data_compat.py

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Utilities to migrate legacy protos to their modern equivalents."""


import numpy as np

from tensorboard.compat.proto import event_pb2
from tensorboard.compat.proto import summary_pb2
from tensorboard.plugins.audio import metadata as audio_metadata
from tensorboard.plugins.histogram import metadata as histogram_metadata
from tensorboard.plugins.image import metadata as image_metadata
from tensorboard.plugins.scalar import metadata as scalar_metadata
from tensorboard.util import tensor_util


def migrate_event(event):
    if not event.HasField("summary"):
        return event
    old_values = event.summary.value
    new_values = [migrate_value(value) for value in old_values]
    # Optimization: Don't create a new event if there were no changes.
    if len(old_values) == len(new_values) and all(
        x is y for (x, y) in zip(old_values, new_values)
    ):
        return event
    result = event_pb2.Event()
    result.CopyFrom(event)
    del result.summary.value[:]
    result.summary.value.extend(new_values)
    return result


def migrate_value(value):
    """Convert `value` to a new-style value, if necessary and possible.

    An "old-style" value is a value that uses any `value` field other than
    the `tensor` field. A "new-style" value is a value that uses the
    `tensor` field. TensorBoard continues to support old-style values on
    disk; this method converts them to new-style values so that further
    code need only deal with one data format.

    Arguments:
      value: A `Summary.Value` object. This argument is not modified.

    Returns:
      If the `value` is an old-style value for which there is a new-style
      equivalent, the result is the new-style value. Otherwise---if the
      value is already new-style or does not yet have a new-style
      equivalent---the value will be returned unchanged.

    :type value: Summary.Value
    :rtype: Summary.Value
    """
    handler = {
        "histo": _migrate_histogram_value,
        "image": _migrate_image_value,
        "audio": _migrate_audio_value,
        "simple_value": _migrate_scalar_value,
    }.get(value.WhichOneof("value"))
    return handler(value) if handler else value


def make_summary(tag, metadata, data):
    tensor_proto = tensor_util.make_tensor_proto(data)
    return summary_pb2.Summary.Value(
        tag=tag, metadata=metadata, tensor=tensor_proto
    )


def _migrate_histogram_value(value):
    histogram_value = value.histo
    bucket_lefts = [histogram_value.min] + histogram_value.bucket_limit[:-1]
    bucket_rights = histogram_value.bucket_limit[:-1] + [histogram_value.max]
    bucket_counts = histogram_value.bucket
    buckets = np.array(
        [bucket_lefts, bucket_rights, bucket_counts], dtype=np.float32
    ).transpose()

    summary_metadata = histogram_metadata.create_summary_metadata(
        display_name=value.metadata.display_name or value.tag,
        description=value.metadata.summary_description,
    )

    return make_summary(value.tag, summary_metadata, buckets)


def _migrate_image_value(value):
    image_value = value.image
    data = [
        str(image_value.width).encode("ascii"),
        str(image_value.height).encode("ascii"),
        image_value.encoded_image_string,
    ]

    summary_metadata = image_metadata.create_summary_metadata(
        display_name=value.metadata.display_name or value.tag,
        description=value.metadata.summary_description,
        converted_to_tensor=True,
    )
    return make_summary(value.tag, summary_metadata, data)


def _migrate_audio_value(value):
    audio_value = value.audio
    data = [[audio_value.encoded_audio_string, b""]]  # empty label
    summary_metadata = audio_metadata.create_summary_metadata(
        display_name=value.metadata.display_name or value.tag,
        description=value.metadata.summary_description,
        encoding=audio_metadata.Encoding.Value("WAV"),
        converted_to_tensor=True,
    )
    return make_summary(value.tag, summary_metadata, data)


def _migrate_scalar_value(value):
    scalar_value = value.simple_value
    summary_metadata = scalar_metadata.create_summary_metadata(
        display_name=value.metadata.display_name or value.tag,
        description=value.metadata.summary_description,
    )
    return make_summary(value.tag, summary_metadata, scalar_value)