Count the MACs / FLOPs of your PyTorch model.

Flops counter for neural networks in pytorch framework

The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)

Count the MACs / FLOPs of PyTorch models

Estimate/count FLOPS for a given neural network using pytorch

Seamless analysis of your PyTorch models (RAM usage, FLOPs, MACs, receptive field, etc.)

A simple program to calculate and visualize the FLOPs and Parameters of Pytorch models, with handy CLI and easy-to-use Python API.

Model Scope in PyTorch (include Params, FLOPs, Madds).

Easily benchmark PyTorch model FLOPs, latency, throughput, allocated gpu memory and energy consumption

pytorch model summary, statistic parameters number, memory usage, FLOPs and so on

A PyTorch implementation of FasterNet: Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks

FLOPs and other statistics COunter for Pytorch neural networks

A simple calculator for computing the number of parameters and FLOPs in convolutional neural networks with PyTorch-like APIs.

MethodsCmp: A Simple Toolkit for Counting the FLOPs/MACs, Parameters and FPS of Pytorch-based Methods

Simple PyTorch profiler that combines DeepSpeed Flops Profiler and TorchInfo

A simple profiler for PyTorch models that can profile: FLOPs for the forward pass, FLOPs for the backward pass and peak memory consumption.

TorchMeter⏲️: Your all-in-one tool for Pytorch model analysis, measuring Params, FLOPs/MACs(aka. MACC or MADD), Memory cost, Inference time and Throughput! ! 🚀

ML toolkit for analyzing the effective use of weights in neural networks. It provides quantitative metrics (entropy, coverage, FLOPs) and visualizations to identify redundant parameters and guide model simplification, compatible with both PyTorch and TensorFlow.

Auto compute the FLOPs of the nerural network with Pytorch.

count the flops of pytorch models

📊 Analyze your PyTorch models with TorchStat2 for detailed stats on parameters, FLOPs, memory, execution time, and more to optimize performance.

Calculate Pytorch model FLOPs

PyTorch module FLOPS counter

tools for FLOPs and parameters calculation of pytorch

Deep Learning Parameter Calculator & AI Architecture Advisor — Calculate parameters, FLOPs, and memory for 14+ layer types. AI-powered architecture generation via RAG pipeline. PyTorch/TensorFlow/JAX code gen.

Only the SIZE of tensors flow for pure FLOPs calculation

This is a pytorch type of counting FLOPs and Params of nets。

torchsummaryDynamic: support real FLOPs calculation of dynamic network or user-custom PyTorch ops

A new approach combining both compression-oriented (static) pruning and FLOPS-oriented (dynamic) pruning. Pytorch Implementation.

Goal: Benchmark attention/MLP layers on CPU, GPU, and Apple M-series. Deliverable: Latency, FLOPs utilization, memory bottlenecks. Grading: Benchmark correctness (30%), Comparison depth (40%), Report (30%). Reference: pytorch/examplesLinks to an external site.