call_functionapplies a free function to some values.nameis similarly the name of the value to assign to.targetis the function to be applied.argsandkwargsrepresent the arguments to the function, following the Python calling convention call_moduleapplies a module in the module hierarchy’sforward()...
...'''# 以下有值的为默认值torch.full(*size, fill_value, *, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False) 创建全填充类似形状 tensor:torch.full_like 同上zeros 和 ones,仅多 fill_value 参数与 memory_format 参数(=troch.memory_format,所需内存格式),但支持正...
self.weights = torch.nn.Parameter( torch.empty(3 * state_size, input_features + state_size)) self.bias = torch.nn.Parameter(torch.empty(3 * state_size)) self.reset_parameters() def reset_parameters(self): stdv = 1.0 / math.sqrt(self.state_size) for weight in self.parameters(): we...
isinstance(value, Parameter): if params is None: raise AttributeError("cannot assign parameters before Module.__init__() call") remove_from(self.__dict__, self._buffers, self._modules) #(4)负责parameter注册的函数 self.registerparameter(, value) # 省略的代码 此函数涉及的内容较多,所以...
self.register_parameter(name, value) elif params is not None and name in params: if value is not None: raise TypeError("cannot assign '{}' as parameter '{}' " "(torch.nn.Parameter or None expected)" .format(torch.typename(value), name)) ...
前述说到了parameters就是Net的权重参数(比如conv的weight、conv的bias、fc的weight、fc的bias),类型为tensor,用于前向和反向;比如,你针对Net使用cpu()、cuda()等调用的时候,实际上调用的就是parameter这个tensor的cpu()、cuda()等方法;再比如,你保存模型或者重新加载pth文件的时候,针对的都是parameter的操作或者赋值...
类型torch.nn.Parameter 官方解释 Parameters是Variable的子类。Variable的一种。 Paramenters和Modules一起使用的时候会有一些特殊的属性,即:当Paramenters赋值给Module的属性的时候,他会自动的被加到Module的参数列表中,也就是会出现在parameters()迭代器中。常被用于模块参数module parameter。
self.eps = eps #Extra learning parameters gamma and beta are introduced to scale and shift the embedding value as the network needed. self.gamma = nn.Parameter(torch.ones(1)) self.beta = nn.Parameter(torch.zeros(1)) def forward(self, input): mean = input.mean(dim=-1, keepdim=True)...
第一篇——什么是torch.fx今天聊一下比较重要的torch.fx,也趁着这次机会把之前的torch.fx笔记整理下,笔记大概拆成三份,分别对应三篇:什么是torch.fx基于tor...
A lot of terms in deep learning are used loosely, and the word parameter is one of them. Try not to let it throw you off. The main thing to remember about any type of parameter is that the parameter is a place-holder that will eventually hold or have a value. The goal of these...