DN6

# Setup
# ----------------------
# Install torch from nightly
# `pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu126`

# Install diffusers
# `pip install diffusers`

import torch
from diffusers import FluxPipeline, FluxTransformer2DModel, GGUFQuantizationConfig

DN6

"""Examples logging Tune runs to comet.ml"""
import comet_ml
import argparse
import numpy as np

from ray import tune
from ray.tune.integration.comet import CometLoggerCallback


def train_function(config, checkpoint_dir=None):

DN6

import sparknlp
from sparknlp.base import *
from sparknlp.annotator import *
from sparknlp.logging.comet import CometLogger

spark = sparknlp.start()

OUTPUT_LOG_PATH = "./run"
logger = CometLogger()

DN6

import comet_ml

import os
import torch
from torch import nn, optim
from torch.utils.data import DataLoader

from catalyst import dl
from catalyst.data import ToTensor
from catalyst.contrib.datasets import MNIST

DN6

import comet_ml
import os
import json
from flask import Flask, request

app = Flask(__name__)


COMET_API_KEY = os.getenv("COMET_API_KEY")
COMET_WORKSPACE = os.getenv("COMET_WORKSPACE")

DN6

from comet_ml import Optimizer

from functools import partial
import numpy as np
import os
import sys

import torch
import torch.nn as nn
import torch.nn.functional as F

DN6

from comet_ml import Experiment

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.callbacks import Callback

import numpy as np
import pandas as pd

from sklearn.model_selection import train_test_split

DN6

dataset	meta data	contents	with audio
200DrumMachines		7371 one-shots	yes
ACM_MIRUM	tempo	1410 excerpts (60s)	yes
AcousticBrainz-Genre	15-31 genres	audio features for about 1000000 songs	no
ADC2004	predominant pitch	20 excerpts	yes
Acoustic Event Dataset	28 event classes	5223 audio snippets	yes
Amg1608	valence &