Feature: multiple Y-axis scales on a single chart

For bug reports, please include the following:

• TensorBoard version (from pip package, also printed out when running tensorboard)
  1.12.0
• TensorFlow version if different from TensorBoard
• OS Platform and version (e.g., Linux Ubuntu 16.04)
  Windows 10 Professional Desktop
• Python version (e.g. 2.7, 3.5)
  Python 3.5.0

Here are the two examples:
1 perfectly worked as the scales was same:

import tensorflow as tf
from numpy import random

writer_1 = tf.summary.FileWriter("./logs/plot_1")
writer_2 = tf.summary.FileWriter("./logs/plot_2")

log_var = tf.Variable(0.0)
tf.summary.scalar("loss", log_var)

write_op = tf.summary.merge_all()

session = tf.InteractiveSession()
session.run(tf.global_variables_initializer())

for i in range(100):
    # for writer 1
    summary = session.run(write_op, {log_var: random.rand()})
    writer_1.add_summary(summary, i)
    writer_1.flush()

    # for writer 2
    summary = session.run(write_op, {log_var: random.rand()})
    writer_2.add_summary(summary, i)
    writer_2.flush()
    print(i)

Got this figure which was understandable :

But take a look at the second case where the values do not fit in the same range. In that case I need to have two different axes on same chart, so that I get a good and understandable image. Check the code:

import tensorflow as tf
from numpy import random

writer_1 = tf.summary.FileWriter("./logs/plot_1")
writer_2 = tf.summary.FileWriter("./logs/plot_2")

log_var = tf.Variable(0.0)
tf.summary.scalar("loss", log_var)

write_op = tf.summary.merge_all()

session = tf.InteractiveSession()
session.run(tf.global_variables_initializer())

for i in range(100):
    # for writer 1
    summary = session.run(write_op, {log_var: i*10})
    writer_1.add_summary(summary, i)
    writer_1.flush()

    # for writer 2
    summary = session.run(write_op, {log_var: random.rand()})
    writer_2.add_summary(summary, i)
    writer_2.flush()
    print(i)

See the image obtained:

Please help me with this query.
I have tried many things and even have placed this question on Stackoverflow but there is no response.

Reproduce the two examples in TensorBoard using the linked screenshots and compare charts with similar and widely different value ranges. Start by locating the chart implementation and its existing scale behavior; done means a single chart can display multiple scalar series with separate, understandable Y-axis scales.