emrul

import numpy as np
from numpy.random import uniform


def update(S, k, v):
    "Update value position `k` in time O(log n)."
    d = S.shape[0]
    i = d//2 + k
    S[i] = v
    while i > 0:

emrul

from typing import Union
from tianshou.data import Batch
from tianshou.policy import RainbowPolicy
import numpy as np
import argparse
# See https://arxiv.org/abs/2006.01782 for paper - Temporally-Extended ε-Greedy Exploration
# See https://www.youtube.com/watch?v=Gi_B0IqscBE for video explaining where it's helpful
# See https://github.com/thu-ml/tianshou/blob/master/examples/atari/atari_rainbow.py for full example of how to setup args/net/collectors/etc.
def get_args():
    parser = argparse.ArgumentParser()

emrul

package com.lapanthere.bohemia

import kotlinx.coroutines.flow.Flow
import kotlinx.coroutines.flow.flow
import org.apache.kafka.clients.consumer.ConsumerRecord
import org.apache.kafka.clients.consumer.KafkaConsumer
import java.time.Duration


fun <K, V> KafkaConsumer<K, V>.asFlow(timeout: Duration = Duration.ofMillis(500)): Flow<ConsumerRecord<K, V>> =

emrul

package nl.avwie

interface Tag<T>

interface Tagged<T> {
    val tag: Tag<T>
}

class ComponentBag {
    private val components = mutableMapOf<Tag<*>, Any>()

emrul

const myOwnEscapeFn = (sql, sqlFragment, type) => {
    const actualType = type.domainBaseType || type;
    if (actualType.category === "N") {
        if (actualType.id === 20) {
            return sql.fragment `to_b64_extid(${sqlFragment})`;
        }
        if (["21" /* int2 */,
            "23" /* int4 */,
            "700" /* float4 */,
            "701" /* float8 */

emrul

using System;
using System.Collections.Generic;

/*
 * References:
 *    Initial idea: https://www.cse.wustl.edu/~jain/papers/ftp/psqr.pdf
 *    Based on implementation: https://github.com/skycmoon/P2
 *
 * Author:
 *    Emrul Islam <emrul@emrul.com>

emrul

import torch

from flair.data import Sentence, Dictionary
from flair.data_fetcher import NLPTaskDataFetcher, NLPTask
from flair.embeddings import TokenEmbeddings, WordEmbeddings, StackedEmbeddings, CharacterEmbeddings, \
    PooledFlairEmbeddings, FlairEmbeddings
from flair.visual.training_curves import Plotter
from flair.trainers import ModelTrainer
from flair.models import SequenceTagger
from flair.datasets import ColumnCorpus

emrul

# List unique values in a DataFrame column
# h/t @makmanalp for the updated syntax!
df['Column Name'].unique()

# Convert Series datatype to numeric (will error if column has non-numeric values)
# h/t @makmanalp
pd.to_numeric(df['Column Name'])

# Convert Series datatype to numeric, changing non-numeric values to NaN
# h/t @makmanalp for the updated syntax!

emrul

/*
 Assuming you have an enum type like this.
 You want to rename 'pending' to 'lodged'
 */
CREATE TYPE dispute_status AS ENUM('pending', 'resolved', 'open', 'cancelled');

BEGIN;

  ALTER TYPE dispute_status ADD VALUE 'lodged';
  UPDATE dispute SET status = 'lodged' WHERE status = 'pending';

emrul

data class User(@JsonProperty("userName") val name: String)

val userObj = User("John")

JsoniterKotlinSupport.enable()
JsoniterAnnotationSupport.enable()

val jsonUserString = JsonStream.serialize(userObj)
// jsonUserString will contain: {"userName":"John"}