lhr0909

<ss cols="4" name="holdem_ring" rows="4" xpad="1" ypad="0">
	<stat _rowcol="(1,1)" _stat_name="blank" click="" popup="default" tip=""/>
	<stat _rowcol="(1,2)" _stat_name="playershort" hudcolor="#7F9476" hudprefix="" hudsuffix="" popup="holdring_main" tip=""/>
	<stat _rowcol="(1,3)" _stat_name="n" hudcolor="#7F9476" hudprefix="(" hudsuffix=")" popup="pophands" tip=""/>
	<stat _rowcol="(1,4)" _stat_name="bbstack" click="" hudcolor="#7F9476" hudsuffix="bb"  stat_hicolor="#D86C1D" stat_hith="130" stat_locolor="#5ec265" stat_loth="40" popup="default" tip=""/>
	<stat _rowcol="(2,1)" _stat_name="vpip_0" hudcolor="#ECEBD0" hudprefix="vpi:" popup="poppreflop" stat_locolor="#D86C1D" stat_hith="40" stat_hicolor="#5ec265" stat_loth="25" tip=""/>
	<stat _rowcol="(2,2)" _stat_name="pfr_0" hudcolor="#ECEBD0" hudprefix="pfr:" popup="poppreflop" stat_locolor="#D86C1D" stat_hith="35" stat_hicolor="#5ec265" stat_loth="20" tip=""/>
	<stat _rowcol="(2,3)" _stat_name="agg_fact_0" hudcolor="#ECEBD0" hudprefix="agg:" popup="popagg" 

lhr0909

package hoolis.util;

import java.net.IDN;
import java.util.Arrays;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.xbill.DNS.ARecord;
import org.xbill.DNS.Lookup;
import org.xbill.DNS.MXRecord;

lhr0909

function flattenObject(obj, prefix) {
  var toReturn = {};

  for (var i in obj) {
    if (!obj.hasOwnProperty(i)) continue;

    if ((typeof obj[i]) == 'object') {
      var flatObject;
      if (prefix) {
        prefix = prefix + '[' + i + ']';

lhr0909

package io.divby0.utils;

import java.io.FilterInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.util.Iterator;
import java.util.LinkedList;
import java.util.Queue;

/**

lhr0909

function asyncIterableToObservable<T>(iterable: AsyncIterable<T>): Observable<T> {
  return new Observable<T>(
    (observer: Subscriber<T>) =>
      void (async () => {
        try {
          for await (const item of iterable) {
            if (observer.closed) {
              return;
            }
            observer.next(item);

lhr0909

import _ from 'lodash';

function flattenObject(obj: any): any {
  function _flattenPairs(obj: any, prefix: string): [string, any][] {
    // console.log(obj, prefix);
    if (!_.isObject(obj)) {
      return [prefix, obj];
    }

    return _.toPairs(obj).reduce((final: [string, any][], nPair: [string, any]) => {

lhr0909

Keybase proof

I hereby claim:

• I am lhr0909 on github.
• I am lhr0909 (https://keybase.io/lhr0909) on keybase.
• I have a public key ASBuOVwpHfFIg-c6qEl2uyn_ANt93FTFtv_XTVkSJ2bkeAo

To claim this, I am signing this object:

lhr0909

import torch
from torch import nn, Tensor

from .config import DIETClassifierConfig

class IntentClassifier(nn.Module):
    def __init__(self, config: DIETClassifierConfig):
        super().__init__()
        # Rasa's embedding layer is actually a "dense embedding layer" which is just a Keras dense layer
        # equivalent to a PyTorch Linear layer.

lhr0909

import torch
from torch import optim, nn, Tensor
import torch.nn.functional as F
import pytorch_lightning as pl

from .config import DIETClassifierConfig
from .models import IntentClassifier

class DIETClassifier(pl.LightningModule):
    def __init__(self, config: DIETClassifierConfig):

lhr0909

from conversational_sentence_encoder.vectorizers import SentenceEncoder
from jina import Executor, requests
from docarray import DocumentArray

class ConveRTFeaturizer(Executor):
    def __init__(self, multiple_contexts=False, **kwargs):
        super(ConveRTFeaturizer, self).__init__(**kwargs)
        self.sentence_encoder = SentenceEncoder(multiple_contexts=multiple_contexts)

    @requests