shivammehta25

from typing import Any, Dict, List, Optional, Tuple

import hydra
import lightning as L
import rootutils
from lightning import Callback, LightningDataModule, LightningModule, Trainer
from lightning.pytorch.loggers import Logger
from omegaconf import DictConfig

from matcha import utils

shivammehta25

import json
import sys

sys.path.append('src/model')
sys.path.insert(0, './hifigan')
import logging
import os
from pathlib import Path
from uuid import uuid4

shivammehta25

{"part_1": {"A": [1.3289685530035618, 1.1651508061381441, 0.7631653476434284, 0.7102941367492636, 0.7141679022121673, 0.9238686165977774, 2.3763289731759945, 1.1728786644866258, 1.5456303986453817, 1.8307110056560796, 0.913641029695185, 0.3207673213283985, 0.6982080749901575, 0.5670384444667927, 0.7984430401385789, 1.056119262388202, 0.717912595855595, 0.5407891112112009, 1.2139131032609538, 1.1906981592748638, 0.7620391245275789, 1.2215988439841174, 1.217804178741637, 1.103111401233095, 0.9365024928859879, 0.553753928583847, 1.526739841606898, 1.4365889644652245, 0.5164525170951063, 0.4446933188187261, 1.700690373005282, 0.9638603458167805, 0.3561246811785101, 1.0794693257439627, 0.7851324510567355, 0.9814201784580446, 0.6218411329885448, 0.5055394878957932, 0.8390436164413066, 0.9053144463446685, 1.2545495866181842, 1.0273653388297026, 0.5370219778704626, 1.3592395313686898, 0.5619163183773729, 1.106004444823451, 0.34593604357115293, 0.6020707771557747, 0.6725565913440426, 0.633786011459005, 1.1367306336009

shivammehta25

from scipy.stats import multivariate_normal
import numpy as np
import matplotlib.pyplot as plt
from collections import namedtuple
import random
import numpy as np
from sklearn.datasets import make_blobs
from matplotlib.colors import ListedColormap
from math import ceil, floor
from matplotlib import cm, gridspec