Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python

15 December 2021

Papers citing "Torch.fx: Practical Program Capture and Transformation for Deep Learning in Python"

6 / 6 papers shown

Title
Allo: A Programming Model for Composable Accelerator Design Hongzheng Chen Niansong Zhang Shaojie Xiang Zhichen Zeng Mengjia Dai Zhiru Zhang 54 14 0 07 Apr 2024
HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis Shiwei Zhang Lansong Diao Chuan Wu Zongyan Cao Siyu Wang Wei Lin 35 12 0 11 Jan 2024
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning Ruihang Lai Junru Shao Siyuan Feng Steven Lyubomirsky Bohan Hou ... Sunghyun Park Prakalp Srivastava Jared Roesch T. Mowry Tianqi Chen 47 9 0 01 Nov 2023
Efficient ConvBN Blocks for Transfer Learning and Beyond Kaichao You Guo Qin Anchang Bao Mengsi Cao Ping-Chia Huang Jiulong Shan Mingsheng Long 31 1 0 19 May 2023
Colossal-Auto: Unified Automation of Parallelization and Activation Checkpoint for Large-scale Models Yuliang Liu Shenggui Li Jiarui Fang Yan Shao Boyuan Yao Yang You OffRL 24 7 0 06 Feb 2023
FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference D. Khudia Jianyu Huang Protonu Basu Summer Deng Haixin Liu Jongsoo Park M. Smelyanskiy FedML MQ 49 46 0 13 Jan 2021