Reading a TFRecord File

TFrecord-Reader.py

label_size = 1 # the length of the previously written label
feature_size = 256 # the length of the previously written feature lists
def map_fn(serialized_example):
    feature = {
        'label': tf.io.FixedLenFeature([label_)size], tf.int64),
        'features': tf.io.FixedLenFeature([feature_size], tf.float32)
    }
    example = tf.io.parse_single_example(serialized_example, feature)
    features = example['features']
    label = tf.cast(example['label'], tf.int32)
    return features, label

dataset = tf.data.TFRecordDataset('examples.tfrecord')
dataset = dataset.map(map_fn)
dataset = dataset.batch(1)

# to see the data
for features, label in dataset.take(1):
  print(features.shape, label.shape)