TensorFlow 2 Network Executor

Options

General Settings

Back end

The deep learning back end which is used to execute the input network for the given input data.

Input batch size

The number of rows that are processed at a time.

Inputs

Conversion

The converter that is used to transform the selected input columns into a format that is accepted by the respective network input specification.

Input columns

The table columns that are part of the respective network input. The availability of a column depends on the currently selected input converter.

Outputs

Conversion

The converter that is used to transform the network output into table columns.

Output columns prefix

The prefix that is used to distinguish between the columns of the different outputs.

Views

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Workflows

• 01_BERT_Sentiment_AnalysisKNIME Hub
• 02_Tensorflow2_Autoencoder_for_Fraud_Detection_TrainingKNIME Hub
• 03_Tensorflow2_CellSegmentationKNIME Hub
• 03. Train Model - solutionKNIME Hub
• 04_Train_a_MLPKNIME Hub
• Show all 11 workflows

Links

• KNIME Deep Learning Documentation

  docs.knime.com/latest/deep_learning_installation_guide/index.html

Developers