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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def tf_summary_to_dict(tf_summary_str_or_pb, namespace=""):
 """Convert a Tensorboard Summary to a dictionary Accepts either a tensorflow.summary.Summary or one encoded as a string. """

    values = {}
    if isinstance(tf_summary_str_or_pb, Summary):
        summary_pb = tf_summary_str_or_pb
    elif isinstance(tf_summary_str_or_pb, Event):
        summary_pb = tf_summary_str_or_pb.summary
        values["global_step"] = tf_summary_str_or_pb.step
        values["_timestamp"] = tf_summary_str_or_pb.wall_time
    else:
        summary_pb = Summary()
        summary_pb.ParseFromString(tf_summary_str_or_pb)

    for value in summary_pb.value:
        kind = value.WhichOneof("value")
        if kind == "simple_value":
            values[namespaced_tag(value.tag, namespace)] = value.simple_value
        elif kind == "image":
            from PIL import Image
            image = wandb.Image(Image.open(
                six.BytesIO(value.image.encoded_image_string)))
            tag_idx = value.tag.rsplit('/', 1)
            if len(tag_idx) > 1 and tag_idx[1].isdigit():
                tag, idx = tag_idx
                values.setdefault(history_image_key(tag), []).append(image)
            else:
                values[history_image_key(value.tag)] = image
        # Coming soon...
        # elif kind == "audio":
        #    audio = wandb.Audio(six.BytesIO(value.audio.encoded_audio_string),
        #                        sample_rate=value.audio.sample_rate, content_type=value.audio.content_type)
        elif kind == "histo":
            first = value.histo.bucket_limit[0] + \
                value.histo.bucket_limit[0] - value.histo.bucket_limit[1]
            last = value.histo.bucket_limit[-2] + \
                value.histo.bucket_limit[-2] - value.histo.bucket_limit[-3]
            np_histogram = (list(value.histo.bucket), [
                first] + value.histo.bucket_limit[:-1] + [last])
            values[namespaced_tag(value.tag)] = wandb.Histogram(
                np_histogram=np_histogram)

    return values