lcskrishna / onnx-parser
ONNX Parser is a tool that automatically generates openvx inference code (CNN) from onnx binary model files.
☆17Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for onnx-parser
- PyTorch -> ONNX -> TVM for autotuning☆23Updated 4 years ago
- Test winograd convolution written in TVM for CUDA and AMDGPU☆40Updated 6 years ago
- ☆19Updated 11 months ago
- CNNs in Halide☆23Updated 9 years ago
- flexible-gemm conv of deepcore☆17Updated 4 years ago
- Training neural networks with 8-bit computations☆29Updated 8 years ago
- This is a PyTorch implementation of the Scalpel. Node pruning for five benchmark networks and SIMD-aware weight pruning for LeNet-300-100…☆41Updated 6 years ago
- Caffe Computation Graph Optimization.☆29Updated 4 years ago
- SqueezeNet Generator☆32Updated 6 years ago
- Binarized Neural Network☆9Updated 7 years ago
- A script to convert floating-point CNN models into generalized low-precision ShiftCNN representation☆55Updated 7 years ago
- Library for fast image convolution in neural networks on Intel Architecture☆29Updated 7 years ago
- Fast matrix multiplication for few-bit integer matrices on CPUs.☆27Updated 5 years ago
- TFLite python API package for parsing TFLite model☆12Updated 4 years ago
- Efficient forward propagation for BCNNs☆50Updated 7 years ago
- ICML2017 MEC: Memory-efficient Convolution for Deep Neural Network C++实现(非官方)☆17Updated 5 years ago
- ☆13Updated 7 years ago
- Optimizing Mobile Deep Learning on ARM GPU with TVM☆179Updated 6 years ago
- Proof-of-Concept CNN in Halide☆21Updated 8 years ago
- nnvm&tvm example of cross compilation and deployment in Nvidia Jetson TX2 platform☆11Updated 6 years ago
- LCNN: Lookup-based Convolutional Neural Network☆52Updated 7 years ago
- An Example of MXNet Models Comilation and Deployment with NNVM in C++☆15Updated 6 years ago
- Fast binary matrix product on CPU☆10Updated 8 years ago
- Caffe implementation of accurate low-precision neural networks☆118Updated 6 years ago
- Implementation of convolution layer in different flavors☆67Updated 7 years ago
- Evaluating efficiency of several types of convolutions☆30Updated 7 years ago
- Training Low-bits DNNs with Stochastic Quantization☆73Updated 7 years ago
- Benchmark of TVM quantized model on CUDA☆112Updated 4 years ago