Deep Learning Framework Developer, focusing on model optimization with quantization, distillation, and pruning
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Intel
- Shanghai
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intelcaffe_weight_to_bvlc Public
This is used to convert intelcaffe weight file to be compatible with bvlc caffe
Python 5
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dlrm Public
Forked from facebookresearch/dlrm
An implementation of a deep learning recommendation model (DLRM)
Python
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pytorch/pytorch Public
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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intel/caffe Public archive
This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors.
71 contributions in the last year
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Contribution activity
December 2022
Reviewed 42 pull requests in 2 repositories
intel/neural-compressor
25 pull requests
- Reconstructing pruning API derived from Component.py.
- Fix onnxrt numpy round bug
- refine torchvision examples
- Export Qlinear to QDQ
- Pruning/Integrate new-developed pruning API with old one
- Update spr-base version number
- Pruning/Integrate new-developed pruning API with old one.
- Integrate new-developed pruning API with old one.
- Fixed pruning and distillation bug and remove invalid code
- Add mse_v2 tuning strategy
- add keras-in/keras-out to INC
- Update DyNAS interface
- Enable Transformer LT search space for Dynamic Neural Architecture Search Toolkit
- Fixed the UTs of sigopt strategy for the new API
- Remove data, metric and common to neural_compressor
- Support different backends for adaptors
- Fix Windows multi-instance bug
- Fix ITEX OOB model benchmark issue
- Refine TF NLP models with INC User NewAPI
- add warning when meets unsupported config
- INC New API TF oob, wide_deep_large_ds, 3dunet-mlperf examples
- Modify NAS n_worker as a variable
- Enhance ITEX benchmark UT check
- Disable inserting QDQ for DepthwiseConv2dNative in ITEX mode
- Refine Keras Examples for INC New API
- Some pull request reviews not shown.

