flops-counter.pytorch
The tool offers an accurate calculation of multiply-add operations and parameters in neural networks through PyTorch and ATEN backends. It provides detailed per-layer cost analysis, especially effective when using the ATEN backend for comprehensive support including transformer models. Key features include per-module statistics, detailed operation logs, and module exclusion options, accommodating complex research requirements. Supporting convolutional layers, activations, RNNs, and transformer architectures, the tool serves researchers and developers in assessing neural network complexities.
