from pprint import pprint

import tensorflow as tf

dataset = tf.data.experimental.make_csv_dataset(
    "training.csv",
    batch_size=2,
    label_name="label",
    num_epochs=1,
    shuffle=False,
)

first_features, first_labels = next(iter(dataset))
row_count = sum(int(labels.shape[0]) for _, labels in dataset)

rounded_features = {
    name: [round(float(value), 2) for value in tensor.numpy().tolist()]
    for name, tensor in first_features.items()
}

print(type(dataset).__name__)
pprint(dataset.element_spec)
print(rounded_features)
print(first_labels.numpy().tolist())
print(f"rows={row_count}")