carlfm01

import spacy
from spacy import displacy
from spacy.lang.es.examples import sentences


f = open("result.txt", mode="w+", encoding="utf-8")
with open('data.txt', mode="r", encoding="utf-8") as file:
    data = file.read().replace('\n', '')
    nlp = spacy.load('es_core_news_sm', disable=['ner', 'textcat'])
    doc = nlp(data)

carlfm01

using DeepSpeechClient;
using DeepSpeechClient.Interfaces;
using DeepSpeechClient.Models;
using NAudio.Wave;
using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.IO;
using System.Linq;

carlfm01

import librosa
import librosa.filters
import numpy as np
import tensorflow as tf
from scipy import signal
from scipy.io import wavfile

def save_wavenet_wav(wav, path, sr, inv_preemphasize, k):
	# wav = inv_preemphasis(wav, k, inv_preemphasize)
	wav *= 32767 / max(0.01, np.max(np.abs(wav)))

carlfm01

for (size_t n = 0; n < totalFrameCnt / 160; n++) {
      get_frame_f32(pWavIn, frameIn, 160);
      float *input = (float *)malloc(480 * sizeof(float));
      float *output = (float *)malloc(160 * sizeof(float));

      //Upsample from 16KHz to 48KHz
      Resample_f32(frameIn, input, 16000, 48000, 160, 1);
  
      float prob = rnnoise_process(pRnnoise, frameOut, input);
      if (isOutput) {

carlfm01

     total_parameters = 0
     for variable in tf.trainable_variables():
         # shape is an array of tf.Dimension
         shape = variable.get_shape()
         print(shape)
         variable_parameters = 1
         for dim in shape:
             variable_parameters *= dim.value
         total_parameters += variable_parameters
     print(f'TOTAL: {total_parameters}')

carlfm01

#!/bin/bash
## This gist contains instructions about cuda v10.1 and cudnn 7.6 installation in Ubuntu 18.04 for Tensorflow 2.1.0

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

carlfm01

#!/bin/bash

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

### to verify your gpu is cuda enable check

carlfm01

var message = new MimeMessage();
    message.From.Add(new MailboxAddress("Your Name", "your-email@yourdomain.com"));
    message.To.Add(new MailboxAddress("", recipientEmail));
    message.Subject = subject;

    message.Body = new TextPart("html")
    {
        Text = body
    };

carlfm01

import os
import time
from typing import Optional, Tuple

import torch
from PIL import Image

import onnxruntime as onnxrt
import requests
from transformers import AutoConfig, AutoModelForVision2Seq, TrOCRProcessor, VisionEncoderDecoderModel