fmcquillan99 removed a comment on issue #409: DL: Add online docs for madlib_keras functions URL: https://github.com/apache/madlib/pull/409#issuecomment-500075322 (1) all of the output table descriptions for fit, evaluate and predict could use a line space and better formatting like the other DL docs i.e., is hard to read: {code} The output table ('model' above) contains the following columns: model_data: Byte array containing the weights of the neural net. model_arch: A JSON representation of the model architecture used in training. {code} . {code} . select madlib.madlib_keras_fit('usage'); madlib_keras_fit ------------------------------------------------------------------------------- ----------------------------------------------------------------------- USAGE ----------------------------------------------------------------------- SELECT madlib.madlib_keras_fit( source_table, -- Name of the table containing the training data model, -- Name of the output table containing the model model_arch_table, -- Name of the table containing the model architecture model_arch_id, -- This is the id in 'model_arch_table' containing the model architecture compile_params, -- Parameters passed to the compile method of the Keras model class fit_params, -- Parameters passed to the fit method of the Keras model class num_iterations, -- Number of iterations to train. gpus_per_host, -- Number of GPUs per segment host to be used for training validation_table, -- Name of the table containing the validation dataset metrics_compute_frequency, -- Frequency to compute per-iteration metrics warm_start, -- Flag to enable warm start name, -- Free text string to identify a name description -- Free text string to provide a description ) ); ----------------------------------------------------------------------- OUTPUT ----------------------------------------------------------------------- The output table ('model' above) contains the following columns: model_data: Byte array containing the weights of the neural net. model_arch: A JSON representation of the model architecture used in training. A summary table ('<model>_summary') is created to store various training statistics as well as the input parameters. {code} (2) missing params {code} madlib=# select madlib.load_keras_model('usage'); load_keras_model ------------------------------------------------------------------------------------------ --------------------------------------------------------------------------- USAGE --------------------------------------------------------------------------- SELECT madlib.load_keras_model( keras_model_arch_table VARCHAR, -- Output table to load keras model arch. model_arch JSON -- JSON of the model architecture to insert. ); --------------------------------------------------------------------------- OUTPUT --------------------------------------------------------------------------- The output table produced by load_keras_model contains the following columns: 'model_id' -- SERIAL PRIMARY KEY. Model ID. 'model_arch' -- JSON. JSON blob of the model architecture. 'model_weights' -- bytea. weights of the model for warm start. '__internal_madlib_id__' -- TEXT. Unique id for model arch. {code} The usage is missing some parameters: {code} CREATE OR REPLACE FUNCTION MADLIB_SCHEMA.load_keras_model( keras_model_arch_table VARCHAR, model_arch JSON, model_weights bytea, name TEXT, description TEXT ) {code} I will update the user docs probably on Mon if you want to wait and copy after I do that.
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