348 lines
13 KiB
Python
348 lines
13 KiB
Python
|
# Copyright 2016 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.
|
||
|
|
# ==============================================================================
|
||
|
|
|
||
|
|
"""Tensor summaries for exporting information about a model.
|
||
|
|
|
||
|
|
See the @{$python/summary} guide.
|
||
|
|
"""
|
||
|
|
|
||
|
|
from __future__ import absolute_import
|
||
|
|
from __future__ import division
|
||
|
|
from __future__ import print_function
|
||
|
|
|
||
|
|
from google.protobuf import json_format as _json_format
|
||
|
|
|
||
|
|
# exports Summary, SummaryDescription, Event, TaggedRunMetadata, SessionLog
|
||
|
|
# pylint: disable=unused-import
|
||
|
|
from tensorflow.core.framework.summary_pb2 import Summary
|
||
|
|
from tensorflow.core.framework.summary_pb2 import SummaryDescription
|
||
|
|
from tensorflow.core.util.event_pb2 import Event
|
||
|
|
from tensorflow.core.util.event_pb2 import SessionLog
|
||
|
|
from tensorflow.core.util.event_pb2 import TaggedRunMetadata
|
||
|
|
# pylint: enable=unused-import
|
||
|
|
|
||
|
|
|
||
|
|
from tensorflow.python.eager import context as _context
|
||
|
|
from tensorflow.python.framework import constant_op as _constant_op
|
||
|
|
from tensorflow.python.framework import dtypes as _dtypes
|
||
|
|
from tensorflow.python.framework import ops as _ops
|
||
|
|
from tensorflow.python.ops import gen_logging_ops as _gen_logging_ops
|
||
|
|
from tensorflow.python.ops import gen_summary_ops as _gen_summary_ops # pylint: disable=unused-import
|
||
|
|
from tensorflow.python.ops import summary_op_util as _summary_op_util
|
||
|
|
|
||
|
|
# exports tensor-related summaries
|
||
|
|
# pylint: disable=unused-import
|
||
|
|
from tensorflow.python.ops.summary_ops import tensor_summary
|
||
|
|
# pylint: enable=unused-import
|
||
|
|
|
||
|
|
# exports text
|
||
|
|
# pylint: disable=unused-import
|
||
|
|
from tensorflow.python.summary.text_summary import text_summary as text
|
||
|
|
# pylint: enable=unused-import
|
||
|
|
|
||
|
|
# exports FileWriter, FileWriterCache
|
||
|
|
# pylint: disable=unused-import
|
||
|
|
from tensorflow.python.summary.writer.writer import FileWriter
|
||
|
|
from tensorflow.python.summary.writer.writer_cache import FileWriterCache
|
||
|
|
# pylint: enable=unused-import
|
||
|
|
|
||
|
|
from tensorflow.python.util import compat as _compat
|
||
|
|
from tensorflow.python.util.tf_export import tf_export
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('summary.scalar')
|
||
|
|
def scalar(name, tensor, collections=None, family=None):
|
||
|
|
"""Outputs a `Summary` protocol buffer containing a single scalar value.
|
||
|
|
|
||
|
|
The generated Summary has a Tensor.proto containing the input Tensor.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
name: A name for the generated node. Will also serve as the series name in
|
||
|
|
TensorBoard.
|
||
|
|
tensor: A real numeric Tensor containing a single value.
|
||
|
|
collections: Optional list of graph collections keys. The new summary op is
|
||
|
|
added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
|
||
|
|
family: Optional; if provided, used as the prefix of the summary tag name,
|
||
|
|
which controls the tab name used for display on Tensorboard.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
A scalar `Tensor` of type `string`. Which contains a `Summary` protobuf.
|
||
|
|
|
||
|
|
Raises:
|
||
|
|
ValueError: If tensor has the wrong shape or type.
|
||
|
|
"""
|
||
|
|
if _summary_op_util.skip_summary():
|
||
|
|
return _constant_op.constant('')
|
||
|
|
with _summary_op_util.summary_scope(
|
||
|
|
name, family, values=[tensor]) as (tag, scope):
|
||
|
|
val = _gen_logging_ops.scalar_summary(tags=tag, values=tensor, name=scope)
|
||
|
|
_summary_op_util.collect(val, collections, [_ops.GraphKeys.SUMMARIES])
|
||
|
|
return val
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('summary.image')
|
||
|
|
def image(name, tensor, max_outputs=3, collections=None, family=None):
|
||
|
|
"""Outputs a `Summary` protocol buffer with images.
|
||
|
|
|
||
|
|
The summary has up to `max_outputs` summary values containing images. The
|
||
|
|
images are built from `tensor` which must be 4-D with shape `[batch_size,
|
||
|
|
height, width, channels]` and where `channels` can be:
|
||
|
|
|
||
|
|
* 1: `tensor` is interpreted as Grayscale.
|
||
|
|
* 3: `tensor` is interpreted as RGB.
|
||
|
|
* 4: `tensor` is interpreted as RGBA.
|
||
|
|
|
||
|
|
The images have the same number of channels as the input tensor. For float
|
||
|
|
input, the values are normalized one image at a time to fit in the range
|
||
|
|
`[0, 255]`. `uint8` values are unchanged. The op uses two different
|
||
|
|
normalization algorithms:
|
||
|
|
|
||
|
|
* If the input values are all positive, they are rescaled so the largest one
|
||
|
|
is 255.
|
||
|
|
|
||
|
|
* If any input value is negative, the values are shifted so input value 0.0
|
||
|
|
is at 127. They are then rescaled so that either the smallest value is 0,
|
||
|
|
or the largest one is 255.
|
||
|
|
|
||
|
|
The `tag` in the outputted Summary.Value protobufs is generated based on the
|
||
|
|
name, with a suffix depending on the max_outputs setting:
|
||
|
|
|
||
|
|
* If `max_outputs` is 1, the summary value tag is '*name*/image'.
|
||
|
|
* If `max_outputs` is greater than 1, the summary value tags are
|
||
|
|
generated sequentially as '*name*/image/0', '*name*/image/1', etc.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
name: A name for the generated node. Will also serve as a series name in
|
||
|
|
TensorBoard.
|
||
|
|
tensor: A 4-D `uint8` or `float32` `Tensor` of shape `[batch_size, height,
|
||
|
|
width, channels]` where `channels` is 1, 3, or 4.
|
||
|
|
max_outputs: Max number of batch elements to generate images for.
|
||
|
|
collections: Optional list of ops.GraphKeys. The collections to add the
|
||
|
|
summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
|
||
|
|
family: Optional; if provided, used as the prefix of the summary tag name,
|
||
|
|
which controls the tab name used for display on Tensorboard.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
|
||
|
|
buffer.
|
||
|
|
"""
|
||
|
|
if _summary_op_util.skip_summary():
|
||
|
|
return _constant_op.constant('')
|
||
|
|
with _summary_op_util.summary_scope(
|
||
|
|
name, family, values=[tensor]) as (tag, scope):
|
||
|
|
val = _gen_logging_ops.image_summary(
|
||
|
|
tag=tag, tensor=tensor, max_images=max_outputs, name=scope)
|
||
|
|
_summary_op_util.collect(val, collections, [_ops.GraphKeys.SUMMARIES])
|
||
|
|
return val
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('summary.histogram')
|
||
|
|
def histogram(name, values, collections=None, family=None):
|
||
|
|
# pylint: disable=line-too-long
|
||
|
|
"""Outputs a `Summary` protocol buffer with a histogram.
|
||
|
|
|
||
|
|
Adding a histogram summary makes it possible to visualize your data's
|
||
|
|
distribution in TensorBoard. You can see a detailed explanation of the
|
||
|
|
TensorBoard histogram dashboard
|
||
|
|
[here](https://www.tensorflow.org/get_started/tensorboard_histograms).
|
||
|
|
|
||
|
|
The generated
|
||
|
|
[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
|
||
|
|
has one summary value containing a histogram for `values`.
|
||
|
|
|
||
|
|
This op reports an `InvalidArgument` error if any value is not finite.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
name: A name for the generated node. Will also serve as a series name in
|
||
|
|
TensorBoard.
|
||
|
|
values: A real numeric `Tensor`. Any shape. Values to use to
|
||
|
|
build the histogram.
|
||
|
|
collections: Optional list of graph collections keys. The new summary op is
|
||
|
|
added to these collections. Defaults to `[GraphKeys.SUMMARIES]`.
|
||
|
|
family: Optional; if provided, used as the prefix of the summary tag name,
|
||
|
|
which controls the tab name used for display on Tensorboard.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
|
||
|
|
buffer.
|
||
|
|
"""
|
||
|
|
if _summary_op_util.skip_summary():
|
||
|
|
return _constant_op.constant('')
|
||
|
|
with _summary_op_util.summary_scope(
|
||
|
|
name, family, values=[values],
|
||
|
|
default_name='HistogramSummary') as (tag, scope):
|
||
|
|
val = _gen_logging_ops.histogram_summary(
|
||
|
|
tag=tag, values=values, name=scope)
|
||
|
|
_summary_op_util.collect(val, collections, [_ops.GraphKeys.SUMMARIES])
|
||
|
|
return val
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('summary.audio')
|
||
|
|
def audio(name, tensor, sample_rate, max_outputs=3, collections=None,
|
||
|
|
family=None):
|
||
|
|
# pylint: disable=line-too-long
|
||
|
|
"""Outputs a `Summary` protocol buffer with audio.
|
||
|
|
|
||
|
|
The summary has up to `max_outputs` summary values containing audio. The
|
||
|
|
audio is built from `tensor` which must be 3-D with shape `[batch_size,
|
||
|
|
frames, channels]` or 2-D with shape `[batch_size, frames]`. The values are
|
||
|
|
assumed to be in the range of `[-1.0, 1.0]` with a sample rate of
|
||
|
|
`sample_rate`.
|
||
|
|
|
||
|
|
The `tag` in the outputted Summary.Value protobufs is generated based on the
|
||
|
|
name, with a suffix depending on the max_outputs setting:
|
||
|
|
|
||
|
|
* If `max_outputs` is 1, the summary value tag is '*name*/audio'.
|
||
|
|
* If `max_outputs` is greater than 1, the summary value tags are
|
||
|
|
generated sequentially as '*name*/audio/0', '*name*/audio/1', etc
|
||
|
|
|
||
|
|
Args:
|
||
|
|
name: A name for the generated node. Will also serve as a series name in
|
||
|
|
TensorBoard.
|
||
|
|
tensor: A 3-D `float32` `Tensor` of shape `[batch_size, frames, channels]`
|
||
|
|
or a 2-D `float32` `Tensor` of shape `[batch_size, frames]`.
|
||
|
|
sample_rate: A Scalar `float32` `Tensor` indicating the sample rate of the
|
||
|
|
signal in hertz.
|
||
|
|
max_outputs: Max number of batch elements to generate audio for.
|
||
|
|
collections: Optional list of ops.GraphKeys. The collections to add the
|
||
|
|
summary to. Defaults to [_ops.GraphKeys.SUMMARIES]
|
||
|
|
family: Optional; if provided, used as the prefix of the summary tag name,
|
||
|
|
which controls the tab name used for display on Tensorboard.
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
|
||
|
|
buffer.
|
||
|
|
"""
|
||
|
|
if _summary_op_util.skip_summary():
|
||
|
|
return _constant_op.constant('')
|
||
|
|
with _summary_op_util.summary_scope(
|
||
|
|
name, family=family, values=[tensor]) as (tag, scope):
|
||
|
|
sample_rate = _ops.convert_to_tensor(
|
||
|
|
sample_rate, dtype=_dtypes.float32, name='sample_rate')
|
||
|
|
val = _gen_logging_ops.audio_summary_v2(
|
||
|
|
tag=tag, tensor=tensor, max_outputs=max_outputs,
|
||
|
|
sample_rate=sample_rate, name=scope)
|
||
|
|
_summary_op_util.collect(val, collections, [_ops.GraphKeys.SUMMARIES])
|
||
|
|
return val
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('summary.merge')
|
||
|
|
def merge(inputs, collections=None, name=None):
|
||
|
|
# pylint: disable=line-too-long
|
||
|
|
"""Merges summaries.
|
||
|
|
|
||
|
|
This op creates a
|
||
|
|
[`Summary`](https://www.tensorflow.org/code/tensorflow/core/framework/summary.proto)
|
||
|
|
protocol buffer that contains the union of all the values in the input
|
||
|
|
summaries.
|
||
|
|
|
||
|
|
When the Op is run, it reports an `InvalidArgument` error if multiple values
|
||
|
|
in the summaries to merge use the same tag.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
inputs: A list of `string` `Tensor` objects containing serialized `Summary`
|
||
|
|
protocol buffers.
|
||
|
|
collections: Optional list of graph collections keys. The new summary op is
|
||
|
|
added to these collections. Defaults to `[]`.
|
||
|
|
name: A name for the operation (optional).
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
A scalar `Tensor` of type `string`. The serialized `Summary` protocol
|
||
|
|
buffer resulting from the merging.
|
||
|
|
|
||
|
|
Raises:
|
||
|
|
RuntimeError: If called with eager mode enabled.
|
||
|
|
|
||
|
|
@compatibility(eager)
|
||
|
|
Not compatible with eager execution. To write TensorBoard
|
||
|
|
summaries under eager execution, use `tf.contrib.summary` instead.
|
||
|
|
@end_compatbility
|
||
|
|
"""
|
||
|
|
# pylint: enable=line-too-long
|
||
|
|
if _context.executing_eagerly():
|
||
|
|
raise RuntimeError(
|
||
|
|
'Merging tf.summary.* ops is not compatible with eager execution. '
|
||
|
|
'Use tf.contrib.summary instead.')
|
||
|
|
if _summary_op_util.skip_summary():
|
||
|
|
return _constant_op.constant('')
|
||
|
|
name = _summary_op_util.clean_tag(name)
|
||
|
|
with _ops.name_scope(name, 'Merge', inputs):
|
||
|
|
val = _gen_logging_ops.merge_summary(inputs=inputs, name=name)
|
||
|
|
_summary_op_util.collect(val, collections, [])
|
||
|
|
return val
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('summary.merge_all')
|
||
|
|
def merge_all(key=_ops.GraphKeys.SUMMARIES, scope=None):
|
||
|
|
"""Merges all summaries collected in the default graph.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
key: `GraphKey` used to collect the summaries. Defaults to
|
||
|
|
`GraphKeys.SUMMARIES`.
|
||
|
|
scope: Optional scope used to filter the summary ops, using `re.match`
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
If no summaries were collected, returns None. Otherwise returns a scalar
|
||
|
|
`Tensor` of type `string` containing the serialized `Summary` protocol
|
||
|
|
buffer resulting from the merging.
|
||
|
|
|
||
|
|
Raises:
|
||
|
|
RuntimeError: If called with eager execution enabled.
|
||
|
|
|
||
|
|
@compatibility(eager)
|
||
|
|
Not compatible with eager execution. To write TensorBoard
|
||
|
|
summaries under eager execution, use `tf.contrib.summary` instead.
|
||
|
|
@end_compatbility
|
||
|
|
"""
|
||
|
|
if _context.executing_eagerly():
|
||
|
|
raise RuntimeError(
|
||
|
|
'Merging tf.summary.* ops is not compatible with eager execution. '
|
||
|
|
'Use tf.contrib.summary instead.')
|
||
|
|
summary_ops = _ops.get_collection(key, scope=scope)
|
||
|
|
if not summary_ops:
|
||
|
|
return None
|
||
|
|
else:
|
||
|
|
return merge(summary_ops)
|
||
|
|
|
||
|
|
|
||
|
|
@tf_export('summary.get_summary_description')
|
||
|
|
def get_summary_description(node_def):
|
||
|
|
"""Given a TensorSummary node_def, retrieve its SummaryDescription.
|
||
|
|
|
||
|
|
When a Summary op is instantiated, a SummaryDescription of associated
|
||
|
|
metadata is stored in its NodeDef. This method retrieves the description.
|
||
|
|
|
||
|
|
Args:
|
||
|
|
node_def: the node_def_pb2.NodeDef of a TensorSummary op
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
a summary_pb2.SummaryDescription
|
||
|
|
|
||
|
|
Raises:
|
||
|
|
ValueError: if the node is not a summary op.
|
||
|
|
|
||
|
|
@compatibility(eager)
|
||
|
|
Not compatible with eager execution. To write TensorBoard
|
||
|
|
summaries under eager execution, use `tf.contrib.summary` instead.
|
||
|
|
@end_compatbility
|
||
|
|
"""
|
||
|
|
|
||
|
|
if node_def.op != 'TensorSummary':
|
||
|
|
raise ValueError("Can't get_summary_description on %s" % node_def.op)
|
||
|
|
description_str = _compat.as_str_any(node_def.attr['description'].s)
|
||
|
|
summary_description = SummaryDescription()
|
||
|
|
_json_format.Parse(description_str, summary_description)
|
||
|
|
return summary_description
|