<jupyter_start><jupyter_text>June 10 - VAE Analysis<jupyter_code># Python library and module imports
import os
import sys
import numpy as np
import matplotlib.pyplot as plt
import math
import h5py
import torch
from matplotlib.colors import LogNorm
import pandas as pd
import random

# Add the path to the parent directory to augment search for module
par_dir = os.path.abspath(os.path.join(os.getcwd(), os.pardir))
if par_dir not in sys.path:
    sys.path.append(par_dir)
    
# Import the custom plotting module
from plot_utils import plot_utils
# Setup the paths to the log files

vae2net_log = "20190609_184706"

# Training log files for the models
log_dir =  "/home/akajal/WatChMaL/WatChMaL-VAE/USER/save_path_vae/data_description/"
vae2net_train_log = log_dir + vae2net_log + "/val_test.csv"
plot_utils.plot_training_loss([vae2net_train_log],
                              ["VAE2Net"],
                              {"VAE2Net":"red"},
                              downsample_interval=1000, show_plot=True)<jupyter_output>62.933643999999994
0
8.478214
4.4e-05
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