摘要：# 1. 自定义模型并训练。 import numpy as np import tensorflow as tf from tensorflow.examples.tutorials.mnist import input_data tf.logging.set_verbosity(tf.logging.INFO) def lenet(x, is_training): x = tf.reshape 阅读全文

摘要：# 1. 模型定义。 import numpy as np import tensorflow as tf from tensorflow.examples.tutorials.mnist import input_data tf.logging.set_verbosity(tf.logging.INFO) mnist = input_data.read_data_sets("F:\\Tensor 阅读全文

摘要：# 1. 模型定义。 import tensorflow as tf from tensorflow.examples.tutorials.mnist import input_data mnist_data = input_data.read_data_sets('F:\\TensorFlowGoogle\\201806-github\\datasets\\MNIST_data', one_... 阅读全文

摘要：# 1. 数据预处理。 import keras from keras.models import Model from keras.datasets import mnist from keras.layers import Input, Dense from tflearn.layers.core import fully_connected num_classes = 10 img_ro... 阅读全文

摘要：# 1. 数据预处理。 import keras from keras.models import Model from keras.datasets import mnist from keras.layers import Input, Dense from tflearn.layers.core import fully_connected num_classes = 10 img_ro... 阅读全文

摘要：# 1. 数据预处理。 from keras.layers import LSTM from keras.datasets import imdb from keras.models import Sequential from keras.preprocessing import sequence from keras.layers import Dense, Embedding max_fea 阅读全文

摘要：# 1. 数据预处理 import keras from keras import backend as K from keras.datasets import mnist from keras.models import Sequential from keras.layers import Dense, Flatten, Conv2D, MaxPooling2D num_classes = 阅读全文

摘要：将原来版本的keras卸载了，再安装2.1.5版本的keras就可以了。 阅读全文

摘要：找到对应的keras配置文件keras.json 将里面的内容修改为以下就可以了 阅读全文

摘要：# 1. 通过TFLearn的API定义卷机神经网络。 import tflearn import tflearn.datasets.mnist as mnist from tflearn.layers.conv import conv_2d, max_pool_2d from tflearn.layers.estimator import regression from tflearn.laye 阅读全文

摘要：# 1. 通过TensorFlow-Slim定义卷机神经网络 import numpy as np import tensorflow as tf import tensorflow.contrib.slim as slim from tensorflow.examples.tutorials.mnist import input_data # 通过TensorFlow-Slim来定义LeN... 阅读全文