Writing a TFRecord File

TFRecord-Writer.py

with tf.io.TFRecordWriter('examples.tfrecord') as training_file:
    for features, label in batch:
        features = {
            'label': tf.train.Feature(int64_list=tf.train.Int64List(value=[label])),
            'features': tf.train.Feature(float_list=tf.train.FloatList(value=features)) # expects list, so if numpy use .tolist() and ensure it's 1-D
        }
        example_proto = tf.train.Example(features=tf.train.Features(feature=features))
        training_file.write(example_proto.SerializeToString())