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# 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."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
from tensorboard.plugins.audio import metadata as audio_metadata
from tensorboard.plugins.image import metadata as image_metadata
from tensorboard.plugins.histogram import metadata as histogram_metadata
from tensorboard.plugins.scalar import metadata as scalar_metadata
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 `tf.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: tf.Summary.Value
:rtype: tf.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 _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]).transpose()
tensor_proto = tf.make_tensor_proto(buckets)
summary_metadata = histogram_metadata.create_summary_metadata(
display_name=value.metadata.display_name or value.tag,
description=value.metadata.summary_description)
return tf.Summary.Value(tag=value.tag,
metadata=summary_metadata,
tensor=tensor_proto)
def _migrate_image_value(value):
image_value = value.image
data = [tf.compat.as_bytes(str(image_value.width)),
tf.compat.as_bytes(str(image_value.height)),
tf.compat.as_bytes(image_value.encoded_image_string)]
tensor_proto = tf.make_tensor_proto(data)
summary_metadata = image_metadata.create_summary_metadata(
display_name=value.metadata.display_name or value.tag,
description=value.metadata.summary_description)
return tf.Summary.Value(tag=value.tag,
metadata=summary_metadata,
tensor=tensor_proto)
def _migrate_audio_value(value):
audio_value = value.audio
data = [[audio_value.encoded_audio_string, b'']] # empty label
tensor_proto = tf.make_tensor_proto(data)
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'))
return tf.Summary.Value(tag=value.tag,
metadata=summary_metadata,
tensor=tensor_proto)
def _migrate_scalar_value(value):
scalar_value = value.simple_value
tensor_proto = tf.make_tensor_proto(scalar_value)
summary_metadata = scalar_metadata.create_summary_metadata(
display_name=value.metadata.display_name or value.tag,
description=value.metadata.summary_description)
return tf.Summary.Value(tag=value.tag,
metadata=summary_metadata,
tensor=tensor_proto)
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