/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Dec 26 07:46:00 2019 Implemented using TensorFlow 1.0 and TFLearn 0.3.2 K. He, X. Zhang, S. Ren, J. Sun, Deep Residual Learning for Image Recognit
train_dataset.output_shapes) images, labels = feed_iterator.get_next()# 创建不同的iteratortrain_iterator =train_dataset.make_one_shot_iterator() val_iterator = val_dataset.make_initializable_iterator()# 创建模型logits = model(images, [500, 500]) loss = tf.nn.sparse_softmax_cross_entropy_w...
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True) 当one-hot变为为TRUE,则只要对应的位置的值为1,其余都是0。 这里,我直接下载了数据集,并放在了我的代码里面。测试如下: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 # _*_coding:utf-8_*_ ...
one-shot 的标准数据集——Omniglot 使用python 获取 CASIA 脱机和在线手写汉字库 python 获取 CASIA 脱机和在线手写汉字库 (二) MPF(Bunch) 转换为 HDF5 COCO 使用说明 LeCun, Y., Cortes, C., & Burges, C. http://yann.lecun.com/exdb/mnist/ ↩︎ Xiao, H., Rasul, K., & Vollgraf, R...
/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Dec 26 07:46:00 2019 Implemented using TensorFlow 1.0 and TFLearn 0.3.2 K. He, X. Zhang, S. Ren, J. Sun, Deep Residual Learning for Image Recognition, CVPR, 2016....
{ name: "fc1" type: "InnerProduct" # learning rate and decay multipliers for the weights param { lr_mult: 1 decay_mult: 1 } # learning rate and decay multipliers for the biases param { lr_mult: 2 decay_mult: 0 } inner_product_param { num_output: 300 weight_filler { type: "...
TensorFlow同样将密集的复杂运算搬到Python外面执行,不过做的更彻底。 首先载入TensorFlow库,并创建一个新的 InteractiveSession ,使用这个命令会将这个session 注册为默认的session,之后的运算也默认跑在这个session里,不同session之间的数据和运算应该都是相互独立的。接下来创建一个 placeholder,即输入数据的地方。
parameters": {"dropout1": {"type": "const", "val": 0.25}, "dropout2": {"type": "const", "val": 0.5}, "learning_rate": {"type": "const", "val": 1}, "n_filters1": {"type": "const", "val": 32}, "n_filters2": {"type": "const", "val": 64}}, "labels": [...
1. 打开examples\mnist目录下的lenet_solver.prototxt文件,可以看到solver_mode: GPU这一选项,可以设置为GPU或者CPU net和snapshot_prefix 设置为绝对路径 2. 打开examples\mnist目录下的lenet_train_test.protot... caffe的mnist小练习 这是一个手写数字分类的小练习,训练集是一些带标签的手写数字,测试集是一些手...
Image generation has become an increasingly popular machine learning task. There are various techniques and applications designed to generate images from scratch, one of which are diffusion models. These models are deep neu- ral networks trained on large datasets which can hinder their deployment on ...