sirius93123

sirius93123

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DeepSpeed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

License:MITStargazers:0Issues:0Issues:0

nncf

PyTorch*-based Neural Network Compression Framework for enhanced OpenVINO™ inference

License:Apache-2.0Stargazers:0Issues:0Issues:0

XNNPACK

High-efficiency floating-point neural network inference operators for mobile, server, and Web

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jax

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

License:Apache-2.0Stargazers:0Issues:0Issues:0

pytorch_block_sparse

Fast Block Sparse Matrices for Pytorch

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dlrm

An implementation of a deep learning recommendation model (DLRM)

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open-earth-compiler

development repository for the open earth compiler

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deepspeech.pytorch

Speech Recognition using DeepSpeech2.

License:MITStargazers:0Issues:0Issues:0

AmpereSparseMatmul

study of Ampere' Sparse Matmul

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EasyTransfer

EasyTransfer is designed to make the development of transfer learning in NLP applications easier.

License:Apache-2.0Stargazers:0Issues:0Issues:0

HAWQ

Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.

License:MITStargazers:0Issues:0Issues:0

Model-Compression-Deploy

model compression and deploy. compression: 1、quantization: quantization-aware-training, 16/8/4/2-bit(dorefa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、ternary/binary(twn/bnn/xnor-net); post-training-quantization, 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization folding for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

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nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

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tvm

Open deep learning compiler stack for cpu, gpu and specialized accelerators

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hummingbird

Hummingbird compiles trained ML models into tensor computation for faster inference.

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vnpy

基于Python的开源量化交易平台开发框架

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DNN_NeuroSim_V2.1

Benchmark framework of compute-in-memory based accelerators for deep neural network (on-chip training chip focused)

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FlexFlow

A distributed deep learning framework that supports flexible parallelization strategies.

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pytorch-hessian-eigenthings

Efficient PyTorch Hessian eigendecomposition tools!

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once-for-all

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

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FlexTensor

Automatic Schedule Exploration and Optimization Framework for Tensor Computations

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inter-operator-scheduler

IOS: Inter-Operator Scheduler for CNN Acceleration

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