complexity estimation utility of neural network
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Updated
Jun 21, 2020 - Python
complexity estimation utility of neural network
Calculating FLOPs of Pre-trained Models in NLP
FLOPs and other statistics COunter for Pytorch neural networks
Count number of parameters / MACs / FLOPS for ONNX models.
Estimate/count FLOPS for a given neural network using pytorch
各种算法评价指标的实现(mAP/Flops/params/fps/error-rate/accuracy)
FLOPs and other statistics COunter for tf.keras neural networks
Utilities to perform deep learning models benchmarking (number of parameters, FLOPS and inference latency)
benchmark pytorch models
【瑞士军刀般的工具】用最短的代码完成对模型的分析,包含 ImageNet Val、FLOPs、Params、Throuthput、CAM 等
Easily benchmark PyTorch model FLOPs, latency, throughput, allocated gpu memory and energy consumption
Dynamic Frame Interpolation in Wavelet Domain (TIP 2023)
FLOPs calculator with tf.profiler for neural network architecture written in tensorflow 2.2+ (tf.keras)
PyTorch module FLOPS counter
A simple program to calculate and visualize the FLOPs and Parameters of Pytorch models, with handy CLI and easy-to-use Python API.
Seamless analysis of your PyTorch models (RAM usage, FLOPs, MACs, receptive field, etc.)
A toolkit for scaling law research ⚖
MethodsCmp: A Simple Toolkit for Counting the FLOPs/MACs, Parameters and FPS of Pytorch-based Methods
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