torchmetrics：支持80+任务评价指标

转自：coggle

torchmetrics是由pytorch-lightning开源的指标计算库，内置了常见的80+指标计算逻辑，可以直接使用，也可以与pytorch-lightning结合一起使用。

安装 & 使用

pip install torchmetrics

基础案例：

# import our library
import torchmetrics

# initialize metric
metric = torchmetrics.Accuracy()

# move the metric to device you want computations to take place
device = "cuda" if torch.cuda.is_available() else "cpu"
metric.to(device)

n_batches = 10
for i in range(n_batches):
    # simulate a classification problem
    preds = torch.randn(10, 5).softmax(dim=-1).to(device)
    target = torch.randint(5, (10,)).to(device)

    # metric on current batch
    acc = metric(preds, target)
    print(f"Accuracy on batch {i}: {acc}")

# metric on all batches using custom accumulation
acc = metric.compute()
print(f"Accuracy on all data: {acc}")

Auido 任务指标

• Perceptual Evaluation of Speech Quality (PESQ)
• Permutation Invariant Training (PIT)
• Scale-Invariant Signal-to-Distortion Ratio (SI-SDR)
• Scale-Invariant Signal-to-Noise Ratio (SI-SNR)
• Short-Time Objective Intelligibility (STOI)
• Signal to Distortion Ratio (SDR)
• Signal-to-Noise Ratio (SNR)

分类 任务指标

• Accuracy
• AUC
• AUROC
• Average Precision
• Binned Average Precision
• Binned Precision Recall Curve
• Binned Recall At Fixed Precision
• Calibration Error
• Cohen Kappa
• Confusion Matrix
• Coverage Error
• Dice Score
• F1 Score
• FBeta Score
• Hamming Distance
• Hinge Loss
• Jaccard Index
• KL Divergence
• Label Ranking Average Precision
• Label Ranking Loss
• Matthews Corr. Coef.
• Precision
• Precision Recall
• Precision Recall Curve
• Recall
• ROC
• Specificity
• Stat Scores

图像 任务指标

• Error Relative Global Dim. Synthesis (ERGAS)
• Frechet Inception Distance (FID)
• Image Gradients
• Inception Score
• Kernel Inception Distance
• Learned Perceptual Image Patch Similarity (LPIPS)
• Multi-Scale SSIM
• Peak Signal-to-Noise Ratio (PSNR)
• Spectral Angle Mapper
• Spectral Distortion Index
• Structural Similarity Index Measure (SSIM)
• Universal Image Quality Index

检测 任务指标

• Mean-Average-Precision (mAP)

Pairwise 任务指标

• Cosine Similarity
• Euclidean Distance
• Linear Similarity
• Manhattan Distance

Regression 任务指标

• Cosine Similarity
• Explained Variance
• Mean Absolute Error (MAE)
• Mean Absolute Percentage Error (MAPE)
• Mean Squared Error (MSE)
• Mean Squared Log Error (MSLE)
• Pearson Corr. Coef.
• R2 Score
• Spearman Corr. Coef.
• Symmetric Mean Absolute Percentage Error (SMAPE)
• Tweedie Deviance Score
• Weighted MAPE

Retrieval 任务指标

• Retrieval Fall-Out
• Retrieval Hit Rate
• Retrieval Mean Average Precision (MAP)
• Retrieval Mean Reciprocal Rank (MRR)
• Retrieval Normalized DCG
• Retrieval Precision
• Retrieval R-Precision
• Retrieval Recall

Text 任务指标

• BERT Score
• BLEU Score
• Char Error Rate
• ChrF Score
• Extended Edit Distance
• Match Error Rate
• ROUGE Score
• Sacre BLEU Score
• SQuAD
• Translation Edit Rate (TER)
• Word Error Rate
• Word Info. Lost
  Word Info. Preserved
  
  
  
  

往期精彩：
 讲解视频来了！机器学习 公式推导与代码实现开录！
 更新！《机器学习：公式推导与代码实现》1-16章PPT下载
《机器学习 公式推导与代码实现》随书PPT示例
 时隔一年！深度学习语义分割理论与代码实践指南.pdf第二版来了！
 新书首发 | 《机器学习 公式推导与代码实现》正式出版！
《机器学习公式推导与代码实现》将会配套PPT和视频讲解！