Deep Neural Network Prediction

Step 1. Genernate random parameters and Run them sequentially : $ python3 collect_data.py -gp -ep -pp -pl pooling -num 10 -shuffle -d 1080ti

Step 2. Data Timeline parser : $ python3 preprocess_data.py -pt -pl pooling -d 1080ti

Step 3. Combine all raw data : $ python3 preprocess_data.py -c -pl pooling -d 1080ti

Step 4. Split raw data to train and test data as performance prediction inputs $ python3 preprocess_data.py -sp -pl pooling -d 1080ti

Step 5. Train Model :

python3 train_model.py -ftf ./utils/Feature_Target/conv_pre.json -log2file 1 -e 1000 -st 400 -sg 0.5 -lf maple -n perfnetA -pd 1080ti -pl convolution -psl pre
    
python3 train_model.py -ftf ./utils/Feature_Target/conv_exe.json -log2file 1 -e 1000 -st 400 -sg 0.5 -lf maple -n perfnetA -pd 1080ti -pl convolution -psl exe
        
python3 train_model.py -ftf ./utils/Feature_Target/conv_post.json -log2file 1 -e 1000 -st 400 -sg 0.5 -lf maple -n perfnetA -pd 1080ti -pl convolution -psl post

Step 6. Generate model csv file :

python3 verify_model.py -gmc --model lenet -b 1

Step 7. Predict model csv file :

python3 verify_model.py -pdm -n perfnetA -d 1080ti -l -eva -lf maple --model lenet -b 1

Or you can use script to predict all models with all batches:

python3 predict_script.py -n perfnetA -d 1080ti -lf maple

Predict the latency time of the deep learning models

Related tags

Overview

Deep Neural Network Prediction

Owner

QAQ

Pytorch implementation of the popular Improv RNN model originally proposed by the Magenta team.

ICSS - Interactive Continual Semantic Segmentation

Implementation of Pooling by Sliced-Wasserstein Embedding (NeurIPS 2021)

PyTorch Implementation of CycleGAN and SSGAN for Domain Transfer (Minimal)

Evaluating Cross-lingual Sentence Representations

[CVPR 2021] Monocular depth estimation using wavelets for efficiency

Pytorch library for seismic data augmentation

Identifying a Training-Set Attack’s Target Using Renormalized Influence Estimation

Cours d'Algorithmique Appliquée avec Python pour BTS SIO SISR

Official repository for the CVPR 2021 paper "Learning Feature Aggregation for Deep 3D Morphable Models"

This is Official implementation for "Pose-guided Feature Disentangling for Occluded Person Re-Identification Based on Transformer" in AAAI2022

[BMVC2021] The official implementation of "DomainMix: Learning Generalizable Person Re-Identification Without Human Annotations"

A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

Unofficial & improved implementation of NeRF--: Neural Radiance Fields Without Known Camera Parameters

Accuracy Aligned. Concise Implementation of Swin Transformer

code for our paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"

A list of all named GANs!

Code & Data for Enhancing Photorealism Enhancement

Real-Time High-Resolution Background Matting

Final project for Intro to CS class.