Logging to tensorboard without tensorflow operations. Uses manually generated su...

Thanks or the code it works great, found a small bug though...
If values is a list in log_histogram then because list has no attribute shape the program crashes you should write values=np.array(values) in the beginning of the function to avoid these issue.

Thank you for such a helpful tool ! I've been confused about how to write what I want into tensorboard

Thanks!

            s = StringIO()
            plt.imsave(s, img, format='png')

doesn't work because pyplot.imsave() expects a file path

Author

doesn't work because pyplot.imsave() expects a file path

That's not true, at least for more recent versions, where it can be a "file-like" object, see:
https://matplotlib.org/api/_as_gen/matplotlib.pyplot.imsave.html

@adizhol: Maybe your version is outdated?

Thanks!

It works, thx!

Great code, thanks

excellent work, and I have to use BytesIO instead of StringIO for python 3.5.5, matplotlib 2.2.2

Cool! Thanks

@gyglim Maybe it is worth to add flush method? I think for newcomers to tensorboard it would be a good hint that they should consider flushing.

Thanks a lot, perfect!

Thanks a lot Michael, this helped me today :).
BTW: I had to use a Bytes-like object (BytesIO) instead of a StringIO for it to work (TF 1.13, Matplotlib 3.0.3).

Cheers !

Are you sure this works for multiple scalars? Is flush needed? I see points showing up in tboard but they do not seem to update often enough?

Also anyone know what to put in a step to get the scalars to look similar to the keras callback scalars?

text summary can be a new feature

Anyone knows how to construct text summary?

What does 'License: Copyleft' mean?
Can you provide more detailed license information, such as GPL, LGPL or MPL?

Thanks!!

Author

Added BSD License 2.0

@gyglim Thanks!! :)

To add text summary

from tensorboard.plugins.text import metadata

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_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.SummaryMetadata.FromString(
	                summary_metadata.SerializeToString())
	        tensor = tf.make_tensor_proto(value, dtype=tf.string)
	        summary = tf.Summary(value=[tf.Summary.Value(
	            tag=tag,
	            metadata=summary_metadata,
	            tensor=tensor
	            )])
	        self.writer.add_summary(summary, step)
	        self.writer.flush()

Example usage:

logger = Logger('/tmp/test')
logger.log_text(tag="string", value="test", step=0)
logger.log_text(tag="table", value=[["r0c0", "r0c1"], ["r1c0", "r1c1"]], step=0)

Tensorboard:

I get some incompatibility errors when running on tensorflow 2.0. Any plans to update this -very useful- code?

Wonderful solution:) Why flush is only in log_histogram?

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)

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

tested it and every things worked great with tf 2.4

tested it and every things worked great with tf 2.4

In tf 2.3, it fails with AttributeError: module 'tensorboard.summary._tf.summary' has no attribute 'FileWriter'

Anyone can tell me how can I use summary add_graph to show modal structure.