python = 3.6 pytorch = 0.4.1 torchvision = 0.2.1 matplotlib = 2.2.2 numpy = 1.14.3 scipy = 1.1.0 Network parameters batch_size = 256 max epochs = 100 learning rate = 0.1 (0.01 at epoch 50 and 0.001 at epoch 65) SGD with momentum = 0.9 ...
Code Issues Pull requests Pytorch implementation of stochastically quantized variational autoencoder (SQ-VAE) machine-learning pytorch generative-model vae bayesian variational-autoencoder vector-quantization gumbel-softmax vq-vae deep-generative-model Updated Jul 20, 2022 Python ...
softmax的PyTorch实现 # 加载各种包或者模块 import torch from torch import nn from torch.nn import init import numpy as np import sys sys.path.append("/home/kesci/input") import d2lzh as d2l print(torch.__version__) 1.4.0 初始化参数和获取数据 batch_size = 256 train_iter, test_iter ...
However, the examples at the bottom of the docstring still apply a softmax before calling the function, which effectively leads to two softmax being applied in a row, thus yielding terrible results. I suggest we update the last example to prevent anyone from thinking that they have to apply ...