mirror of
https://github.com/yunjey/pytorch-tutorial.git
synced 2025-07-06 01:15:59 +08:00
71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
# Code referenced from https://gist.github.com/gyglim/1f8dfb1b5c82627ae3efcfbbadb9f514
|
|
import tensorflow as tf
|
|
import numpy as np
|
|
import scipy.misc
|
|
try:
|
|
from StringIO import StringIO # Python 2.7
|
|
except ImportError:
|
|
from io import BytesIO # Python 3.x
|
|
|
|
|
|
class Logger(object):
|
|
|
|
def __init__(self, log_dir):
|
|
"""Create a summary writer logging to log_dir."""
|
|
self.writer = tf.summary.FileWriter(log_dir)
|
|
|
|
def scalar_summary(self, tag, value, step):
|
|
"""Log a scalar variable."""
|
|
summary = tf.Summary(value=[tf.Summary.Value(tag=tag, simple_value=value)])
|
|
self.writer.add_summary(summary, step)
|
|
|
|
def image_summary(self, tag, images, step):
|
|
"""Log a list of images."""
|
|
|
|
img_summaries = []
|
|
for i, img in enumerate(images):
|
|
# Write the image to a string
|
|
try:
|
|
s = StringIO()
|
|
except:
|
|
s = BytesIO()
|
|
scipy.misc.toimage(img).save(s, 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
|
|
img_summaries.append(tf.Summary.Value(tag='%s/%d' % (tag, i), image=img_sum))
|
|
|
|
# Create and write Summary
|
|
summary = tf.Summary(value=img_summaries)
|
|
self.writer.add_summary(summary, step)
|
|
|
|
def histo_summary(self, tag, values, step, bins=1000):
|
|
"""Log a histogram of the tensor of values."""
|
|
|
|
# Create a histogram using numpy
|
|
counts, bin_edges = np.histogram(values, bins=bins)
|
|
|
|
# Fill the fields of the 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))
|
|
|
|
# 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() |