Serving a TFLite Model
Learn to use a TFLite model for inference.
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We can use the TFLite model for inference on our datasets.
The tensorflow
package supports TFLite and comes with built-in functions for inference.
Utility functions
We’ll need the softmax
utility function to convert the tensor output to probabilities. Implement it by entering the following code:
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import numpy as npimport tensorflow as tfimport osos.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'def softmax(vec):exponential = np.exp(vec)probabilities = exponential / np.sum(exponential)return probabilities# test softmax functiondummy_vec = np.array([1.5630065, -0.24305986, -0.08382231, -0.4424621])print('The output probabilities after softmax is:', softmax(dummy_vec))
Note: ...