Hi @albanD, @yf225
thanks for your answer.  Yes i had a look at the docs. I will try to explain better. On python implementation inside Prelu class here https://pytorch.org/docs/stable/_modules/torch/nn/modules/activation.html#PReLU 3 you can find self.weight = Parameter(torch.Tensor(num_parameters).fill_(init)) and by default self.weights is added to the model’s Parameters if i have understood well.
On pytorch c++ i have some doubts on how to use “self.weights” Tensor and pass to the prelu function. Now i’m using register_parameter in the constructor of the model like this register_parameter("prelu1", prelu1.fill_(0.25)); where prelu is torch::Tensor prelu1 = torch::ones({1})
In the forward i use the function like this x = torch::prelu(inputs,prelu1);
Is this a correct way to register the Tensor to the model like python version?
This is what i have done.
struct TestImpl : nn::Module {


	TestImpl() : conv1(register_module("conv1", nn::Conv2d(nn::Conv2dOptions(1, 32, 4).stride(2).padding(1)))){

		register_parameter("prelu1", prelu1.fill_(0.25));

	
	
	}

	torch::Tensor forward(torch::Tensor x) {
	
		x = torch::prelu(x, prelu1);
	
	}


	nn::Conv2d conv1;

	torch::Tensor prelu1 = torch::ones({ 1 });



};

Thanks