ggaammdev

from abc import ABC, abstractmethod
import dask.dataframe as dd
import dask.array as da
from dask.distributed import Client, LocalCluster
import pandas as pd
import numpy as np
import logging
import time

# ==========================================

ggaammdev

from abc import ABC, abstractmethod
from pyspark.sql import SparkSession
import pyspark.sql.functions as F
import logging
import time

class SparkJobBase(ABC):
    def __init__(self, job_name):
        self.job_name = job_name
        logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

ggaammdev

#include <iostream>
#include <memory>
#include <vector>
#include <string>

// ==========================================
// CONFIGURATION
// ==========================================
// Increase this number until your program crashes on the "Unsafe" tests.
// On many systems, 50,000 to 100,000 is enough to overflow the default stack.

ggaammdev

import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.init as init
import math

# ==========================================
# 1. The Scheduler Class
# ==========================================
class SaliencePulseScheduler:

ggaammdev

import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.init as init
import math

# ==========================================
# 1. Setup: Model, Optimizer, Data, Metrics
# ==========================================
# A simple model for demonstration