GPUCodeForces/S1/28/mseloss_torch.py

23 lines
530 B
Python

# mseloss_torch.py
import torch
import torch.nn as nn
import torch.nn.functional as F
BATCH_SIZE = 16
DIM = 16384 * 16
class Model(nn.Module):
def forward(self, pred: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
# F.mse_loss 默认返回 mean reduction
return F.mse_loss(pred, target, reduction='mean')
def get_inputs():
pred = torch.randn(BATCH_SIZE, DIM, dtype=torch.float32)
target = pred + torch.rand_like(pred) * 0.1
return [pred, target]
def get_init_inputs():
return []