Files
ColossalAI/colossalai/legacy/nn/metric/accuracy_2d.py
Hongxin Liu 554aa9592e [legacy] move communication and nn to legacy and refactor logger (#4671)
* [legacy] move communication to legacy (#4640)

* [legacy] refactor logger and clean up legacy codes (#4654)

* [legacy] make logger independent to gpc

* [legacy] make optim independent to registry

* [legacy] move test engine to legacy

* [legacy] move nn to legacy (#4656)

* [legacy] move nn to legacy

* [checkpointio] fix save hf config

* [test] remove useledd rpc pp test

* [legacy] fix nn init

* [example] skip tutorial hybriad parallel example

* [devops] test doc check

* [devops] test doc check
2023-09-11 16:24:28 +08:00

31 lines
792 B
Python

import torch
from torch import nn
from colossalai.legacy.nn.layer.parallel_2d import reduce_by_batch_2d, split_batch_2d
from ._utils import calc_acc
class Accuracy2D(nn.Module):
"""Accuracy for 2D parallelism
"""
def __init__(self):
super().__init__()
def forward(self, logits, targets):
"""Calculate the accuracy of predicted labels.
Args:
logits (:class:`torch.tensor`): Predicted labels.
targets (:class:`torch.tensor`): True labels from data.
Returns:
float: the accuracy of prediction.
"""
with torch.no_grad():
targets = split_batch_2d(targets)
correct = calc_acc(logits, targets)
correct = reduce_by_batch_2d(correct)
return correct