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Python layers.Affine方法代码示例

本文整理汇总了Python中neon.layers.Affine方法的典型用法代码示例。如果您正苦于以下问题:Python layers.Affine方法的具体用法?Python layers.Affine怎么用?Python layers.Affine使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在neon.layers的用法示例。


在下文中一共展示了layers.Affine方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: main

# 需要导入模块: from neon import layers [as 别名]
# 或者: from neon.layers import Affine [as 别名]
def main():
    parser = get_parser()
    args = parser.parse_args()
    print('Args:', args)

    loggingLevel = logging.DEBUG if args.verbose else logging.INFO
    logging.basicConfig(level=loggingLevel, format='')

    ext = extension_from_parameters(args)

    loader = p1b3.DataLoader(feature_subsample=args.feature_subsample,
                             scaling=args.scaling,
                             drug_features=args.drug_features,
                             scramble=args.scramble,
                             min_logconc=args.min_logconc,
                             max_logconc=args.max_logconc,
                             subsample=args.subsample,
                             category_cutoffs=args.category_cutoffs)

    # initializer = Gaussian(loc=0.0, scale=0.01)
    initializer = GlorotUniform()
    activation = get_function(args.activation)()

    layers = []
    reshape = None

    if args.convolution and args.convolution[0]:
        reshape = (1, loader.input_dim, 1)
        layer_list = list(range(0, len(args.convolution), 3))
        for l, i in enumerate(layer_list):
            nb_filter = args.convolution[i]
            filter_len = args.convolution[i+1]
            stride = args.convolution[i+2]
            # print(nb_filter, filter_len, stride)
            # fshape: (height, width, num_filters).
            layers.append(Conv((1, filter_len, nb_filter), strides={'str_h':1, 'str_w':stride}, init=initializer, activation=activation))
            if args.pool:
                layers.append(Pooling((1, args.pool)))

    for layer in args.dense:
        if layer:
            layers.append(Affine(nout=layer, init=initializer, activation=activation))
        if args.drop:
            layers.append(Dropout(keep=(1-args.drop)))
    layers.append(Affine(nout=1, init=initializer, activation=neon.transforms.Identity()))

    model = Model(layers=layers)

    train_iter = ConcatDataIter(loader, ndata=args.train_samples, lshape=reshape, datatype=args.datatype)
    val_iter = ConcatDataIter(loader, partition='val', ndata=args.val_samples, lshape=reshape, datatype=args.datatype)

    cost = GeneralizedCost(get_function(args.loss)())
    optimizer = get_function(args.optimizer)()
    callbacks = Callbacks(model, eval_set=val_iter, **args.callback_args)

    model.fit(train_iter, optimizer=optimizer, num_epochs=args.epochs, cost=cost, callbacks=callbacks) 
开发者ID:ECP-CANDLE,项目名称:Benchmarks,代码行数:58,代码来源:p1b3_baseline_neon.py


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