Model with softmax output layer not outputing probabilities but just 1 and 0

[croraf]

I'm testing the model provided in node-js example https://github.com/tensorflow/tfjs-examples/blob/master/mnist-node/model.js to classify images of numbers into classes 0 to 9.

It is a tf.sequential() model, and its final layer is model.add(tf.layers.dense({ units: 10, activation: "softmax" }));

Therefore the prediction should output probabilities per class, but this is not happening. Instead only 0s and 1s (in a one-hot fashion) are outputed in the following logging.

const predictions = model.predict(data);
predictions.print();

How to get the probabilities of specific image belonging to specific class

[gaikwadrahul8]

Hi, @croraf

I apologize for the delayed response and you're absolutely right. The final layer in your model (tf.layers.dense({ units: 10, activation: 'softmax' })) is configured correctly to output probabilities for each class (0-9). However, the way you're interpreting the model's prediction (predictions.print()) might be misleading. that's why maybe you're seeing only 0s and 1s because one-Hot encoded predictions format, the softmax activation ensures the output is a probability distribution between 0 and 1, where each element represents the probability of the input belonging to a specific class.When you print the tensor using predictions.print(), TensorFlow might display the values in a one-hot encoded format. This means the element with the highest probability will be set to 1 and all others will be 0.

Could you please try the below code snippet and see if it is working as expected or not ? If the issue still persists please let us know. Thank you for your cooperation and patience.

const predictions = model.predict(data);
const classProbabilities = predictions.dataSync(); // Use dataSync() for Node.js

// Loop through each element (probability for each class)
for (let i = 0; i < classProbabilities.length; i++) {
  console.log(`Probability of class ${i}: ${classProbabilities[i]}`);
}

[croraf]

It outputs the same (except in one value where it is basically 0)