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SynapseML

microsoft / SynapseML

Star 3.3k
Open

[LightGBM] Regression: how to penalize negative predictions

18
brunocous
brunocous commented Sep 2, 2020

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

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enhancement good first issue LightGBM
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666DZY666 / micronet

Star 1.8k

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

pytorch pruning convolutional-networks quantization xnor-net tensorrt model-compression bnn neuromorphic-computing group-convolution onnx network-in-network tensorrt-int8-python dorefa twn network-slimming integer-arithmetic-only quantization-aware-training post-training-quantization batch-normalization-fuse
  • Updated Oct 6, 2021
  • Python

PINTO0309 / PINTO_model_zoo

Sponsor
Star 1.7k

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

caffe computer-vision model-zoo tensorflow model models keras pytorch pretrained-models coreml onnx tensorflow-lite tflite tensorflowjs tfjs openvino edgetpu mediapipe tflite-models tf-trt
  • Updated May 14, 2022
  • Python
AdvBox

advboxes / AdvBox

Star 1.2k

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

security machine-learning deep-learning paddlepaddle adversarial-example adversarial-examples onnx fgsm adversarial-attacks deepfool graphpipe
  • Updated May 15, 2022
  • Jupyter Notebook

nebuly-ai / nebullvm

Star 1.1k
Open

Upgrade OpenVino API to v2.0

morgoth95
morgoth95 commented Apr 24, 2022

The latest release of openvino has changed the inference engine API, providing a new API that takes advantage of the full potential of Intel's latest version of IR (IR 11). More information can be found at this link. We should adapt nebullvm's OpenVinoInferenceLearner to their latest API.

Usef

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enhancement good first issue

onnx / onnx-tensorflow

Star 1.1k
Open

Tensors in list passed to 'values' of 'ConcatV2' Op have types [float64, int64, int64, int64, int64] that don't all match.

6
ansh1204
ansh1204 commented Apr 27, 2020

I am trying to convert a custom pytorch model to tensorflow, I am abe to convert pytorch to onnx but converting onnx to tensorflow gives issue.

The code snippets are as follows-

pytorch to onnx

net = custom pytorch model
net.load_state_dict("pre-trained model")
dummyInput = np.random.uniform(0,1,(1,8,3,256,256))
dummyInput = Variable(torch.FloatTensor(dummyInput))
torch.onnx.export(ne

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good first issue
sparseml

neuralmagic / sparseml

Star 960

Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models

nlp sparsity tensorflow keras pytorch deep-learning-algorithms image-classification deep-learning-library pruning object-detection automl computer-vision-algorithms onnx deep-learning-models sparsification pruning-algorithms smaller-models model-sparsification sparsification-recipes recipe-driven-approaches
  • Updated May 13, 2022
  • Python

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