Skip to content

Instantly share code, notes, and snippets.

View kunci115's full-sized avatar
🏠
Building The World

Rino Alfian kunci115

🏠
Building The World
  • Somewhere i belong
View GitHub Profile
https://www.instagram.com/reel/CxBfDy5yK4O/?igshid=NzZhOTFlYzFmZQ==
import random
def hello_logic(prompt_text="hello"):
"""
:param prompt_text: hello, hello_repeat, hello_null
:return: nn.say prompt_text
"""
mem = {"hello": "<Name>, good afternoon! You are concerned about Company X, "
"we are conducting a survey of satisfaction with our services. "
# Created by https://www.toptal.com/developers/gitignore/api/osx,java,eclipse,intellij,maven
# Edit at https://www.toptal.com/developers/gitignore?templates=osx,java,eclipse,intellij,maven
### Eclipse ###
.metadata
bin/
tmp/
*.tmp
*.bak
@kunci115
kunci115 / soundtextconvert.py
Created September 26, 2019 06:13
to convert text to sound text format
import json
dict1 = {
"utter_agent.acquaintance": {
"en": {
"content": {
"type": "sound_text",
"elements": [
"I'm a virtual agent",
"Think of me as a virtual agent.",
"Well, I'm not a person, I'm a virtual agent.",
version: '3'
services:
mongo:
image: mongo:4.0.3
environment:
- MONGO_DATA_DIR=/data/db
- MONGO_LOG_DIR=/dev/null
volumes:
- ./data/db:/data/db
ports:
##
# You should look at the following URL's in order to grasp a solid understanding
# of Nginx configuration files in order to fully unleash the power of Nginx.
# https://www.nginx.com/resources/wiki/start/
# https://www.nginx.com/resources/wiki/start/topics/tutorials/config_pitfalls/
# https://wiki.debian.org/Nginx/DirectoryStructure
#
# In most cases, administrators will remove this file from sites-enabled/ and
# leave it as reference inside of sites-available where it will continue to be
# updated by the nginx packaging team.
vocab_size = ...
src_txt_length = ...
sum_txt_length = ...
# encoder input model
inputs = Input(shape=(src_txt_length,))
encoder1 = Embedding(vocab_size, 128)(inputs)
encoder2 = LSTM(128)(encoder1)
encoder3 = RepeatVector(sum_txt_length)(encoder2)
# decoder output model
decoder1 = LSTM(128, return_sequences=True)(encoder3)