Serving a TensorFlow Model

Learn to use a TensorFlow image classification model for inference.

We can use the TensorFlow model for inference on our datasets.

Utility functions

First, we need to define the softmax utility function.

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import tensorflow as tf
import numpy as np
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
def softmax(vec):
exponential = np.exp(vec)
probabilities = exponential / np.sum(exponential)
return probabilities
# test softmax function
dummy_vec = np.array([1.5630065, -0.24305986, -0.08382231, -0.4424621])
print('The output probabilities after softmax is:', softmax(dummy_vec))

Note: The softmax utility function will convert the model prediction into probabilities that sum to 1. ...