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Add accurancy in loss.

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Colin 2024-03-05 19:30:15 +08:00
parent cf726a5b9f
commit fdc8c657b3
1 changed files with 33 additions and 10 deletions
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43
test/loss.py
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@ -4,19 +4,42 @@ import torch.nn.functional as F
import torch.utils.checkpoint import torch.utils.checkpoint
from torch.nn import CrossEntropyLoss from torch.nn import CrossEntropyLoss
import math import math
import torchmetrics
shift_logits = torch.zeros((16, 4096)) # shift_logits = torch.zeros((16, 4096))
shift_logits[:, 2] = 10.0 # shift_logits[:, 2] = 10.0
shift_labels = (torch.ones(16) * 2).long() # shift_labels = (torch.ones(16) * 2).long()
loss = CrossEntropyLoss()(shift_logits, shift_labels) # loss = CrossEntropyLoss()(shift_logits, shift_labels)
print(loss) # print(loss)
loss = nn.CrossEntropyLoss() # loss = nn.CrossEntropyLoss()
input = torch.tensor([[1.0, 2.0, 3.0]]) # input = torch.tensor([[1.0, 2.0, 3.0]])
target = torch.tensor([0]).long() # target = torch.tensor([0]).long()
output = loss(input, target) # output = loss(input, target)
print(output) # print(output)
target = torch.tensor([0, 1, 2])
preds = torch.tensor([[0.1, 0.9, 0], [0.3, 10.1, 0.6], [0.2, 0.3, 0.9]])
accuracy = torchmetrics.Accuracy(task="multiclass", num_classes=3)
accur = accuracy(preds, target)
metric_accuracy = torchmetrics.Accuracy(
task="multiclass",
num_classes=4096,
)
shift_logits = torch.zeros((16, 2, 4096))
shift_logits[:8, :, 2] = 10.0
shift_labels = (torch.ones((16, 2)) * 2).long()
label_mask = shift_labels != 4096
shift_logits = shift_logits[label_mask]
shift_labels = shift_labels[label_mask]
accur = metric_accuracy(shift_logits, shift_labels)
metric_accuracy.update(shift_logits, shift_labels)
# torch.manual_seed(32) # torch.manual_seed(32)