tensorflow.js

I have a 2d tensor and I would like to get the value of the element of index i,j value. There are many ways one can retrieve the value of the element [i,j] of a tensor2d Consider the following: Using slice to retrieve directly the tensor2d starting at the coordinate [i, j] that has the size [1, 1] h.slice([i, j], 1).as1D().print() Get the row i as a tensor2d with gather and then the element j with slice h.gather(tf.tensor1d([i], 'int32')).slice([0, j], [1, 1]).as1D().print() Using stack to retrieve the row i as tensor1d and slice to retrieve the desired element h.unstack()[i].slice([j], [1])

I have the following example code. I'm able to see the correct result in the console from the print function. // Define a model for linear regression. const model = tf.sequential(); model.add(tf.layers.dense({units: 1, inputShape: [1]})); model.add(tf.layers.dense({units: 4, inputShape: [1]})); model.add(tf.layers.dense({units: 10, inputShape: [1]})); model.add(tf.layers.dense({units: 1, inputShape: [1]})); // Prepare the model for training: Specify the loss and the optimizer. model.compile({loss: 'meanSquaredError', optimizer: 'sgd'}); // Generate some synthetic data for training. const xs =

I'm new to Machine Learning and Tensorflow, since I don't know python so I decide to use there javascript version (maybe more like a wrapper). The problem is I tried to build a model that process the Natural Language. So the first step is tokenizer the text in order to feed the data to model. I did a lot research, but most of them are using python version of tensorflow that use method like: tf.keras.preprocessing.text.Tokenizer which I can't find similar in tensorflow.js. I'm stuck in this step and don't know how can I transfer text to vector that can feed to model. Please help :) To transform

Several ways of retraining MobileNet for use with Tensorflow.js have failed for me. Is there any way to use a retrained model with Tensorflow.js? Both using the modern, hub-based tutorial, as well as using retrain.py seem to fail. Convert output of retrain.py to tensorflow.js Error converting keras model to tfjs: duplicate weight name Variable as well as some other open questions Retrain an Image Classifier in tensorflow js Loading of mobilenet v2 works, but pretrained mobilenet v2 fails Can't convert TensorFlow saved model to tfjs_layers_model webmodel The top two other questions show the

I have converted a keras model to tensorflow json format and saved it locally in my computer. I am trying to load that json model in a javascript code using the below command model = await tf.loadModel('web_model') But the model is not getting loaded. Is there a way to load tensorflow json model from local file system? I know you're trying to load your model in a browser but if anybody lands here that's trying to do it in Node, here's how: const tf = require("@tensorflow/tfjs"); const tfn = require("@tensorflow/tfjs-node"); const handler = tfn.io.fileSystem("./path/to/your/model.json"); const

After compiling and training my custom model, I saved it and got two files such as .bin and .json. Further, I loaded that custom model on another page where I'm giving images as input which I used for training of that model and getting the prediction for those images based on the loaded custom model. Since it works fine for some of the images but returning the wrong prediction for other images. This is my code: $("#predict-button").click(async function(){ let image= $('#selected-image').get(0); let image1 = $('#selected-image1').get(0); console.log('image:::',image); console.log('image1:::'