javascript - Keras-js input data error in Node-Red (not recognized as Float32Array) -


after exporting keras model , weights, tried following code in node.js (v6.9.4), , runs ok:

const kerasjs = require('keras-js');  const model_folder = '... model_files_folder';  const model_file_path = {     model: model_folder + 'model.json',     weights: model_folder + 'model_weights.buf',     metadata: model_folder + 'model_metadata.json' };  const model_config = {     filepaths: model_file_path,     gpu: false,     filesystem: true };  const model = new kerasjs.model(model_config);  model.ready().then(() => {     const inputdata = {         'input': new float32array(5)     }     console.log('input: ' + inputdata.input);     return model.predict(inputdata)     }).then(outputdata => {         var out = outputdata['output']         console.log('output: ' + out);     }).catch(err => {         console.error(err)     })

i got result as:

> input: 0,0,0,0,0 output: 0.4446795582771301,0.0000053633639254258014,1.1930331722531662e-11,3.77190296774188e-8,1.060054266588395e-10

i changed settings.js file of node-red include keras-js:

functionglobalcontext: {     os:require('os'),     kerasjs:require('keras-js')     // ... },

and test function wrote in node-red (v0.17.5):

const kerasjs = global.get('kerasjs');  (...model_folder,  model_config, etc.  same above codes tested in node.js...)  model.ready()   .then(() => {     const inputdata = {     'input': new float32array(5)     }     node.warn('input: ' + inputdata.input);     return model.predict(inputdata)   })   .then(outputdata => {     var out = outputdata['output']     node.warn('output: ' + out);     msg.payload = {         'output': out     };     node.send(msg);   })   .catch(err => {     node.error(err);   })  return null;

but got following error:

function : (error) "error: predict() must take object values flattened data float32array."

i got confused since assigned inputdata.input float32array already. me fix this? thank you!


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