How to load a big file in tensorflow?

@wilmer.lemke 

To load a big file in TensorFlow, you can use the tf.data module which provides a collection of classes and functions for easily creating complex input pipelines. Here is a general approach to loading a big file in TensorFlow:

1. Create a dataset object using tf.data.TextLineDataset or tf.data.FixedLengthRecordDataset depending on the type of data in the file.

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dataset = tf.data.TextLineDataset("path/to/bigfile.txt")

1. If needed, preprocess the data and parse the lines into tensors using the map method. You can use tf.strings.split to split a string into a tensor of strings and tf.strings.to_number to convert a string tensor to a numerical tensor.

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dataset = dataset.map(lambda x: tf.strings.to_number(tf.strings.split(x, ","), out_type=tf.float32))

1. Shuffle, batch, and prefetch the dataset to optimize performance.

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dataset = dataset.shuffle(buffer_size=1000)
dataset = dataset.batch(batch_size)
dataset = dataset.prefetch(buffer_size=tf.data.experimental.AUTOTUNE)

1. Finally, create an iterator to iterate over the dataset and access the data in batches.

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iterator = iter(dataset)
batch_data = next(iterator)

By using tf.data module, you can efficiently load and process large datasets in TensorFlow.