pipeline

Given this in my app startup ... app.Use((context, next) => { return next.Invoke(); }).UseStageMarker(PipelineStage.PostAuthenticate); app.Use((context, next) => { return next.Invoke(); }).UseStageMarker(PipelineStage.Authenticate); ... why does the PostAuthenticate code execute before the Authenticate code? I don't mean "why does the first app.use get called before the second app.use" I mean: Why does the first invoke get called before the second given that that the second should be happening earlier in the request pipeline? EDIT Related to this problem: How am I getting a windows identity in

I am working in scikit and I am trying to tune my XGBoost. I made an attempt to use a nested cross-validation using the pipeline for the rescaling of the training folds (to avoid data leakage and overfitting) and in parallel with GridSearchCV for param tuning and cross_val_score to get the roc_auc score at the end. from imblearn.pipeline import Pipeline from sklearn.model_selection import RepeatedKFold from sklearn.model_selection import GridSearchCV from sklearn.model_selection import cross_val_score from xgboost import XGBClassifier std_scaling = StandardScaler() algo = XGBClassifier() steps

I'm trying to write a program in C which replicates the pipeline: gst-launch -v filesrc location="bbb.mp4" ! decodebin2 ! ffmpegcolorspace ! autovideosink DecodeBin2 has a dynamic pad and I've attached a callback to handle its creation. I am unable to link it to ffmpegcolorspace however because the pad capability is always video/quicktime. I would like it to be video/x-raw-yuv or something else which is compatible with ffmpegcolorspace. Is this possible to force/select the output type of decodebin2? Thanks. EDIT: Please do not recommend playbin. I'm trying to learn how how to make pipelines.

I have text as shown : list1 = ["My name is xyz", "My name is pqr", "I work in abc"] The above will be training set for clustering text using kmeans. list2 = ["My name is xyz", "I work in abc"] The above is my test set. I have built a vectorizer and the model as shown below: vectorizer = TfidfVectorizer(min_df = 0, max_df=0.5, stop_words = "english", charset_error = "ignore", ngram_range = (1,3)) vectorized = vectorizer.fit_transform(list1) km=KMeans(n_clusters=2, init='k-means++', n_init=10, max_iter=1000, tol=0.0001, precompute_distances=True, verbose=0, random_state=None, copy_x=True, n

I have Jenkins pipeline with an Input step, and I would like to submit this input(single string argument) via a script. So far I am trying with curl, ideally I'll be sending it via Python requests library. This should be an easy POST request, however with CSRF it becomes tricky. I've obtained Jenkins-Crumb (using curl in this case, from the same machine and same bash session), but still can't send the content... I'm sending Jenkins-Crumb:XXX header, just like it is explained at https://wiki.jenkins-ci.org/display/JENKINS/Remote+access+API my request looks like this: curl -vvv -X POST --user '$

Is piping parameter into line is working only for functions that accept one parameter? If we look at the example at Chris Smiths' page , // Using the Pipe-Forward operator (|>) let photosInMB_pipeforward = @"C:\Users\chrsmith\Pictures\" |> filesUnderFolder |> Seq.map fileInfo |> Seq.map fileSize |> Seq.fold (+) 0L |> bytesToMB where his filesUnderFolder function was expecting only rootFolder parameter, what if the function was expecting two parameters, i.e. let filesUnderFolder size rootFolder Then this does not work: // Using the Pipe-Forward operator (|>) let size= 4 let photosInMB