How can I build a custom data generator for large datasets in TensorFlow

Question

With the help of Python programming, can you build a custom data generator for large datasets in TensorFlow?

Answer 1

In order to build a custom data generator for large datasets in TensorFlow, you can create a Python generator function and wrap it with tf.data.Dataset.from_generator. This is especially useful for handling large datasets that cannot fit into memory. Here is the code snippet you can refer to:

In the above code, we are using the following:

• Define a Generator Function: Use yield to stream data one sample at a time.
• Wrap with tf.data.Dataset.from_generator: Specify output types and shapes using output_signature.
• Apply Optimizations: Shuffle, batch, and prefetch data to improve performance.

Hence, this approach allows efficient data loading for large datasets, ensuring scalability and flexibility.

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