Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
values |
|---|---|---|---|---|---|---|
abess | abess-master/python/include/unsupported/test/special_functions.cpp | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2016 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can ob... | 16,332 | 46.205202 | 186 | cpp |
abess | abess-master/python/include/unsupported/test/splines.cpp | // This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2010-2011 Hauke Heibel <heibel@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain o... | 8,521 | 29.219858 | 91 | cpp |
abess | abess-master/python/include/unsupported/test/mpreal/mpreal.h | /*
MPFR C++: Multi-precision floating point number class for C++.
Based on MPFR library: http://mpfr.org
Project homepage: http://www.holoborodko.com/pavel/mpfr
Contact e-mail: pavel@holoborodko.com
Copyright (c) 2008-2015 Pavel Holoborodko
Contributors:
Dmitriy Gubanov, Konsta... | 115,135 | 36.080837 | 177 | h |
abess | abess-master/python/pytest/test_alg.py | import sys
import abess
import pytest
import numpy as np
from scipy.sparse import coo_matrix
from sklearn.metrics import ndcg_score
from sklearn.model_selection import KFold, GridSearchCV
from sklearn.linear_model import (
LinearRegression,
LogisticRegression,
PoissonRegressor)
from sklearn.utils.estimator_... | 25,928 | 30.892989 | 79 | py |
abess | abess-master/python/pytest/test_check.py | import abess
import numpy as np
import pytest
@pytest.mark.filterwarnings("ignore")
class TestCheck:
"""
Test for argument error, which should be recognized before the algorithm.
"""
@staticmethod
def test_base():
# path
try:
model = abess.LinearRegression(path_type='o... | 16,095 | 23.240964 | 77 | py |
abess | abess-master/python/pytest/test_dataset.py | import pytest
import numpy as np
import abess
from utilities import assert_shape
@pytest.mark.filterwarnings("ignore")
class TestOther:
"""
Test for other modules in abess package.
Include: `abess.datasets`
"""
@staticmethod
def test_glm():
np.random.seed(123)
n = 100
... | 3,791 | 28.858268 | 78 | py |
abess | abess-master/python/pytest/test_deprecated.py | import abess
import pytest
@pytest.mark.filterwarnings("ignore")
class TestDeprecated:
"""
Test for (future) deprecated modules in abess package.
"""
@staticmethod
def test_linear():
abess.abessLm()
abess.abessLogistic()
abess.abessPoisson()
abess.abessCox()
... | 1,979 | 19.625 | 68 | py |
abess | abess-master/python/pytest/test_flow.py | from time import time
import pytest
import numpy as np
from utilities import (assert_nan, assert_value, assert_fit)
from scipy.sparse import coo_matrix
import abess
@pytest.mark.filterwarnings("ignore")
class TestWorkflow:
"""
Test for abess workflow in cpp. (Take `LinearRegression` as an example.)
"""
... | 6,759 | 29.727273 | 76 | py |
abess | abess-master/python/pytest/utilities.py | import os
import pickle
import numpy as np
import pytest
CURRENT = os.path.dirname(os.path.abspath(__file__))
def assert_nan(coef):
assert not np.isnan(np.sum(coef))
def assert_value(coef1, coef2, rel=1e-2, abs=1e-2):
coef1 = coef1.reshape(-1)
coef2 = coef2.reshape(-1)
assert coef1.shape == coef2.s... | 1,134 | 22.163265 | 58 | py |
abess | abess-master/python/src/List.cpp | #ifdef R_BUILD
#include <Rcpp.h>
#include <RcppEigen.h>
#else
#include <Eigen/Eigen>
#include "List.h"
#endif
#include <iostream>
#include <typeinfo>
#include <vector>
using namespace std;
using namespace Eigen;
// void List::add(string name, int value)
// {
// // cout<<"value in int add"<<endl;
// std::s... | 6,118 | 26.075221 | 94 | cpp |
abess | abess-master/python/src/List.h | #ifndef SRC_LIST_H
#define SRC_LIST_H
#include <Eigen/Eigen>
#include <iostream>
#include <vector>
using namespace std;
using namespace Eigen;
class List {
public:
List(){};
~List(){};
// void add(string name, int value);
// void get_value_by_name(string name, int &value);
void add(string name,... | 1,775 | 36 | 93 | h |
abess | abess-master/python/src/pywrap.cpp | #include <pybind11/eigen.h>
#include <pybind11/pybind11.h>
#include <tuple>
#include "List.h"
#include "api.h"
std::tuple<Eigen::MatrixXd, Eigen::VectorXd, double, double, double> pywrap_GLM(
Eigen::MatrixXd x_Mat, Eigen::MatrixXd y_Mat, Eigen::VectorXd weight_Vec, int n, int p, int normalize_type,
int algor... | 6,368 | 49.149606 | 119 | cpp |
abess | abess-master/src/Algorithm.h | /**
* @file Algorithm.h
* @brief the algorithm for fitting on given parameter.
* @author Jin Zhu (zhuj37@mail2.sysu.edu.cn),
* Kangkang Jiang (jiangkk3@mail2.sysu.edu.cn),
* Junhao Huang (huangjh256@mail2.sysu.edu.cn)
* @version 0.0.1
* @date 2021-07-31
* @copyright GNU General Public License (GPL)
*/
... | 27,565 | 42.617089 | 120 | h |
abess | abess-master/src/AlgorithmGLM.h | #ifndef SRC_ALGORITHMGLM_H
#define SRC_ALGORITHMGLM_H
#include "Algorithm.h"
using namespace std;
template <class T1, class T2, class T3, class T4>
class _abessGLM : public Algorithm<T1, T2, T3, T4> {
public:
_abessGLM(int algorithm_type, int model_type, int max_iter, int primary_model_fit_max_iter,
... | 84,696 | 43.320774 | 120 | h |
abess | abess-master/src/AlgorithmPCA.h | #ifndef SRC_ALGORITHMPCA_H
#define SRC_ALGORITHMPCA_H
#include <Spectra/SymEigsSolver.h>
#include "Algorithm.h"
using namespace Spectra;
template <class T4>
class abessPCA : public Algorithm<Eigen::VectorXd, Eigen::VectorXd, double, T4> {
public:
int pca_n = -1;
bool is_cv = false;
MatrixXd sigma;
... | 11,557 | 36.044872 | 120 | h |
abess | abess-master/src/Data.h | //
// Created by Jin Zhu on 2020/2/18.
//
// #define R_BUILD
#ifndef SRC_DATA_H
#define SRC_DATA_H
#ifdef R_BUILD
#include <RcppEigen.h>
// [[Rcpp::depends(RcppEigen)]]
#else
#include <Eigen/Eigen>
#endif
#include <iostream>
#include <vector>
#include "normalize.h"
#include "utilities.h"
using namespace std;
using n... | 2,313 | 21.686275 | 113 | h |
abess | abess-master/src/Metric.h | //
// Created by Jin Zhu on 2020/2/18.
//
// #define R_BUILD
#ifndef SRC_METRICS_H
#define SRC_METRICS_H
#ifdef R_BUILD
#include <Rcpp.h>
using namespace Rcpp;
#endif
#include <algorithm>
#include <random>
#include <vector>
#include "Algorithm.h"
#include "Data.h"
#include "utilities.h"
template <class T1, class T2... | 19,691 | 39.68595 | 119 | h |
abess | abess-master/src/abessOpenMP.h | #ifndef SRC_ABESSOPENMP_H
#define SRC_ABESSOPENMP_H
#ifdef _OPENMP
#include <omp.h>
// [[Rcpp::plugins(openmp)]]
#else
#ifndef DISABLE_OPENMP
#ifndef R_BUILD
// use pragma message instead of warning
#pragma message( \
"Warning: OpenMP is not available, " \
... | 725 | 28.04 | 69 | h |
abess | abess-master/src/api.cpp | // #define R_BUILD
#ifdef R_BUILD
#include <Rcpp.h>
#include <RcppEigen.h>
// [[Rcpp::depends(RcppEigen)]]
using namespace Rcpp;
#else
#include <Eigen/Eigen>
#include "List.h"
#endif
#include <iostream>
#include <vector>
#include "Algorithm.h"
#include "AlgorithmGLM.h"
#include "AlgorithmPCA.h"
#include "utiliti... | 26,560 | 46.857658 | 120 | cpp |
abess | abess-master/src/api.h | /*****************************************************************************
* OpenST Basic tool library *
* Copyright (C) 2021 Kangkang Jiang jiangkk3@mail2.sysu.edu.cn *
* ... | 9,617 | 71.315789 | 120 | h |
abess | abess-master/src/normalize.cpp | //
// Created by Kangkang Jiang on 2020/3/8.
//
// #define R_BUILD
#ifdef R_BUILD
#include <Rcpp.h>
#include <RcppEigen.h>
// [[Rcpp::depends(RcppEigen)]]
using namespace Rcpp;
#else
#include <Eigen/Eigen>
#endif
#include <iostream>
#include <exception>
#include <string>
using namespace std;
void constant_warning_ith... | 4,467 | 30.027778 | 119 | cpp |
abess | abess-master/src/normalize.h | //
// Created by Jin Zhu on 2020/3/8.
//
// #define R_BUILD
#ifndef SRC_NORMALIZE_H
#define SRC_NORMALIZE_H
#ifdef R_BUILD
#include <RcppEigen.h>
#else
#include <Eigen/Eigen>
#endif
void constant_warning_ith_variable(int i);
void Normalize(Eigen::MatrixXd &X, Eigen::VectorXd &y, Eigen::VectorXd &weights, Eigen::Vect... | 1,375 | 42 | 119 | h |
abess | abess-master/src/path.h | //
// Created by Jin Zhu on 2020/3/8.
//
#ifndef SRC_PATH_H
#define SRC_PATH_H
#ifdef R_BUILD
#include <RcppEigen.h>
// [[Rcpp::depends(RcppEigen)]s]
using namespace Eigen;
#else
#include <Eigen/Eigen>
#include "List.h"
#endif
#include <vector>
#include "Algorithm.h"
#include "Data.h"
#include "Metric.h"
#include... | 12,293 | 38.277955 | 119 | h |
abess | abess-master/src/screening.h | #ifndef SRC_SCREENING_H
#define SRC_SCREENING_H
// #define R_BUILD
#ifdef R_BUILD
#include <Rcpp.h>
#include <RcppEigen.h>
using namespace Rcpp;
// [[Rcpp::depends(RcppEigen)]]
#else
#include <Eigen/Eigen>
#endif
#include <algorithm>
#include <cfloat>
#include <iostream>
#include "Data.h"
#include "utilities.h"
u... | 3,639 | 30.37931 | 110 | h |
abess | abess-master/src/utilities.cpp | //
// Created by jiangkangkang on 2020/3/9.
//
#ifndef R_BUILD
#include <Eigen/Eigen>
#include <unsupported/Eigen/MatrixFunctions>
#else
#include <RcppEigen.h>
#endif
#include <string.h>
#include <algorithm>
#include <iostream>
using namespace std;
using namespace Eigen;
Eigen::VectorXi find_ind(Eigen::VectorXi... | 16,092 | 28.857143 | 117 | cpp |
abess | abess-master/src/utilities.h | //
// Created by jiangkangkang on 2020/3/9.
//
/**
* @file utilities.h
* @brief some utilities for abess package.
*/
#ifndef SRC_UTILITIES_H
#define SRC_UTILITIES_H
#ifndef R_BUILD
#include <Eigen/Eigen>
#include <unsupported/Eigen/MatrixFunctions>
#else
#include <Rcpp.h>
#include <RcppEigen.h>
#endif
#include... | 17,518 | 32.755299 | 119 | h |
abess | abess-master/src/workflow.h | /**
* @file workflow.h
* @brief The main workflow for abess.
* @details It receives all inputs from API, runs the whole abess process
* and then return the results as a list.
*/
#ifndef SRC_WORKFLOW_H
#define SRC_WORKFLOW_H
// #define R_BUILD
#ifdef R_BUILD
#include <Rcpp.h>
#include <RcppEigen.h>
// [[Rcpp::de... | 12,239 | 39 | 120 | h |
null | RIQ-main/README.md | # Content
<!-- TOC -->
- [Overview](#overview)
- [Package Architecture](#model-architecture)
- [Dataset](#dataset)
- [ImageNet Classification](#ImageNet)
- [COCO Detection](#COCO)
- [SQuAD Dataset](#SQuAD)
- [Environment Requirements](#environment-requirements)
- [Quick Start](#quick-start)
- [Script Detailed D... | 4,363 | 29.732394 | 208 | md |
null | RIQ-main/compare_cv.py | """compare between the accuracy of the quant model and the base model"""
import os
import sys
os.environ['CURL_CA_BUNDLE'] = ''
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
import torch
import torchvision
import numpy as np
from utils import presets
from utils.onnx_bridge import OnnxBridge
from utils.quantize import get_q... | 4,222 | 41.23 | 92 | py |
null | RIQ-main/evaluate_nlp.py | """evaluate nlp"""
import sys
import os
os.environ['CURL_CA_BUNDLE'] = ''
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
from collections import Counter
import re
import string
import numpy as np
import torch
from transformers import DistilBertTokenizer
from transformers.data.processors.squad import SquadV1Processor
from ut... | 4,835 | 32.351724 | 99 | py |
null | RIQ-main/evaluate_quantization.sh | #!/bin/bash
usage() {
echo "evaluate_quantization.sh MODEL [ -v VALIDATION_DATASET] [-d DISTORTION] [-c CALIBRATION_DATA]"
echo " MODEL can be either one of the following models: VGG, resnet, alexnet, ViT, YOLO, or BERT"
echo " alternatively an onnx mod... | 4,482 | 34.579365 | 145 | sh |
null | RIQ-main/utils/ans.py | """ans"""
import numpy as np
def first_1_index(val):
"""Return the Index of the First Non-Zero Bit."""
counter = 0
while val > 1:
counter += 1
val = val >> 1
return counter
def output_nb_bits(state, nb_bits):
"""Output NbBits to a BitStream"""
mask = (1 << nb_bits) - 1
li... | 9,391 | 38.462185 | 105 | py |
null | RIQ-main/utils/dataset.py | """prepare calibration dataset for quantization"""
import numpy as np
import torch as pt
from transformers import DistilBertTokenizer
from transformers.data.processors.squad import SquadV1Processor
from utils.onnx_bridge import OnnxBridge
from utils.image_dir import ImageDir
def prepare_dataset_images(dataset_path, p... | 4,287 | 43.206186 | 97 | py |
null | RIQ-main/utils/download_BERT.py | """ download BERT model from Neural Magic Sparse Zoo"""
import os
os.environ['CURL_CA_BUNDLE'] = ''
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
from sparsezoo import Model
stub = "zoo:nlp/question_answering/distilbert-none/pytorch/huggingface/squad/base-none"
download_path = 'models/downloads/sparsezoo_bert'
model = Mod... | 471 | 38.333333 | 87 | py |
null | RIQ-main/utils/download_VGG.py | """ download VGG model"""
import torch
from torchvision.models import vgg16, VGG16_Weights
model = vgg16(weights=VGG16_Weights.IMAGENET1K_V1)
model.eval()
inp = torch.randn(1, 3, 224, 224)
in_names = ["actual_input"]
out_name = ["output"]
torch.onnx.export(model, inp, "models/VGG.onnx", verbose=False, input_names=in_n... | 387 | 31.333333 | 108 | py |
null | RIQ-main/utils/download_ViT.py | """download ViT model"""
import torch
from torchvision.models import vit_b_16, ViT_B_16_Weights
model = vit_b_16(weights=ViT_B_16_Weights.IMAGENET1K_V1)
model.eval()
inp = torch.randn(1, 3, 224, 224)
in_names = ["actual_input"]
out_name = ["output"]
torch.onnx.export(model, inp, "models/ViT.onnx", verbose=False, input... | 398 | 32.25 | 85 | py |
null | RIQ-main/utils/download_YOLO.py | """download yolo model from sparsezoo"""
import os
from sparsezoo import Model
stub = "zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none"
download_path = 'models/downloads/sparsezoo_yolo'
model = Model(stub, download_path=download_path)
os.system('mv models/downloads/sparsezoo_yolo/model.onnx models/YOLO.on... | 364 | 32.181818 | 75 | py |
null | RIQ-main/utils/download_alexnet.py | """download alexnet model"""
from torchvision.models import alexnet, AlexNet_Weights
import torch
model = alexnet(weights=AlexNet_Weights.IMAGENET1K_V1)
model.eval()
inputs = torch.randn(1, 3, 224, 224)
in_names = ["actual_input"]
out_name = ["output"]
torch.onnx.export(model, inputs, "models/alexnet.onnx", verbose=Fa... | 408 | 33.083333 | 92 | py |
null | RIQ-main/utils/download_resnet.py | """download resnet model"""
import torch
from torchvision.models import resnet50, ResNet50_Weights
model = resnet50(weights=ResNet50_Weights.IMAGENET1K_V1)
model.eval()
inp = torch.randn(1, 3, 224, 224)
in_names = ["actual_input"]
out_name = ["output"]
torch.onnx.export(model, inp, "models/resnet.onnx", verbose=False,... | 404 | 32.75 | 88 | py |
null | RIQ-main/utils/image_dir.py | """prepare images for calibration dataset"""
import glob
import cv2
import numpy as np
class ImageDir:
"""image dir"""
def __init__(self, dataset_calibration_path, dims=(1, 3, 512, 512)):
self.dataset_calibration_path = dataset_calibration_path
self.dims = dims
self.additional_input_dim... | 1,296 | 36.057143 | 91 | py |
null | RIQ-main/utils/onnx_bridge.py | """onnx bridge"""
import numpy as np
import onnx
import onnx.numpy_helper as nh
import onnxruntime
import torch
class OnnxBridge:
"""class onnxBridge"""
def __init__(self, fn):
self.m = onnx.load(fn)
cuda = torch.cuda.is_available()
providers = ['CUDAExecutionProvider', 'CPUExecutionPro... | 2,083 | 34.931034 | 99 | py |
null | RIQ-main/utils/presets.py | """presets"""
import torch
from torchvision.transforms import autoaugment, transforms
from torchvision.transforms.functional import InterpolationMode
class Chann3:
"""chan3"""
def __init__(self):
self.transform = transforms.Grayscale(3)
def __call__(self, x):
if len(x.mode) == 1:
... | 2,729 | 34 | 100 | py |
null | RIQ-main/utils/quantize.py | """quantizer"""
from math import sqrt
import numpy as np
from utils.onnx_bridge import OnnxBridge
from utils import ans
import pickle
sanity = False
verbose = False
minsize = 512
min_out_channel_size = 1
def compressed_bits(qw):
"""compressed bits"""
_, c = np.unique(qw, return_counts=True)
p = c / sum(c)
... | 7,269 | 34.291262 | 113 | py |
null | RIQ-main/utils/quantize_bert.py | """quantize bert model"""
import sys
import os
os.environ['CURL_CA_BUNDLE'] = ''
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
import onnx
import numpy as np
from onnx_bridge import OnnxBridge
from quantize import get_quantized_model
from dataset import prepare_dataset_text
def measure_cos_err(lhs, rhs):
"""measure co... | 1,239 | 28.52381 | 93 | py |
null | RIQ-main/utils/quantize_yolo.py | """quantize yolo model"""
import sys
import os
os.environ['CURL_CA_BUNDLE'] = ''
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
import onnx
import numpy as np
from quantize import get_quantized_model, get_quantized_model_by_const
from dataset import prepare_dataset_images
def measure_cos_err(lhs, rhs):
"""measure cos e... | 1,317 | 35.611111 | 99 | py |
null | OpenOOD-main/.pre-commit-config.yaml | exclude: ^tests/data/
repos:
- repo: https://github.com/PyCQA/flake8.git
rev: 3.8.3
hooks:
- id: flake8
- repo: https://github.com/pre-commit/mirrors-yapf
rev: v0.30.0
hooks:
- id: yapf
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.1.0
hooks:
- id: traili... | 893 | 26.090909 | 57 | yaml |
null | OpenOOD-main/CODE_OF_CONDUCT.md | # Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of... | 5,227 | 39.527132 | 80 | md |
null | OpenOOD-main/CONTRIBUTING.md | ## Contributing to OpenOOD
All kinds of contributions are welcome, including but not limited to the following.
- Integrate more methods under generalized OOD detection
- Fix typo or bugs
- Add new features and components
### Workflow
1. fork and pull the latest OpenOOD repository
2. checkout a new branch (do not us... | 3,077 | 43.608696 | 251 | md |
null | OpenOOD-main/README.md | # OpenOOD: Benchmarking Generalized OOD Detection
[-b31b1b?style=for-the-badge)](https://openreview.net/pdf?id=gT6j4_tskUt)
[-yellowgreen?style=for-the-badge)](https://arxiv.org/a... | 33,949 | 90.509434 | 2,893 | md |
null | OpenOOD-main/environment.yml | name: openood
channels:
- pytorch
- conda-forge
dependencies:
- python=3.8
- pytorch=1.8.1
- torchvision=0.9.1
- cudatoolkit=10.1
- scikit-learn=0.24.2
- json5=0.9.6
- matplotlib=3.3.0
- scipy=1.5
- tqdm=4.62.3
- pip
- pip:
- pyyaml==5.4.1
- pre-commit
- opencv-python==4.4.0.46
... | 502 | 16.344828 | 29 | yml |
null | OpenOOD-main/imglist_generator.py | import os
'''
path="./data/images_classic/cinic/valid"
save_path="./data/benchmark_imglist/cifar10/val_cinic10.txt"
prefix="cinic/valid/"
category=["airplane","automobile","bird","cat","deer","dog","frog","horse","ship","truck"]
with open(save_path,'a') as f:
for name in category:
label=category.index(name)... | 1,283 | 28.860465 | 90 | py |
null | OpenOOD-main/main.py | from openood.pipelines import get_pipeline
from openood.utils import launch, setup_config
def main(config):
"""Main entrance. Config is all you need to provide to run the code. Config
should be provided in the format of YAML and can be modified with command
line.
Example:
python main.py \
... | 1,114 | 24.340909 | 79 | py |
null | OpenOOD-main/setup.py | import setuptools
with open('README.md', 'r', encoding='utf-8') as fh:
long_description = fh.read()
setuptools.setup(
name='openood',
version='1.5',
author='openood dev team',
author_email='jingkang001@e.ntu.edu.sg',
description=
'This package provides a unified test platform for Out-of-Di... | 1,065 | 34.533333 | 87 | py |
null | OpenOOD-main/configs/datasets/aircraft/aircraft.yml | dataset:
name: aircraft
num_classes: 50
pre_size: 512
image_size: 448
interpolation: bilinear
normalization_type: aircraft
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir... | 815 | 23 | 63 | yml |
null | OpenOOD-main/configs/datasets/aircraft/aircraft_oe.yml | name: aircraft_oe
dataset:
name: aircraft_oe
split_names: [train, oe, val, test]
oe:
dataset_class: ImglistDataset
data_dir: ./data/images_largescale/
imglist_pth: ./data/benchmark_imglist/aircraft/train_oe.txt
batch_size: 32
shuffle: True
interpolation: bilinear
| 295 | 21.769231 | 63 | yml |
null | OpenOOD-main/configs/datasets/aircraft/aircraft_ood.yml | ood_dataset:
name: aircraft_ood
num_classes: 50
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 64
shuffle: False
pre_size: 512
image_size: 448
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood]
val:
... | 735 | 24.37931 | 70 | yml |
null | OpenOOD-main/configs/datasets/cifar10/cifar10.yml | dataset:
name: cifar10
num_classes: 10
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./... | 815 | 23 | 67 | yml |
null | OpenOOD-main/configs/datasets/cifar10/cifar10_double_label.yml | dataset:
name: cifar10_double_label
interpolation: bilinear
normalization_type: cifar10
split_names: [train, val, test]
num_classes: 12 # actually it's 10 classes but it has 2 groups
image_size: 32
pre_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
t... | 967 | 28.333333 | 71 | yml |
null | OpenOOD-main/configs/datasets/cifar10/cifar10_extra.yml | dataset:
name: cifar10
num_classes: 10
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistExtraDataDataset
dat... | 1,020 | 25.868421 | 76 | yml |
null | OpenOOD-main/configs/datasets/cifar10/cifar10_fsood.yml | ood_dataset:
name: cifar10_fsood
num_classes: 10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, nearood, farood, csid]
val:
data_dir: ./data/images_classic/
imglist_pth: ... | 1,333 | 29.318182 | 70 | yml |
null | OpenOOD-main/configs/datasets/cifar10/cifar10_oe.yml | name: cifar10_oe
dataset:
name: cifar10_oe
split_names: [train, oe, val, test]
oe:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/cifar10/train_tin597.txt
batch_size: 256
shuffle: True
interpolation: bilinear
| 294 | 21.692308 | 66 | yml |
null | OpenOOD-main/configs/datasets/cifar10/cifar10_ood.yml | ood_dataset:
name: cifar10_ood
num_classes: 10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, nearood, farood]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/b... | 1,168 | 28.974359 | 70 | yml |
null | OpenOOD-main/configs/datasets/cifar100/cifar100.yml | dataset:
name: cifar100
num_classes: 100
image_size: 32
pre_size: 32
interpolation: bilinear
normalization_type: cifar100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir:... | 824 | 23.264706 | 69 | yml |
null | OpenOOD-main/configs/datasets/cifar100/cifar100_double_label.yml | dataset:
name: cifar100_double_label
interpolation: bilinear
normalization_type: cifar100
split_names: [train, val, test]
num_classes: 120 # actually it's 100 classes but it has 20 groups
image_size: 32
pre_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}... | 978 | 28.666667 | 73 | yml |
null | OpenOOD-main/configs/datasets/cifar100/cifar100_extra.yml | dataset:
name: cifar100
num_classes: 100
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistExtraDataDataset
... | 1,031 | 26.157895 | 77 | yml |
null | OpenOOD-main/configs/datasets/cifar100/cifar100_fsood.yml | ood_dataset:
name: cifar100_ood
num_classes: 100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, nearood, farood, csid]
val:
data_dir: ./data/images_classic/
imglist_pth: ... | 1,346 | 29.613636 | 71 | yml |
null | OpenOOD-main/configs/datasets/cifar100/cifar100_oe.yml | name: cifar100_oe
dataset:
name: cifar100_oe
split_names: [train, oe, val, test]
oe:
dataset_class: ImglistDataset
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark_imglist/cifar100/train_tin597.txt
batch_size: 256
shuffle: True
interpolation: bilinear
| 297 | 21.923077 | 67 | yml |
null | OpenOOD-main/configs/datasets/cifar100/cifar100_ood.yml | ood_dataset:
name: cifar100_ood
num_classes: 100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, nearood, farood]
val:
data_dir: ./data/images_classic/
imglist_pth: ./da... | 1,178 | 29.230769 | 71 | yml |
null | OpenOOD-main/configs/datasets/covid/covid.yml | dataset:
name: covid
split_names: [train, val, test]
num_classes: 2
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
train:
dataset_class: ImglistDataset
data_dir: ./data/covid_images/
imglist_pth: ./data/imglist/covid/train_bimcv.txt
... | 774 | 24.833333 | 53 | yml |
null | OpenOOD-main/configs/datasets/covid/covid_fsood.yml | ood_dataset:
name: covid_fsood
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 20
shuffle: False
num_classes: 2
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, csid, nearood, farood]
val:
data_dir: .... | 1,337 | 26.875 | 57 | yml |
null | OpenOOD-main/configs/datasets/covid/covid_ood.yml | ood_dataset:
name: covid_ood
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 128
shuffle: False
num_classes: 2
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood]
val:
data_dir: ./data/c... | 1,075 | 25.9 | 57 | yml |
null | OpenOOD-main/configs/datasets/imagenet/imagenet.yml | dataset:
name: imagenet
num_classes: 1000
pre_size: 256
image_size: 224
interpolation: bilinear
normalization_type: imagenet
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_d... | 836 | 23.617647 | 69 | yml |
null | OpenOOD-main/configs/datasets/imagenet/imagenet_double_label.yml | dataset:
name: imagenet_double_label
interpolation: bilinear
normalization_type: imagenet
split_names: [train, val, test]
num_classes: 1008 # actually it's 1000 classes but it has 8 groups
image_size: 224
pre_size: 256
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machin... | 990 | 29.030303 | 73 | yml |
null | OpenOOD-main/configs/datasets/imagenet/imagenet_double_label_fsood.yml | ood_dataset:
name: imagenet_fsood
num_classes: 200
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 256
shuffle: False
pre_size: 256
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood, csid]
... | 1,639 | 32.469388 | 77 | yml |
null | OpenOOD-main/configs/datasets/imagenet/imagenet_fsood.yml | ood_dataset:
name: imagenet_ood
num_classes: 1000
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 32
shuffle: False
pre_size: 256
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood, csid]
... | 1,625 | 32.183673 | 73 | yml |
null | OpenOOD-main/configs/datasets/imagenet/imagenet_ood.yml | ood_dataset:
name: imagenet_ood
num_classes: 1000
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 32
shuffle: False
pre_size: 256
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood]
val:
... | 1,170 | 29.815789 | 73 | yml |
null | OpenOOD-main/configs/datasets/imagenet200/imagenet200.yml | dataset:
name: imagenet200
num_classes: 200
pre_size: 256
image_size: 224
interpolation: bilinear
normalization_type: imagenet
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data... | 856 | 24.205882 | 75 | yml |
null | OpenOOD-main/configs/datasets/imagenet200/imagenet200_double_label.yml | dataset:
name: imagenet200_double_label
interpolation: bilinear
normalization_type: imagenet
split_names: [train, val, test]
num_classes: 206 # actually it's 200 classes but it has 6 groups
image_size: 224
pre_size: 256
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machi... | 1,009 | 29.606061 | 79 | yml |
null | OpenOOD-main/configs/datasets/imagenet200/imagenet200_double_label_fsood.yml | ood_dataset:
name: imagenet200_fsood
num_classes: 200
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 256
shuffle: False
pre_size: 256
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood, csi... | 1,663 | 32.959184 | 83 | yml |
null | OpenOOD-main/configs/datasets/imagenet200/imagenet200_fsood.yml | ood_dataset:
name: imagenet200_fsood
num_classes: 200
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 256
shuffle: False
pre_size: 256
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood, csi... | 1,651 | 32.714286 | 79 | yml |
null | OpenOOD-main/configs/datasets/imagenet200/imagenet200_oe.yml | name: imagenet200_oe
dataset:
name: imagenet200_oe
split_names: [train, oe, val, test]
oe:
dataset_class: ImglistDataset
data_dir: ./data/images_largescale/
imglist_pth: ./data/benchmark_imglist/imagenet200/train_imagenet800.txt
batch_size: 256
shuffle: True
interpolation: bilinear
| 314 | 23.230769 | 75 | yml |
null | OpenOOD-main/configs/datasets/imagenet200/imagenet200_ood.yml | ood_dataset:
name: imagenet200_ood
num_classes: 200
dataset_class: ImglistDataset
interpolation: bilinear
batch_size: 256
shuffle: False
pre_size: 256
image_size: 224
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [val, nearood, farood]
val... | 1,176 | 29.973684 | 73 | yml |
null | OpenOOD-main/configs/datasets/mnist/mnist.yml | dataset:
name: mnist
num_classes: 10
image_size: 28
pre_size: 28
interpolation: bilinear
normalization_type: mnist
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir: ./data... | 799 | 22.529412 | 63 | yml |
null | OpenOOD-main/configs/datasets/mnist/mnist_fsood.yml | ood_dataset:
name: mnist_fsood
num_classes: 10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, nearood, farood, csid]
val:
data_dir: ./data/images_classic/
imglist_pth: ./... | 1,336 | 29.386364 | 71 | yml |
null | OpenOOD-main/configs/datasets/mnist/mnist_ood.yml | ood_dataset:
name: mnist_ood
num_classes: 10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, nearood, farood]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/ben... | 1,189 | 29.512821 | 71 | yml |
null | OpenOOD-main/configs/datasets/mvtec/bottle.yml | dataset:
name: bottle
num_classes: 2
pre_size: 256
image_size: 256
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, test, val]
train:
dataset_class: ImglistDataset
data_dir: ./... | 1,187 | 21.415094 | 73 | yml |
null | OpenOOD-main/configs/datasets/mvtec/cable.yml | dataset:
name: cable
num_classes: 2
pre_size: 256
image_size: 256
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, test, val]
train:
dataset_class: ImglistDataset
data_dir: ./d... | 1,181 | 21.301887 | 72 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed1.yml | dataset:
name: cifar50_seed1
num_classes: 50
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_... | 882 | 24.970588 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed1_osr.yml | ood_dataset:
name: cifar50_seed1_osr
num_classes: 50
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/... | 585 | 23.416667 | 91 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed2.yml | dataset:
name: cifar50_seed2
num_classes: 50
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_... | 882 | 24.970588 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed2_osr.yml | ood_dataset:
name: cifar50_seed2_osr
num_classes: 50
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/... | 585 | 23.416667 | 91 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed3.yml | dataset:
name: cifar50_seed3
num_classes: 50
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_... | 882 | 24.970588 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed3_osr.yml | ood_dataset:
name: cifar50_seed3_osr
num_classes: 50
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/... | 585 | 23.416667 | 91 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed4.yml | dataset:
name: cifar50_seed4
num_classes: 50
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_... | 882 | 24.970588 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed4_osr.yml | ood_dataset:
name: cifar50_seed4_osr
num_classes: 50
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/... | 585 | 23.416667 | 91 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed5.yml | dataset:
name: cifar50_seed5
num_classes: 50
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar100
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_... | 882 | 24.970588 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar50/cifar50_seed5_osr.yml | ood_dataset:
name: cifar50_seed5_osr
num_classes: 50
pre_size: 32
image_size: 32
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/... | 585 | 23.416667 | 91 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed1.yml | dataset:
name: cifar6_seed1
num_classes: 6
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir... | 870 | 24.617647 | 85 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed1_osr.yml | ood_dataset:
name: cifar6_seed1_osr
num_classes: 6
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
dataset_class: ImglistDataset
batch_size: 128
shuffle: False
split_names: [val, osr]
val:
data_dir: ./data/images_classic/
imglist_pth: ./data/benchmark... | 543 | 23.727273 | 88 | yml |
null | OpenOOD-main/configs/datasets/osr_cifar6/cifar6_seed2.yml | dataset:
name: cifar6_seed2
num_classes: 6
pre_size: 32
image_size: 32
interpolation: bilinear
normalization_type: cifar10
num_workers: '@{num_workers}'
num_gpus: '@{num_gpus}'
num_machines: '@{num_machines}'
split_names: [train, val, test]
train:
dataset_class: ImglistDataset
data_dir... | 870 | 24.617647 | 85 | yml |