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PyTorch中的train()、eval()和no_grad()的使用_python_脚本之家
def forward(self, x): x = torch.relu(self.fc1(x)) x = self.fc2(x) return x model = MyModel() optimizer = optim.SGD(model.parameters(), lr=0.1) criterion = nn.CrossEntropyLoss() # 训练模型 model.train() for epoch in range(num_epochs): optimizer.zero_grad() outputs = model(...
www.jb51.net/article/280262.htm 2023-4-7
python如何利用joblib保存训练模型_python_脚本之家
model.fit(X_train, y_train) # save the updated model with open('my_updated_model.pkl', 'wb') as f: pickle.dump(model, f) 方法二:使用joblib——大型模型 joblib是一个用于将Python对象序列化为磁盘文件的库,专门用于 大型数组。它可以高效地处理大型数据集和模型。对于大型机器学习模型,使用joblib...
www.jb51.net/python/288250x...htm 2024-6-1
完美解决TensorFlow和Keras大数据量内存溢出的问题_python_脚本之家
X_train=tf.cast(X_train, tf.string) y_train=tf.cast(y_train, tf.int32) # make an input queue input_queue=tf.train.slice_input_producer([X_train, y_train]) y_train=input_queue[1] X_train_contents=tf.read_file(input_queue[0]) ...
www.jb51.net/article/1900...htm 2024-6-1
python函数中将变量名转换成字符串实例_python_脚本之家
defsmall_feature_model(model,X_train=X_train,y_train=y_train,X_test=X_test, y_test=y_test): pca=PCA(n_components=150,random_state=0,whiten=True) pipeline=Pipeline([('scale',StandardScaler()),('pca',pca)]) processing=pipeline.fit(X_train) ...
www.jb51.net/article/1862...htm 2024-5-31
Python机器学习之底层实现KNN_python_脚本之家
x_test = x[test_indexs] y_test = y[test_indexs] # 将切分好的数据集返回出去 # print(y_train) return x_train, x_test, y_train, y_test 四、计算距离 此处用到欧氏距离,pow()函数用来计算幂次方。length指属性值数量,在计算最近邻时用到。 1 2 3 4 5 def CountDistance(train,test,length...
www.jb51.net/article/2153...htm 2024-6-2