forked from ccf-ai-infra/GPUCodeForces
27 lines
582 B
Python
27 lines
582 B
Python
import torch
|
|
import torch.nn as nn
|
|
import torch.nn.functional as F
|
|
|
|
|
|
class Model(nn.Module):
|
|
def __init__(self, alpha: float = 1.0, beta: float = 1.0):
|
|
super().__init__()
|
|
self.alpha = alpha
|
|
self.beta = beta
|
|
|
|
def forward(self, x: torch.Tensor) -> torch.Tensor:
|
|
gate = torch.tanh(torch.log(1.0 + torch.exp(self.beta * x)))
|
|
return self.alpha * x * gate
|
|
|
|
|
|
batch_size = 128
|
|
feature_dim = 512
|
|
|
|
|
|
def get_inputs():
|
|
x = torch.randn(batch_size, feature_dim, dtype=torch.float32)
|
|
return [x]
|
|
|
|
|
|
def get_init_inputs():
|
|
return [1.0, 1.0] |