def read_from_tfr()

in 07_training/serverlessml/flowers/ingest/tfrecords.py [0:0]

• 14 lines of code
• 1 McCabe index (conditional complexity)

    def read_from_tfr(self, proto):
        feature_description = {
            'image': tf.io.VarLenFeature(tf.float32),
            'shape': tf.io.VarLenFeature(tf.int64),
            'label': tf.io.FixedLenFeature([], tf.string, default_value=''),
            'label_int': tf.io.FixedLenFeature([], tf.int64, default_value=0),
        }
        rec = tf.io.parse_single_example(
            proto, feature_description
        )
        shape = tf.sparse.to_dense(rec['shape'])
        img = tf.reshape(tf.sparse.to_dense(rec['image']), shape)
        label_int = rec['label_int']
        return img, label_int