Posted in Python onDecember 30, 2019
1、Motivation:
I wanna modify the value of some param;
I wanna check the value of some param.
The needed function:
2、state_dict() #generator type
model.modules()#generator type
named_parameters()#OrderDict type
from torch import nn import torch #creat a simple model model = nn.Sequential( nn.Conv3d(1,16,kernel_size=1), nn.Conv3d(16,2,kernel_size=1))#tend to print the W of this layer input = torch.randn([1,1,16,256,256]) if torch.cuda.is_available(): print('cuda is avaliable') model.cuda() input = input.cuda() #打印某一层的参数名 for name in model.state_dict(): print(name) #Then I konw that the name of target layer is '1.weight' #schemem1(recommended) print(model.state_dict()['1.weight']) #scheme2 params = list(model.named_parameters())#get the index by debuging print(params[2][0])#name print(params[2][1].data)#data #scheme3 params = {}#change the tpye of 'generator' into dict for name,param in model.named_parameters(): params[name] = param.detach().cpu().numpy() print(params['0.weight']) #scheme4 for layer in model.modules(): if(isinstance(layer,nn.Conv3d)): print(layer.weight) #打印每一层的参数名和参数值 #schemem1(recommended) for name,param in model.named_parameters(): print(name,param) #scheme2 for name in model.state_dict(): print(name) print(model.state_dict()[name])
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pytorch获取模型某一层参数名及参数值方式
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HuiYu-Li声明:登载此文出于传递更多信息之目的,并不意味着赞同其观点或证实其描述。
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