自主課題
#chainer
##train_mnist.py
MNIST(手書き数字)データを深層学習で0~9に分類
| package httputils | |
| import ( | |
| "fmt" | |
| "io" | |
| "net/http" | |
| "time" | |
| "github.com/go-chi/chi/middleware" | |
| ) |
| import numpy as np | |
| import tensorflow as tf | |
| import time | |
| class VAE_BP(object): | |
| def __init__(self, in_dim=784, hidden_units=[512, 256], latent_dim=50, lr=0.001): | |
| self.in_dim = in_dim | |
| self.hidden_units = hidden_units | |
| self.latent_dim = latent_dim | |
| self.lr = tf.constant(lr, dtype=tf.float32) |
自主課題
#chainer
##train_mnist.py
MNIST(手書き数字)データを深層学習で0~9に分類