Audioset records extraction

#Till now, I have used grep and stored the index of the Clapping feature in a class_label_index variable. Then,
#I have stored the Tensorflow IDs in an examples variable.
#Then, I will store the prefixes of the tfrecord separatley in a tf_record_prefixes variable
#Then, I create the tfrecord_filenames variable to store the tfrecord in a file format like '['bal_train/1I.tfrecord', 'bal_train/0F.tfrecord']'
#When I run this part of the code, I get NotFoundError: bal_train/1I.tfrecord

audio_embeddings_dict = {}
audio_labels_dict = {}

#Load embeddings
sess = tf.Session()
for tfrecord in tfrecord_filenames:
    for example in tf.python_io.tf_record_iterator(tfrecord):
        tf_example = tf.train.Example.FromString(example)
        vid_id = tf_example.features.feature['video_id'].bytes_list.value[0].decode(encoding = 'UTF-8')
        if vid_id in examples:
            example_label = list(np.asarray(tf_example.features.feature['labels'].int64_list.value))
            tf_seq_example = tf.train.SequenceExample.FromString(example)
            n_frames = len(tf_seq_example.feature_lists.feature_list['audio_embedding'].feature)
            
            audio_frame = []
            for i in range(n_frames):
                audio_frame.append(tf.cast(tf.decode_raw(tf_seq_example.feature_lists.feature_list['audio_embedding'].
                                                         feature[i].bytes_list.value[0],tf.unit8
                                                        ),tf.float32),eval(session = sess))
                audio_embeddings_dict[vid_id] = audio_frame
                audio_labels_dict[vid_id] = example_label
                
#On investigating the trace of error, I find that the error lies in python_io.tf_record_iterator. I am unclear as to how I will resolve this.