# 比较与torch.nn.init.constant_的功能差异 [![查看源文件](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r1.8/resource/_static/logo_source.png)](https://gitee.com/mindspore/docs/blob/r1.8/docs/mindspore/source_zh_cn/note/api_mapping/pytorch_diff/Constant.md) ## torch.nn.init.constant_ ```python torch.nn.init.constant_( tensor, val ) ``` 更多内容详见[torch.nn.init.constant_](https://pytorch.org/docs/1.5.0/nn.init.html#torch.nn.init.constant_)。 ## mindspore.common.initializer.Constant ```python class mindspore.common.initializer.Constant(value)(arr) ``` 更多内容详见[mindspore.common.initializer.Constant](https://mindspore.cn/docs/zh-CN/r1.8/api_python/mindspore.common.initializer.html#mindspore.common.initializer.Constant)。 ## 使用方式 PyTorch:以常量`val`填充输入的tensor。 MindSpore:以`value`(整型或numpy数组)填充输入的numpy数组,且是原地更新输入值。 ## 代码示例 ```python import mindspore import torch import numpy as np # In MindSpore, fill a constant array with value(int or numpy array). input_constant = np.array([1, 2, 3]) constant_init = mindspore.common.initializer.Constant(value=1) out_constant = constant_init(input_constant) print(input_constant) # Out: # [1 1 1] # In torch, fill in the input tensor with constant val. input_constant = np.array([1, 2, 3]) out_constant = torch.nn.init.constant_( tensor=torch.tensor(input_constant), val=1 ) print(out_constant) # Out: # tensor([1, 1, 1]) ```