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Commit f8e7b87b authored by Anjith GEORGE's avatar Anjith GEORGE
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logger

parent 01a78753
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# 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()
\ No newline at end of file
......@@ -7,8 +7,7 @@ import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
from bob.learn.pytorch.utils import comp_bce_loss_weights
from bob.learn.pytorch.trainers import Logger
from .logger import Logger
import bob.core
logger = bob.core.log.setup("bob.learn.pytorch")
......
......@@ -2,7 +2,6 @@ from .CNNTrainer import CNNTrainer
from .MCCNNTrainer import MCCNNTrainer
from .DCGANTrainer import DCGANTrainer
from .ConditionalGANTrainer import ConditionalGANTrainer
from .Logger import Logger
# gets sphinx autodoc done right - don't remove it
__all__ = [_ for _ in dir() if not _.startswith('_')]
......
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