That’s where input formats come in!

In this case, we’re using Transformers with TensorFlow, which is like having a fancy kitchen appliance that can do all sorts of cool things for us. And just like how we have different types of ingredients (like fruits and veggies), there are also different ways to format our input data.

For example, let’s say you want to make a smoothie with some bananas, strawberries, and spinach. You could chop them up into small pieces and put them in the blender all at once (which is called “batch” mode), or you could add each ingredient one by one as needed (called “streaming” mode).

In Transformers with TensorFlow, we use a similar concept to process our input data. We can either load everything into memory and then feed it through the model all at once (which is called “batch” mode), or we can stream in smaller chunks as they become available (called “streaming” mode).

Here’s an example of how this might look like using Python code:

# Load data into memory and process it all at once (in batch mode)
data = load_data()  # This could be a function that reads in the text from a file or database, for example.
batch_size = 32   # The number of sentences we want to process at once.
num_batches = len(data) // batch_size    # Calculate how many batches we need based on our data and batch size.

# Loop through each batch
for i in range(num_batches):
    # Prepare the input and label tensors for each batch
    inputs, labels = prepare_batch(data[i*batch_size:(i+1)*batch_size])   # This could be a function that prepares the input and label tensors for each batch.
    # Train our model using TensorFlow's built-in training loop
    model.train_step(inputs=inputs, labels=labels)

Or we can use streaming mode to process smaller chunks of data as they become available:

# Load data in a stream and process it one chunk at a time (in streaming mode)
# This script uses streaming mode to process smaller chunks of data as they become available.

# Open the data file and read it line by line
with open('data.txt') as file:
    for line in file:
        # Prepare the input data for the model
        inputs = prepare_input(line)
        # Use TensorFlow's built-in prediction loop to predict the output
        model.predict_step(inputs=inputs)

Input formats in Transformers with TensorFlow are like having a fancy kitchen appliance that can handle different types of ingredients and cooking methods, just like our favorite smoothie recipe.