit hard grasp how to make use of the pipeline concept in circle ci language? Also what's the point of pipelines and pipeline variables? The following docs were useful but were far from enough for me to figure out how they actually work: https://circleci.com/docs/2.0/pipelines https://circleci.com/docs/2.0/build-processing (Enabling pipelines) https://circleci.com/docs/2.0/pipeline-variables/#conditional-workflows (Pipeline variables and conditional

问题 I have a question about implementing pipeline using Dataflow TPL library. My case is that I have a software that needs to process some tasks concurrently. Processing looks like this: first we process album at global level, and then we go inside album and process each picture individually. Let's say that application has got processing slots and they are configurable (for the sake of example assume slots = 2). This means that application can process either: a) two albums on the same time b) one

问题 The ELI5 library provides the function transform_feature_names to retrieve the feature names for the output of an sklearn transformer. The documentation says that the function works out of the box when the transformer includes nested Pipelines. I'm trying to get the function to work on a simplified version of the example in the answer to SO 57528350. My simplified example doesn't need Pipeline , but in real life I will need it in order to add steps to categorical_transformer , and I will also

问题 The ELI5 library provides the function transform_feature_names to retrieve the feature names for the output of an sklearn transformer. The documentation says that the function works out of the box when the transformer includes nested Pipelines. I'm trying to get the function to work on a simplified version of the example in the answer to SO 57528350. My simplified example doesn't need Pipeline , but in real life I will need it in order to add steps to categorical_transformer , and I will also

问题 In Azure Devops when your Maven build task fails it will display an an error like below in the build summary: Maven build error Now if you click in and scroll up you will be able to find the error next to the reactor summary. This is easy enough to do at home with a mouse and a big screen but for some of our devs on trains or in cafes it can be quite an effort for them to find the error. I want to be able to make the error easier to find. Some suggestions I've thought of but not sure how to

问题 I wonder if it is possible to use a MultilabelBinarizer within a ColumnTransformer. I have a toy pandas dataframe like: df = pd.DataFrame({"id":[1,2,3], "text": ["some text", "some other text", "yet another text"], "label": [["white", "cat"], ["black", "cat"], ["brown", "dog"]]}) preprocess = ColumnTransformer( [ ('vectorizer', CountVectorizer(), 'text'), ('binarizer', MultiLabelBinarizer(), ['label']), ], remainder='drop') this code, however, throws an exception: ~/lib/python3.7/site

问题 In below example, if shell script shell_script.sh sends a job to cluster, is it possible to have snakemake aware of that cluster job's completion? That is, first, file a should be created by shell_script.sh which sends its own job to the cluster, and then once this cluster job is completed, file b should be created. For simplicity, let's assume that snakemake is run locally meaning that the only cluster job originating is from shell_script.sh and not by snakemake . localrules: that_job rule

问题 I am trying to pickle a sklearn machine-learning model, and load it in another project. The model is wrapped in pipeline that does feature encoding, scaling etc. The problem starts when i want to use self-written transformers in the pipeline for more advanced tasks. Let's say I have 2 projects: train_project: it has the custom transformers in src.feature_extraction.transformers.py use_project: it has other things in src, or has no src catalog at all If in "train_project" I save the pipeline

问题 The Goal is to have everyone get a notification for every failed pipeline (at their discretion). Currently any of us can run a pipeline on this project branch, and the creator of the pipeline gets an email, no one else does. I have tried setting the notification level to watch and custom (with failed pipelines checked) at project, group and global levels without success. The help page regarding notifications says the failed pipeline checkbox for custom notification levels notifies the author