deepdeepdot

Default

Powerlevel9k

deepdeepdot

$ python xor.py
Training:
  Epoch   0   MSE: 1.765
  Epoch 100   MSE: 0.015
  Epoch 200   MSE: 0.005
  * Target MSE reached *
Evaluating:
  1 XOR 0 = 1 ( 0.904)   Error: 0.096
  0 XOR 1 = 1 ( 0.908)   Error: 0.092
  1 XOR 1 = 0 (-0.008)   Error: 0.008

deepdeepdot

#include <time.h> //  Robert Nystrom
#include <stdio.h> // @munificentbob
#include <stdlib.h> //     for Ginny
#define  r return    //    2008-2019
#define  l(a, b, c, d) for (i y=a;y\
<b; y++) for (int x = c; x < d; x++)
typedef int i;const i H=40;const i W
=80;i m[40][80];i g(i x){r rand()%x;
}void cave(i s){i w=g(10)+5;i h=g(6)
+3;i t=g(W-w-2)+1;i u=g(H-h-2)+1;l(u

deepdeepdot

This configuration worked for me, hope it helps

It is based on: https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

and on: https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support

Hardware

deepdeepdot

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)