小编Joh*_*her的帖子

我试图将映射变量传递到 template_file 中，但抛出此错误：

vars (varsname): '' 预期类型 'string'，得到不可转换类型 'map[string]interface {}'

    data "template_file" "app" {

        template = "${file("./app_template.tpl")}"

        vars {
                container = "${var.container-configuration}"
        }
    }

变量.tf

    variable "container-configuration" {
        description = "Configuration for container"
        type        = "map"
        default     = {
                    image          = "blahblah.dkr.ecr.us-east-2.amazonaws.com/connect"
                    container-port = "3000"
                    host-port      = "3000"
                    cpu            = "1024"
                    memory         = "2048"
                    log-group      = "test"
                    log-region     = "us-east-2a"
                  }
    }

有没有办法将地图传递到模板文件中进行插值？我在文档中没有找到任何明确的内容。

如何在训练后保存模型重量？

Keras提供:

model.save( 'weights.h5')`

模型对象由build_fn属性函数初始化,如何进行保存？

def model():
    model = Sequential()
    model.add(Dense(10, activation='relu', input_dim=5))
    model.add(Dense(5, activation='relu'))
    model.add(Dense(1, kernel_initializer='normal'))
    model.compile(loss='mean_squared_error', optimizer='adam')
    return model


if __name__ == '__main__':
`

    X, Y = process_data()

    print('Dataset Samples: {}'.format(len(Y)))

    model = KerasRegressor(build_fn=model,
            epochs=10,
            batch_size=10,
            verbose=1)


    kfold = KFold(n_splits=2, random_state=seed)

    results = cross_val_score(model, X, Y, cv=kfold)

    print('Results: {0}.2f ({1}.2f MSE'.format(results.mean(), results.std()))