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01_​Training

Workflow

Pre Processing and Encoding Train and Save Network Define Network Structure Generate Text Using a Many-To-One LSTM Network (Training)The workflow builds, trains, and saves an RNN with an LSTM layer to generate new fictive fairy tales. The brown nodes define the network structure. The "Pre-Processing" metanodereads fairy tales and index-encodes them. The Keras Network Learner node trains the network using index-encoded fairy tales. Finally, the trained network is converted into aTensorFlow model, and saved to a file.In order to run the example, please make sure you have the following KNIME extensions installed:* KNIME Deep Learning - Keras Integration (Labs)* KNIME Deep Learning - TensorFlow Integration* KNIME Python IntegrationYou also need a local Python installation that includes Keras. Please refer to https://www.knime.com/deeplearning#keras for installation recommendations and further information. Read Grimm'fairy talesApply dictionaryCreate overlappingsequencesdictionary sizefor regularizationoutput: sequence of hidden states?, dictionary sizeCreate inputcollectionCreate targetcollectionRead dictionary one column,each char in single row File Reader Cell Replacer Lag Column Keras Dense Layer Keras Dropout Layer Keras LSTM Layer Keras Input Layer Keras NetworkLearner Create CollectionColumn Create CollectionColumn Keras to TensorFlowNetwork Converter Resort Columns Column Filter Table Reader Reshape Text Keras NetworkWriter TensorFlowNetwork Writer Pre Processing and Encoding Train and Save Network Define Network Structure Generate Text Using a Many-To-One LSTM Network (Training)The workflow builds, trains, and saves an RNN with an LSTM layer to generate new fictive fairy tales. The brown nodes define the network structure. The "Pre-Processing" metanodereads fairy tales and index-encodes them. The Keras Network Learner node trains the network using index-encoded fairy tales. Finally, the trained network is converted into aTensorFlow model, and saved to a file.In order to run the example, please make sure you have the following KNIME extensions installed:* KNIME Deep Learning - Keras Integration (Labs)* KNIME Deep Learning - TensorFlow Integration* KNIME Python IntegrationYou also need a local Python installation that includes Keras. Please refer to https://www.knime.com/deeplearning#keras for installation recommendations and further information. Read Grimm'fairy talesApply dictionaryCreate overlappingsequencesdictionary sizefor regularizationoutput: sequence of hidden states?, dictionary sizeCreate inputcollectionCreate targetcollectionRead dictionary one column,each char in single row File Reader Cell Replacer Lag Column Keras Dense Layer Keras Dropout Layer Keras LSTM Layer Keras Input Layer Keras NetworkLearner Create CollectionColumn Create CollectionColumn Keras to TensorFlowNetwork Converter Resort Columns Column Filter Table Reader Reshape Text Keras NetworkWriter TensorFlowNetwork Writer

Download

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Nodes

01_​Training consists of the following 30 nodes(s):

Plugins

01_​Training contains nodes provided by the following 5 plugin(s):