Namespace(dataset=None, gpu=-1, epochs=200, num_heads=8, l0=0, num_out_heads=1, num_layers=1, num_hidden=8, residual=False, idrop=0.6, adrop=0.6, lr=0.005, weight_decay=0.0005, alpha=0.2, early_stop=True, fastmode=False, seed=123, bias=0, loss_l0=0, syn_type='scipy', self_loop=False, sess='default')
时间: 2023-08-27 11:06:32 浏览: 62
这段代码没有提供足够的上下文,但是我可以猜测它是一个使用 argparse 模块解析命令行参数的代码段。它返回一个 Namespace 对象,其中包含了解析后的参数和对应的值。这个 Namespace 对象中包含了很多参数,包括但不限于:
- dataset: 数据集名称或路径
- gpu: 使用的 GPU 编号,-1 表示不使用 GPU
- epochs: 训练的轮数
- num_heads: 每层的头数
- l0: L0 正则化系数
- num_out_heads: 输出的头数
- num_layers: 网络层数
- num_hidden: 隐藏层的大小
- residual: 是否使用残差连接
- idrop: 输入 Dropout 的概率
- adrop: 注意力 Dropout 的概率
- lr: 初始学习率
- weight_decay: L2 正则化系数
- alpha: LeakyReLU 的负斜率
- early_stop: 是否启用早停
- fastmode: 是否启用快速模式
- seed: 随机数种子
- bias: 是否使用偏置
- loss_l0: L0 正则化系数(用于损失函数)
- syn_type: 使用的同步类型(例如“scipy”)
- self_loop: 是否使用自环
- sess: Tensorflow 会话名称
相关问题
patch_size = dataset.shape[0] - ground_truth.shape[0] + 1
This line of code is calculating the patch size by subtracting the number of rows in the ground_truth dataset from the number of rows in the dataset variable.
The resulting value is the number of rows that need to be removed from the dataset variable in order to match the number of rows in the ground_truth variable.
num_samples should be a positive integer value, but got num_samples=0
As an AI language model, I cannot see the code you are referring to, but I can provide a general explanation of this error message.
This error message typically occurs when a function or method that requires a certain number of samples is called with a value of 0 for the num_samples parameter. For example, if you are trying to generate a sample dataset but you provide a value of 0 for the number of samples, the function will not be able to generate any data and will throw this error.
To fix this error, simply provide a positive integer value for the num_samples parameter that is greater than 0.
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