Skip to content

Instantly share code, notes, and snippets.

Embed
What would you like to do?
Logging to tensorboard without tensorflow operations. Uses manually generated summaries instead of summary ops
"""Simple example on how to log scalars and images to tensorboard without tensor ops.
License: BSD License 2.0
"""
__author__ = "Michael Gygli"
import tensorflow as tf
from StringIO import StringIO
import matplotlib.pyplot as plt
import numpy as np
class Logger(object):
"""Logging in tensorboard without tensorflow ops."""
def __init__(self, log_dir):
"""Creates a summary writer logging to log_dir."""
self.writer = tf.summary.FileWriter(log_dir)
def log_scalar(self, tag, value, step):
"""Log a scalar variable.
Parameter
----------
tag : basestring
Name of the scalar
value
step : int
training iteration
"""
summary = tf.Summary(value=[tf.Summary.Value(tag=tag,
simple_value=value)])
self.writer.add_summary(summary, step)
def log_images(self, tag, images, step):
"""Logs a list of images."""
im_summaries = []
for nr, img in enumerate(images):
# Write the image to a string
s = StringIO()
plt.imsave(s, img, format='png')
# Create an Image object
img_sum = tf.Summary.Image(encoded_image_string=s.getvalue(),
height=img.shape[0],
width=img.shape[1])
# Create a Summary value
im_summaries.append(tf.Summary.Value(tag='%s/%d' % (tag, nr),
image=img_sum))
# Create and write Summary
summary = tf.Summary(value=im_summaries)
self.writer.add_summary(summary, step)
def log_histogram(self, tag, values, step, bins=1000):
"""Logs the histogram of a list/vector of values."""
# Convert to a numpy array
values = np.array(values)
# Create histogram using numpy
counts, bin_edges = np.histogram(values, bins=bins)
# Fill fields of histogram proto
hist = tf.HistogramProto()
hist.min = float(np.min(values))
hist.max = float(np.max(values))
hist.num = int(np.prod(values.shape))
hist.sum = float(np.sum(values))
hist.sum_squares = float(np.sum(values**2))
# Requires equal number as bins, where the first goes from -DBL_MAX to bin_edges[1]
# See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/summary.proto#L30
# Thus, we drop the start of the first bin
bin_edges = bin_edges[1:]
# Add bin edges and counts
for edge in bin_edges:
hist.bucket_limit.append(edge)
for c in counts:
hist.bucket.append(c)
# Create and write Summary
summary = tf.Summary(value=[tf.Summary.Value(tag=tag, histo=hist)])
self.writer.add_summary(summary, step)
self.writer.flush()
@Zlo7
Copy link

Zlo7 commented Oct 11, 2020

Very minor tweaks for xrz000's text summary for TF2 Compatibility:

class Logger(object):
"""Logging in tensorboard without tensorflow ops."""

def __init__(self, log_dir):
    """Creates a summary writer logging to log_dir."""
    self.writer = tf.compat.v1.summary.FileWriter(log_dir)

def log_text(self, tag, value, step):
    """Log string or 2D string tables. """
    summary_metadata = metadata.create_summary_metadata(
        display_name="text",
        description="Text Summary")
    summary_metadata = tf.compat.v1.SummaryMetadata.FromString(
        summary_metadata.SerializeToString())
    tensor = tf.make_tensor_proto(value, dtype=tf.string)
    summary = tf.compat.v1.Summary(value=[tf.compat.v1.Summary.Value(
                tag=tag,
                metadata=summary_metadata,
                tensor=tensor
            )])
    self.writer.add_summary(summary, step)
    self.writer.flush()

Example Usage:

with tf.compat.v1.Graph().as_default():
    logger.log_text(tag="string", value="test", step=0)
    logger.log_text(tag="table", value=[["r0c0", "r0c1"], ["r1c0", "r1c1"]], step=0)

@hanchengyu3
Copy link

hanchengyu3 commented Oct 14, 2021

在张力流 2.0 上运行时,我遇到一些不兼容的错误。有什么计划来更新这个 - 非常有用的代码?

Hello, has your problem been solved? Which version should be configured to be compatible

@Kisameee
Copy link

Kisameee commented Oct 14, 2021

tested it and every things worked great with tf 2.4

@hanchengyu3
Copy link

hanchengyu3 commented Oct 14, 2021

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment