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logger.py
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logger.py
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import numpy as np
import tensorflow as tf
class Logger(object):
"""Logs values to be visualized in the tensorboard.
Note:
Code referenced from https://gist.github.com/gyglim/1f8dfb1b5c82627ae3efcfbbadb9f514
"""
def __init__(self, log_dir):
self.writer = tf.summary.FileWriter(log_dir)
def scalar_summary(self, tag, value, step):
"""Adds scalar summary to the tensorboard"""
summary = tf.Summary(value=[tf.Summary.Value(tag=tag, simple_value=value)])
self.writer.add_summary(summary, step)
def histo_summary(self, tag, values, step, bins=1000):
"""Adds histogram to the tensorboard"""
counts, bin_edges = np.histogram(values, bins=bins)
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))
bin_edges = bin_edges[1:]
for edge in bin_edges:
hist.bucket_limit.append(edge)
for c in counts:
hist.bucket.append(c)
summary = tf.Summary(value=[tf.Summary.Value(tag=tag, histo=hist)])
self.writer.add_summary(summary, step)
self.writer.flush()