text stringlengths 5 22M | id stringlengths 12 177 | metadata dict | __index_level_0__ int64 0 1.37k |
|---|---|---|---|
import logging
import torch.nn as nn
from ..runner import load_checkpoint
class AlexNet(nn.Module):
"""AlexNet backbone.
Args:
num_classes (int): number of classes for classification.
"""
def __init__(self, num_classes=-1):
super(AlexNet, self).__init__()
self.num_classes =... | Cream/CDARTS/CDARTS_detection/mmcv/cnn/alexnet.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmcv/cnn/alexnet.py",
"repo_id": "Cream",
"token_count": 1038
} | 267 |
from __future__ import division
import cv2
import numpy as np
def imflip(img, direction='horizontal'):
"""Flip an image horizontally or vertically.
Args:
img (ndarray): Image to be flipped.
direction (str): The flip direction, either "horizontal" or "vertical".
Returns:
ndarray:... | Cream/CDARTS/CDARTS_detection/mmcv/image/transforms/geometry.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmcv/image/transforms/geometry.py",
"repo_id": "Cream",
"token_count": 3037
} | 268 |
from .hook import Hook
class ClosureHook(Hook):
def __init__(self, fn_name, fn):
assert hasattr(self, fn_name)
assert callable(fn)
setattr(self, fn_name, fn)
| Cream/CDARTS/CDARTS_detection/mmcv/runner/hooks/closure.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmcv/runner/hooks/closure.py",
"repo_id": "Cream",
"token_count": 85
} | 269 |
import functools
import sys
import time
from getpass import getuser
from socket import gethostname
import torch
import torch.distributed as dist
import mmcv
def get_host_info():
return '{}@{}'.format(getuser(), gethostname())
def get_dist_info():
if torch.__version__ < '1.0':
initialized = dist._i... | Cream/CDARTS/CDARTS_detection/mmcv/runner/utils.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmcv/runner/utils.py",
"repo_id": "Cream",
"token_count": 840
} | 270 |
import os
import os.path as osp
import subprocess
import tempfile
from mmcv.utils import requires_executable
@requires_executable('ffmpeg')
def convert_video(in_file, out_file, print_cmd=False, pre_options='',
**kwargs):
"""Convert a video with ffmpeg.
This provides a general api to ffmpeg... | Cream/CDARTS/CDARTS_detection/mmcv/video/processing.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmcv/video/processing.py",
"repo_id": "Cream",
"token_count": 2503
} | 271 |
from .anchor import * # noqa: F401, F403
from .bbox import * # noqa: F401, F403
from .evaluation import * # noqa: F401, F403
from .fp16 import * # noqa: F401, F403
from .mask import * # noqa: F401, F403
from .post_processing import * # noqa: F401, F403
from .utils import * # noqa: F401, F403
| Cream/CDARTS/CDARTS_detection/mmdet/core/__init__.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/core/__init__.py",
"repo_id": "Cream",
"token_count": 118
} | 272 |
from .base_sampler import BaseSampler
from ..assign_sampling import build_sampler
class CombinedSampler(BaseSampler):
def __init__(self, pos_sampler, neg_sampler, **kwargs):
super(CombinedSampler, self).__init__(**kwargs)
self.pos_sampler = build_sampler(pos_sampler, **kwargs)
self.neg_sa... | Cream/CDARTS/CDARTS_detection/mmdet/core/bbox/samplers/combined_sampler.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/core/bbox/samplers/combined_sampler.py",
"repo_id": "Cream",
"token_count": 203
} | 273 |
import functools
from inspect import getfullargspec
import torch
from .utils import cast_tensor_type
def auto_fp16(apply_to=None, out_fp32=False):
"""Decorator to enable fp16 training automatically.
This decorator is useful when you write custom modules and want to support
mixed precision training. If ... | Cream/CDARTS/CDARTS_detection/mmdet/core/fp16/decorators.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/core/fp16/decorators.py",
"repo_id": "Cream",
"token_count": 2998
} | 274 |
import os.path as osp
import mmcv
import numpy as np
from torch.utils.data import Dataset
from mmdet.core import eval_map, eval_recalls
from .pipelines import Compose
from .registry import DATASETS
@DATASETS.register_module
class CustomDataset(Dataset):
"""Custom dataset for detection.
Annotation format:
... | Cream/CDARTS/CDARTS_detection/mmdet/datasets/custom.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/datasets/custom.py",
"repo_id": "Cream",
"token_count": 3973
} | 275 |
import os.path as osp
import xml.etree.ElementTree as ET
import mmcv
import numpy as np
from .custom import CustomDataset
from .registry import DATASETS
@DATASETS.register_module
class XMLDataset(CustomDataset):
def __init__(self, min_size=None, **kwargs):
super(XMLDataset, self).__init__(**kwargs)
... | Cream/CDARTS/CDARTS_detection/mmdet/datasets/xml_style.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/datasets/xml_style.py",
"repo_id": "Cream",
"token_count": 1657
} | 276 |
# --------------------------------------------------------
# Copyright (c) 2019 Jianyuan Guo (guojianyuan1@huawei.com)
# --------------------------------------------------------
import torch
import torch.nn as nn
import torch.nn.functional as F
from .mbblock_ops import OPS
PRIMITIVES = [
'ir_k3_e3',
'ir_k3_e6... | Cream/CDARTS/CDARTS_detection/mmdet/models/bbox_heads/auto_head/mbblock_head_search.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/models/bbox_heads/auto_head/mbblock_head_search.py",
"repo_id": "Cream",
"token_count": 747
} | 277 |
import torch
from mmdet.core import bbox2roi, build_assigner, build_sampler
from .two_stage import TwoStageDetector
from .. import builder
from ..registry import DETECTORS
@DETECTORS.register_module
class MaskScoringRCNN(TwoStageDetector):
"""Mask Scoring RCNN.
https://arxiv.org/abs/1903.00241
"""
... | Cream/CDARTS/CDARTS_detection/mmdet/models/detectors/mask_scoring_rcnn.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/models/detectors/mask_scoring_rcnn.py",
"repo_id": "Cream",
"token_count": 5128
} | 278 |
from .fcn_mask_head import FCNMaskHead
from .fused_semantic_head import FusedSemanticHead
from .grid_head import GridHead
from .htc_mask_head import HTCMaskHead
from .maskiou_head import MaskIoUHead
__all__ = [
'FCNMaskHead', 'HTCMaskHead', 'FusedSemanticHead', 'GridHead',
'MaskIoUHead'
]
| Cream/CDARTS/CDARTS_detection/mmdet/models/mask_heads/__init__.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/models/mask_heads/__init__.py",
"repo_id": "Cream",
"token_count": 113
} | 279 |
# --------------------------------------------------------
# Copyright (c) 2019 Jianyuan Guo (guojianyuan1@huawei.com)
# --------------------------------------------------------
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import kaiming_init, constant_init, xavier_init
from mmdet.... | Cream/CDARTS/CDARTS_detection/mmdet/models/necks/search_pafpn.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/models/necks/search_pafpn.py",
"repo_id": "Cream",
"token_count": 2998
} | 280 |
from .dcn import (DeformConv, DeformConvPack, ModulatedDeformConv,
ModulatedDeformConvPack, DeformRoIPooling,
DeformRoIPoolingPack, ModulatedDeformRoIPoolingPack,
deform_conv, modulated_deform_conv, deform_roi_pooling)
from .gcb import ContextBlock
from .nms import ... | Cream/CDARTS/CDARTS_detection/mmdet/ops/__init__.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/ops/__init__.py",
"repo_id": "Cream",
"token_count": 408
} | 281 |
#include <torch/extension.h>
#include <cmath>
#include <vector>
int ROIPoolForwardLaucher(const at::Tensor features, const at::Tensor rois,
const float spatial_scale, const int channels,
const int height, const int width, const int num_rois,
... | Cream/CDARTS/CDARTS_detection/mmdet/ops/roi_pool/src/roi_pool_cuda.cpp/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/ops/roi_pool/src/roi_pool_cuda.cpp",
"repo_id": "Cream",
"token_count": 1416
} | 282 |
import inspect
import mmcv
class Registry(object):
def __init__(self, name):
self._name = name
self._module_dict = dict()
def __repr__(self):
format_str = self.__class__.__name__ + '(name={}, items={})'.format(
self._name, list(self._module_dict.keys()))
return f... | Cream/CDARTS/CDARTS_detection/mmdet/utils/registry.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_detection/mmdet/utils/registry.py",
"repo_id": "Cream",
"token_count": 975
} | 283 |
## Prerequisites
- Ubuntu 16.04
- Python 3.7
- CUDA 11.1 (lower versions may work but were not tested)
- NVIDIA GPU (>= 11G graphic memory) + CuDNN v7.3
This repository has been tested on RTX 3090. Configurations (e.g batch size, image patch size) may need to be changed on different platforms.
## Installation
* Clone... | Cream/CDARTS/CDARTS_segmentation/README.md/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/README.md",
"repo_id": "Cream",
"token_count": 670
} | 284 |
# ------------------------------------------------------------------------------
# Loads Cityscapes panoptic dataset.
# Written by Bowen Cheng (bcheng9@illinois.edu)
# ------------------------------------------------------------------------------
import json
import os
import numpy as np
from .cityscapes import Citys... | Cream/CDARTS/CDARTS_segmentation/dataloaders/segdatasets/cityscapes_panoptic.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/dataloaders/segdatasets/cityscapes_panoptic.py",
"repo_id": "Cream",
"token_count": 2718
} | 285 |
# ------------------------------------------------------------------------------
# Reference: https://github.com/facebookresearch/detectron2/blob/master/detectron2/evaluation/sem_seg_evaluation.py
# Modified by Bowen Cheng (bcheng9@illinois.edu)
# ------------------------------------------------------------------------... | Cream/CDARTS/CDARTS_segmentation/segmentation/evaluation/semantic.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/segmentation/evaluation/semantic.py",
"repo_id": "Cream",
"token_count": 1892
} | 286 |
# ------------------------------------------------------------------------------
# Loss functions.
# Written by Bowen Cheng (bcheng9@illinois.edu)
# ------------------------------------------------------------------------------
import torch
import torch.nn as nn
from torch.nn import functional as F
class RegularCE(n... | Cream/CDARTS/CDARTS_segmentation/segmentation/model/loss/criterion.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/segmentation/model/loss/criterion.py",
"repo_id": "Cream",
"token_count": 2230
} | 287 |
# ------------------------------------------------------------------------------
# Saves raw outputs and targets.
# Written by Bowen Cheng (bcheng9@illinois.edu)
# ------------------------------------------------------------------------------
import os
import numpy as np
import PIL.Image as img
import torch
from .s... | Cream/CDARTS/CDARTS_segmentation/segmentation/utils/debug.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/segmentation/utils/debug.py",
"repo_id": "Cream",
"token_count": 4617
} | 288 |
from collections import namedtuple
Genotype = namedtuple('Genotype', 'normal normal_concat reduce reduce_concat')
PRIMITIVES = [
'skip',
'conv',
'conv_di',
'conv_2x',
'conv_2x_di',
]
NASNet = Genotype(
normal = [
('sep_conv_5x5', 1),
('sep_conv_3x3', 0),
('sep_conv_5x5', 0),
('s... | Cream/CDARTS/CDARTS_segmentation/tools/utils/genotypes.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/tools/utils/genotypes.py",
"repo_id": "Cream",
"token_count": 1235
} | 289 |
_BASE_: ../Cityscapes-PanopticSegmentation/Base-PanopticDeepLab-OS16.yaml
MODEL:
WEIGHTS: "detectron2://DeepLab/R-52.pkl"
PIXEL_MEAN: [123.675, 116.280, 103.530]
PIXEL_STD: [58.395, 57.120, 57.375]
BACKBONE:
NAME: "build_resnet_deeplab_backbone"
RESNETS:
DEPTH: 50
NORM: "SyncBN"
RES5_MULTI_GRI... | Cream/CDARTS/CDARTS_segmentation/train/configs/ADE20K/512.yaml/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/train/configs/ADE20K/512.yaml",
"repo_id": "Cream",
"token_count": 565
} | 290 |
import numpy as np
try:
from utils.darts_utils import compute_latency_ms_tensorrt as compute_latency
print("use TensorRT for latency test")
except:
from utils.darts_utils import compute_latency_ms_pytorch as compute_latency
print("use PyTorch for latency test")
import torch
import torch.nn as nn
import... | Cream/CDARTS/CDARTS_segmentation/train/seg_oprs.py/0 | {
"file_path": "Cream/CDARTS/CDARTS_segmentation/train/seg_oprs.py",
"repo_id": "Cream",
"token_count": 11850
} | 291 |
import math
import torch
import random
import numpy as np
import torch.distributed as dist
from torch.utils.data import Sampler
from PIL import Image, ImageEnhance, ImageOps
class SubsetDistributedSampler(Sampler):
"""Sampler that restricts data loading to a subset of the dataset.
It is especially useful in c... | Cream/CDARTS/benchmark201/datasets/data_utils.py/0 | {
"file_path": "Cream/CDARTS/benchmark201/datasets/data_utils.py",
"repo_id": "Cream",
"token_count": 8183
} | 292 |
import os
import argparse
parser = argparse.ArgumentParser(description='supernet training')
parser.add_argument('path', type=str, default='train',
help='mode')
args = parser.parse_args()
def main():
file_path = args.path
info = {}
cnt = 0
dataset_idx = 0
dataset = ['cifar10-va... | Cream/CDARTS/benchmark201/utils/get_info.py/0 | {
"file_path": "Cream/CDARTS/benchmark201/utils/get_info.py",
"repo_id": "Cream",
"token_count": 690
} | 293 |
import torch
import torch.nn as nn
import torch.nn.functional as F
cos = nn.CosineSimilarity(dim=1, eps=1e-6)
mse = nn.MSELoss()
smooth_l1 = nn.SmoothL1Loss()
class CrossEntropyLabelSmooth(nn.Module):
def __init__(self, num_classes, epsilon):
super(CrossEntropyLabelSmooth, self).__init__()
self.n... | Cream/CDARTS/lib/models/loss.py/0 | {
"file_path": "Cream/CDARTS/lib/models/loss.py",
"repo_id": "Cream",
"token_count": 573
} | 294 |
import os
import time
import torch
import torchvision
from collections import OrderedDict
from lib.utils.util import AverageMeter, accuracy, reduce_tensor
# retrain function
def train_epoch(
epoch, model, loader, optimizer, loss_fn, cfg,
lr_scheduler=None, saver=None, output_dir='', use_amp=False,
... | Cream/Cream/lib/core/retrain.py/0 | {
"file_path": "Cream/Cream/lib/core/retrain.py",
"repo_id": "Cream",
"token_count": 2740
} | 295 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Written by Hao Du and Houwen Peng
# email: haodu8-c@my.cityu.edu.hk and houwen.peng@microsoft.com
import sys
import argparse
import torch.nn as nn
from torch import optim as optim
from thop import profile, clever_format
from timm.utils import... | Cream/Cream/lib/utils/util.py/0 | {
"file_path": "Cream/Cream/lib/utils/util.py",
"repo_id": "Cream",
"token_count": 2691
} | 296 |
'''
Build trainining/testing datasets
'''
import os
import json
from torchvision import datasets, transforms
from torchvision.datasets.folder import ImageFolder, default_loader
import torch
from timm.data.constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.data import create_transform
try:
fro... | Cream/EfficientViT/classification/data/datasets.py/0 | {
"file_path": "Cream/EfficientViT/classification/data/datasets.py",
"repo_id": "Cream",
"token_count": 2417
} | 297 |
#!/usr/bin/env bash
CONFIG=$1
GPUS=$2
PORT=${PORT:-29500}
PYTHONPATH="$(dirname $0)/..":$PYTHONPATH \
python -m torch.distributed.launch --nproc_per_node=$GPUS --master_port=$PORT \
$(dirname "$0")/train.py $CONFIG --launcher pytorch ${@:3}
| Cream/EfficientViT/downstream/dist_train.sh/0 | {
"file_path": "Cream/EfficientViT/downstream/dist_train.sh",
"repo_id": "Cream",
"token_count": 108
} | 298 |
# Mini-DeiT
This repo is for MiniViT for DeiTs.
## Model Zoo
Model | Params. | Input | Top-1 Acc. % | Top-5 Acc. % | Download link
--- |:---:|:---:|:---:|:---:|:---:
Mini-DeiT-Ti | 3M | 224x224 | 73.0 | 91.6 | [model](https://github.com/DominickZhang/MiniViT-model-zoo/releases/download/v1.0.0/mini_deit_tiny_patch16_2... | Cream/MiniViT/Mini-DeiT/README.md/0 | {
"file_path": "Cream/MiniViT/Mini-DeiT/README.md",
"repo_id": "Cream",
"token_count": 2032
} | 299 |
"""
Misc functions, including distributed helpers.
Mostly copy-paste from torchvision references.
"""
import io
import os
import time
from collections import defaultdict, deque
import datetime
import torch
import torch.distributed as dist
class SmoothedValue(object):
"""Track a series of values and provide acce... | Cream/MiniViT/Mini-DeiT/utils.py/0 | {
"file_path": "Cream/MiniViT/Mini-DeiT/utils.py",
"repo_id": "Cream",
"token_count": 3386
} | 300 |
import io
import os
import time
import torch.distributed as dist
import torch.utils.data as data
from PIL import Image
from .zipreader import is_zip_path, ZipReader
def has_file_allowed_extension(filename, extensions):
"""Checks if a file is an allowed extension.
Args:
filename (string): path to a fi... | Cream/MiniViT/Mini-Swin/data/cached_image_folder.py/0 | {
"file_path": "Cream/MiniViT/Mini-Swin/data/cached_image_folder.py",
"repo_id": "Cream",
"token_count": 3975
} | 301 |
import os
import torch
import torch.nn as nn
import torch.distributed as dist
import torch.nn.functional as F
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
try:
# noinspection PyUnresolvedReferences
from apex import amp
except ImportError:
amp = None
import argparse
from config import g... | Cream/MiniViT/Mini-Swin/utils.py/0 | {
"file_path": "Cream/MiniViT/Mini-Swin/utils.py",
"repo_id": "Cream",
"token_count": 4868
} | 302 |
import torch
import torch.nn as nn
from torch.nn import functional as F
try:
import torch.distributed.nn
from torch import distributed as dist
has_distributed = True
except ImportError:
has_distributed = False
try:
import horovod.torch as hvd
except ImportError:
hvd = None
def gather_feature... | Cream/TinyCLIP/src/open_clip/loss.py/0 | {
"file_path": "Cream/TinyCLIP/src/open_clip/loss.py",
"repo_id": "Cream",
"token_count": 3078
} | 303 |
from typing import Optional, Sequence, Tuple
import torch
import torch.nn as nn
import torchvision.transforms.functional as F
from torchvision.transforms import Normalize, Compose, RandomResizedCrop, InterpolationMode, ToTensor, Resize, \
CenterCrop
from .constants import OPENAI_DATASET_MEAN, OPENAI_DATASET_STD
... | Cream/TinyCLIP/src/open_clip/transform.py/0 | {
"file_path": "Cream/TinyCLIP/src/open_clip/transform.py",
"repo_id": "Cream",
"token_count": 2065
} | 304 |
import numpy as np
def assign_learning_rate(optimizer, new_lr):
if isinstance(optimizer, list):
for opt in optimizer:
assign_learning_rate(opt, new_lr)
else:
for param_group in optimizer.param_groups:
param_group["lr"] = new_lr
def _warmup_lr(base_lr, warmup_length, s... | Cream/TinyCLIP/src/training/scheduler.py/0 | {
"file_path": "Cream/TinyCLIP/src/training/scheduler.py",
"repo_id": "Cream",
"token_count": 1286
} | 305 |
import os
# from torchvision.datasets import CIFAR100, CIFAR10, MNIST, QMNIST, KMNIST, FashionMNIST, ImageNet, ImageFolder
from torchvision.datasets import CIFAR100, CIFAR10, MNIST, KMNIST, FashionMNIST, ImageFolder
try:
from torchvision.datasets import Places365
has_places365 = True
except ImportError:
ha... | Cream/TinyViT/data/augmentation/dataset_factory.py/0 | {
"file_path": "Cream/TinyViT/data/augmentation/dataset_factory.py",
"repo_id": "Cream",
"token_count": 2475
} | 306 |
""" Real labels evaluator for ImageNet
Paper: `Are we done with ImageNet?` - https://arxiv.org/abs/2006.07159
Based on Numpy example at https://github.com/google-research/reassessed-imagenet
Hacked together by / Copyright 2020 Ross Wightman
"""
import os
import json
import numpy as np
class RealLabelsImagenet:
... | Cream/TinyViT/data/augmentation/real_labels.py/0 | {
"file_path": "Cream/TinyViT/data/augmentation/real_labels.py",
"repo_id": "Cream",
"token_count": 742
} | 307 |
# --------------------------------------------------------
# TinyViT Main (train/validate)
# Copyright (c) 2022 Microsoft
# Based on the code: Swin Transformer
# (https://github.com/microsoft/swin-transformer)
# Add distillation with saved teacher logits
# --------------------------------------------------------
imp... | Cream/TinyViT/main.py/0 | {
"file_path": "Cream/TinyViT/main.py",
"repo_id": "Cream",
"token_count": 10302
} | 308 |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import torch.utils.data
import torchvision
from .coco import build as build_coco
def get_coco_api_from_dataset(dataset):
for _ in range(10):
# if isinstance(dataset, torchvision.datasets.CocoDetection):
# break
if ... | Cream/iRPE/DETR-with-iRPE/datasets/__init__.py/0 | {
"file_path": "Cream/iRPE/DETR-with-iRPE/datasets/__init__.py",
"repo_id": "Cream",
"token_count": 365
} | 309 |
"""Functional interface"""
import warnings
import math
import torch
from torch._C import _infer_size, _add_docstr
from torch.nn import _reduction as _Reduction
from torch.nn.modules import utils
from torch.nn.modules.utils import _single, _pair, _triple, _list_with_default
from torch.nn import grad # noqa: F401
from ... | Cream/iRPE/DETR-with-iRPE/models/rpe_attention/rpe_attention_function.py/0 | {
"file_path": "Cream/iRPE/DETR-with-iRPE/models/rpe_attention/rpe_attention_function.py",
"repo_id": "Cream",
"token_count": 7847
} | 310 |
Hiring research interns for neural architecture search projects: houwen.peng@microsoft.com
# Rethinking and Improving Relative Position Encoding for Vision Transformer
[[Paper]](https://openaccess.thecvf.com/content/ICCV2021/html/Wu_Rethinking_and_Improving_Relative_Position_Encoding_for_Vision_Transformer_ICCV_2021_... | Cream/iRPE/DeiT-with-iRPE/README.md/0 | {
"file_path": "Cream/iRPE/DeiT-with-iRPE/README.md",
"repo_id": "Cream",
"token_count": 2509
} | 311 |
# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
"""
A script to run multinode training with submitit.
"""
import argparse
import os
import uuid
from pathlib import Path
import main as classification
import submitit
def parse_args():
classification_parser = classification.get_args_parser()
... | Cream/iRPE/DeiT-with-iRPE/run_with_submitit.py/0 | {
"file_path": "Cream/iRPE/DeiT-with-iRPE/run_with_submitit.py",
"repo_id": "Cream",
"token_count": 1646
} | 312 |
import torch as th
import torch.nn as nn
import torch.nn.functional as F
def linear_combination(x, y, epsilon):
return epsilon*x + (1-epsilon)*y
def reduce_loss(loss, reduction='mean'):
return loss.mean() if reduction == 'mean' \
else loss.sum() if reduction == 'sum' else loss
class LabelS... | CvT/lib/core/loss.py/0 | {
"file_path": "CvT/lib/core/loss.py",
"repo_id": "CvT",
"token_count": 685
} | 313 |
import pickle
import torch
import torch.distributed as dist
class Comm(object):
def __init__(self, local_rank=0):
self.local_rank = 0
@property
def world_size(self):
if not dist.is_available():
return 1
if not dist.is_initialized():
return 1
return... | CvT/lib/utils/comm.py/0 | {
"file_path": "CvT/lib/utils/comm.py",
"repo_id": "CvT",
"token_count": 1625
} | 314 |
import sys
sys.path.append('../')
import unittest
import numpy as np
import pandas as pd
import shutil
import os
import invoker
class TestErrorInput(unittest.TestCase):
def setUp(self):
self.__input_path = './error_test_input_file.csv'
self.__detect_mode = 'AnomalyOnly'
self.__timestamp_c... | anomalydetector/aml_component/tests/test_error_input.py/0 | {
"file_path": "anomalydetector/aml_component/tests/test_error_input.py",
"repo_id": "anomalydetector",
"token_count": 4170
} | 315 |
"""
Copyright (C) Microsoft Corporation. All rights reserved.
Microsoft Corporation ("Microsoft") grants you a nonexclusive, perpetual,
royalty-free right to use, copy, and modify the software code provided by us
("Software Code"). You may not sublicense the Software Code or any use of it
(except to your affiliates... | anomalydetector/srcnn/net.py/0 | {
"file_path": "anomalydetector/srcnn/net.py",
"repo_id": "anomalydetector",
"token_count": 1578
} | 316 |
{
"python.testing.pytestArgs": [
"tests"
],
"python.testing.unittestEnabled": false,
"python.testing.nosetestsEnabled": false,
"python.testing.pytestEnabled": true,
"cmake.configureOnOpen": false
} | archai/.vscode/settings.json/0 | {
"file_path": "archai/.vscode/settings.json",
"repo_id": "archai",
"token_count": 94
} | 317 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import List
from logging import Handler
import os
import time
from overrides import overrides
from threading import Lock
class AtomicFileHandler(Handler):
"""
This class opens and writes entire file instead of appending one... | archai/archai/common/atomic_file_handler.py/0 | {
"file_path": "archai/archai/common/atomic_file_handler.py",
"repo_id": "archai",
"token_count": 755
} | 318 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import argparse
import os
import glob
import sys
import logging
import datetime
import platform
import time
import numpy as np
import re
from torch import Tensor
from azure.data.tables import TableServiceClient, UpdateMode, EntityProperty, EdmType... | archai/archai/common/store.py/0 | {
"file_path": "archai/archai/common/store.py",
"repo_id": "archai",
"token_count": 13684
} | 319 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import Callable, Optional
from overrides import overrides
from torch.utils.data import Dataset
from torchvision.datasets import KMNIST, MNIST, QMNIST, FashionMNIST
from torchvision.transforms import ToTensor
from archai.api.dataset_... | archai/archai/datasets/cv/mnist_dataset_provider.py/0 | {
"file_path": "archai/archai/datasets/cv/mnist_dataset_provider.py",
"repo_id": "archai",
"token_count": 1031
} | 320 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import List, Optional
from overrides import overrides
from archai.api.dataset_provider import DatasetProvider
from archai.common.distributed_utils import sync_workers
from archai.datasets.nlp.nvidia_dataset_provider_utils import Cor... | archai/archai/datasets/nlp/nvidia_dataset_provider.py/0 | {
"file_path": "archai/archai/datasets/nlp/nvidia_dataset_provider.py",
"repo_id": "archai",
"token_count": 773
} | 321 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from archai.api.dataset_provider import DatasetProvider
from archai.discrete_search.api.archai_model import ArchaiModel
from archai.discrete_search.api.model_evaluator import ModelEvaluator, AsyncModelEvaluator
from archai.discrete_search.api.pre... | archai/archai/discrete_search/api/__init__.py/0 | {
"file_path": "archai/archai/discrete_search/api/__init__.py",
"repo_id": "archai",
"token_count": 275
} | 322 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import Any, Dict, List, Optional, Tuple, Union
import onnxruntime as rt
import torch
from overrides import overrides
from archai.common.timing import MeasureBlockTime
from archai.discrete_search.api.archai_model import ArchaiModel
f... | archai/archai/discrete_search/evaluators/onnx_model.py/0 | {
"file_path": "archai/archai/discrete_search/evaluators/onnx_model.py",
"repo_id": "archai",
"token_count": 1514
} | 323 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import itertools
from collections import OrderedDict
from copy import deepcopy
from functools import reduce
from random import Random
from typing import Any, Dict, List, Optional, Tuple
from archai.discrete_search.search_spaces.config.arch_confi... | archai/archai/discrete_search/search_spaces/config/arch_param_tree.py/0 | {
"file_path": "archai/archai/discrete_search/search_spaces/config/arch_param_tree.py",
"repo_id": "archai",
"token_count": 2712
} | 324 |
'''
Adapted from https://github.com/ctlllll/SGConv
'''
import math
from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import PretrainedConfig
from einops import rearrange
import opt_einsum as oe
from archai.discrete_search.search_spaces.config import... | archai/archai/discrete_search/search_spaces/nlp/tfpp/ops/sgconv.py/0 | {
"file_path": "archai/archai/discrete_search/search_spaces/nlp/tfpp/ops/sgconv.py",
"repo_id": "archai",
"token_count": 9690
} | 325 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from __future__ import annotations
from typing import Any, Dict, Optional
import torch
import transformers
from archai.quantization.quantizers import FakeDynamicQuant
class FakeDynamicQuantHFConv1D(transformers.modeling_utils.Conv1D):
""... | archai/archai/quantization/nlp/modules.py/0 | {
"file_path": "archai/archai/quantization/nlp/modules.py",
"repo_id": "archai",
"token_count": 1899
} | 326 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import Optional
from overrides import overrides
from archai.common.config import Config
from archai.common.ordered_dict_logger import get_global_logger
from archai.supergraph.nas.arch_trainer import ArchTrainer
from archai.supergrap... | archai/archai/supergraph/algos/didarts/didarts_arch_trainer.py/0 | {
"file_path": "archai/archai/supergraph/algos/didarts/didarts_arch_trainer.py",
"repo_id": "archai",
"token_count": 719
} | 327 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import copy
from typing import List, Tuple
from overrides import overrides
from archai.common.config import Config
from archai.supergraph.algos.gumbelsoftmax.gs_op import GsOp
from archai.supergraph.nas.model_desc import (
CellType,
Con... | archai/archai/supergraph/algos/gumbelsoftmax/gs_model_desc_builder.py/0 | {
"file_path": "archai/archai/supergraph/algos/gumbelsoftmax/gs_model_desc_builder.py",
"repo_id": "archai",
"token_count": 1058
} | 328 |
"""Model specification for module connectivity individuals.
This module handles pruning the unused parts of the computation graph but should
avoid creating any TensorFlow models (this is done inside model_builder.py).
"""
from __future__ import absolute_import, division, print_function
import copy
import numpy as n... | archai/archai/supergraph/algos/nasbench101/model_spec.py/0 | {
"file_path": "archai/archai/supergraph/algos/nasbench101/model_spec.py",
"repo_id": "archai",
"token_count": 1836
} | 329 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import math as ma
from typing import Optional
import torch
from overrides import overrides
from torch import Tensor, nn
from torch.optim.optimizer import Optimizer
from archai.common import ml_utils
from archai.common.common import get_conf
fro... | archai/archai/supergraph/algos/xnas/xnas_arch_trainer.py/0 | {
"file_path": "archai/archai/supergraph/algos/xnas/xnas_arch_trainer.py",
"repo_id": "archai",
"token_count": 3257
} | 330 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import torchvision
from overrides import overrides
from torchvision.transforms import transforms
from archai.common import utils
from archai.common.config import Config
from archai.supergraph.datasets.dataset_provider import (
DatasetProvide... | archai/archai/supergraph/datasets/providers/fashion_mnist_provider.py/0 | {
"file_path": "archai/archai/supergraph/datasets/providers/fashion_mnist_provider.py",
"repo_id": "archai",
"token_count": 784
} | 331 |
import os
import torch
import torch.nn as nn
__all__ = ['MobileNetV2', 'mobilenet_v2']
class ConvBNReLU(nn.Sequential):
def __init__(self, in_planes, out_planes, kernel_size=3, stride=1, groups=1):
padding = (kernel_size - 1) // 2
super(ConvBNReLU, self).__init__(
nn.Conv2d(in_planes... | archai/archai/supergraph/models/mobilenetv2.py/0 | {
"file_path": "archai/archai/supergraph/models/mobilenetv2.py",
"repo_id": "archai",
"token_count": 2133
} | 332 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from typing import Iterable, List, Optional
from overrides import EnforceOverrides, overrides
from torch import nn
from archai.supergraph.nas.arch_module import ArchModule
from archai.supergraph.nas.dag_edge import DagEdge
from archai.supergrap... | archai/archai/supergraph/nas/cell.py/0 | {
"file_path": "archai/archai/supergraph/nas/cell.py",
"repo_id": "archai",
"token_count": 1305
} | 333 |
import itertools
import math
import os
from collections import OrderedDict
import torch
from torch import nn
from torch.nn.parallel.data_parallel import DataParallel
from tqdm import tqdm
from archai.common import ml_utils, utils
from archai.common.common import get_tb_writer
from archai.common.ordered_dict_logger im... | archai/archai/supergraph/utils/augmented_trainer.py/0 | {
"file_path": "archai/archai/supergraph/utils/augmented_trainer.py",
"repo_id": "archai",
"token_count": 5463
} | 334 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import json
import math
import os
import time
from typing import Any, Dict, Iterable, Iterator, Optional, Tuple, Union
import deepspeed
import mlflow
import torch
from deepspeed.pipe import PipelineModule
from deepspeed.utils import RepeatingLoa... | archai/archai/trainers/nlp/ds_trainer.py/0 | {
"file_path": "archai/archai/trainers/nlp/ds_trainer.py",
"repo_id": "archai",
"token_count": 6868
} | 335 |
autoaug:
model:
type: shakeshake26_2x112d
loader:
aug: fa_reduced_cifar10
cutout: 16
batch: 512
epochs: 1800
lr_schedule:
type: 'cosine'
warmup:
multiplier: 4
epochs: 5
optimizer:
type: sgd
lr: 0.01
nesterov: True
decay: 0.002
| archai/confs/aug/shake26_2x112d_cifar_b512.yaml/0 | {
"file_path": "archai/confs/aug/shake26_2x112d_cifar_b512.yaml",
"repo_id": "archai",
"token_count": 150
} | 336 |
dataset:
dataroot: '$default_dataroot' # folder where directory for each dataset exist, empty string means chose default based on OS which is typically ~/dataroot
# Typically, create symbolic link ~/dataroot pointing to yout dataset location
# cd %USERPROFILE%
# mklink /D dataroot E:\datasets
dataset_eval:
dataro... | archai/confs/datasets/dataroot.yaml/0 | {
"file_path": "archai/confs/datasets/dataroot.yaml",
"repo_id": "archai",
"token_count": 128
} | 337 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
# Root image to be based
# Available images: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch/tags
FROM nvcr.io/nvidia/pytorch:22.10-py3
# Labels for the docker
LABEL description="NVIDIA Docker with Archai" \
repository="archa... | archai/docker/Dockerfile/0 | {
"file_path": "archai/docker/Dockerfile",
"repo_id": "archai",
"token_count": 302
} | 338 |
<jupyter_start><jupyter_text>QuickStartIn this Notebook we run Archai's [Quickstart](https://microsoft.github.io/archai/getting_started/quick_start.html) example on Azure Machine Learning. Prerequisites- Python 3.7 or later- An Azure subscription- An Azure Resource Group- An Azure Machine Learning [Workspace](https://l... | archai/docs/advanced_guide/cloud/azure/notebooks/quickstart/quickstart.ipynb/0 | {
"file_path": "archai/docs/advanced_guide/cloud/azure/notebooks/quickstart/quickstart.ipynb",
"repo_id": "archai",
"token_count": 1859
} | 339 |
<jupyter_start><jupyter_text>Training a CV-based ModelTraining a CV-based model with PyTorch-Lightning is a simplified process, where the model architecture, loss function, and training process are defined using the `LightningModule`. Archai offers a set of dataset providers to load and pre-process the data. Additional... | archai/docs/getting_started/notebooks/cv/pl_trainer.ipynb/0 | {
"file_path": "archai/docs/getting_started/notebooks/cv/pl_trainer.ipynb",
"repo_id": "archai",
"token_count": 1388
} | 340 |
<jupyter_start><jupyter_text>Training NLP-based Models with NVIDIA Defining the Model<jupyter_code>from transformers import GPT2Config, GPT2LMHeadModel
config = GPT2Config(
vocab_size=50257,
n_positions=16,
n_embd=512,
n_layer=4,
n_head=8,
embd_pdrop=0.0,
attn_pdrop=0.0,
use_cache=Fals... | archai/docs/getting_started/notebooks/nlp/nvidia_trainer.ipynb/0 | {
"file_path": "archai/docs/getting_started/notebooks/nlp/nvidia_trainer.ipynb",
"repo_id": "archai",
"token_count": 983
} | 341 |
Datasets
========
.. toctree::
:maxdepth: 2
archai.datasets.cv
archai.datasets.nlp
| archai/docs/reference/api/archai.datasets.rst/0 | {
"file_path": "archai/docs/reference/api/archai.datasets.rst",
"repo_id": "archai",
"token_count": 44
} | 342 |
Search Spaces
=============
.. toctree::
:maxdepth: 2
archai.discrete_search.search_spaces.benchmark
archai.discrete_search.search_spaces.config
archai.discrete_search.search_spaces.cv
archai.discrete_search.search_spaces.nlp
| archai/docs/reference/api/archai.discrete_search.search_spaces.rst/0 | {
"file_path": "archai/docs/reference/api/archai.discrete_search.search_spaces.rst",
"repo_id": "archai",
"token_count": 91
} | 343 |
XNAS
====
Architecture Trainer
--------------------
.. automodule:: archai.supergraph.algos.xnas.xnas_arch_trainer
:members:
:undoc-members:
Experiment Runner
-----------------
.. automodule:: archai.supergraph.algos.xnas.xnas_exp_runner
:members:
:undoc-members:
Model Description Builder
-------------... | archai/docs/reference/api/archai.supergraph.algos.xnas.rst/0 | {
"file_path": "archai/docs/reference/api/archai.supergraph.algos.xnas.rst",
"repo_id": "archai",
"token_count": 196
} | 344 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
[tool.black]
line-length = 120 | archai/pyproject.toml/0 | {
"file_path": "archai/pyproject.toml",
"repo_id": "archai",
"token_count": 29
} | 345 |
<jupyter_start><jupyter_text>How-To Evaluate a Custom Task with LM-Eval HarnessEven though `lm_eval` framework supports more than 200 tasks, one might want to implement an additional one. With that in mind, this tutorial walks through the process of creating a custom task, including it in the registry and evaluating mo... | archai/research/lm_eval_harness/tutorials/custom_task_evaluation.ipynb/0 | {
"file_path": "archai/research/lm_eval_harness/tutorials/custom_task_evaluation.ipynb",
"repo_id": "archai",
"token_count": 1837
} | 346 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
""" Script to prepare flower102 dataset for pytorch dataloader.
"""
import argparse
import os
import tempfile
from collections import defaultdict
from typing import Dict, List
from torchvision.datasets.utils import download_and_extract_archive,... | archai/scripts/supergraph/download_datasets/flower102_install.py/0 | {
"file_path": "archai/scripts/supergraph/download_datasets/flower102_install.py",
"repo_id": "archai",
"token_count": 2349
} | 347 |
from archai.common.common import common_init
from archai.supergraph.algos.nasbench101.nasbench101_dataset import Nasbench101Dataset
from archai.supergraph.datasets import data
from archai.supergraph.utils.trainer import Trainer
def main():
# 6, 7, 9, 10, 16
# model = model_builder.build(model_builder.EXAMPLE... | archai/scripts/supergraph/nasbench101/pytorch_train.py/0 | {
"file_path": "archai/scripts/supergraph/nasbench101/pytorch_train.py",
"repo_id": "archai",
"token_count": 324
} | 348 |
# Training Models with Archai
This folder contains the necessary files and instructions to train models using Archai.
## Installation
Before you can start training models, you need to install Archai. To do so, you can follow these instructions:
1. Open your terminal and run the following command:
```bash
p... | archai/scripts/trainers/README.md/0 | {
"file_path": "archai/scripts/trainers/README.md",
"repo_id": "archai",
"token_count": 914
} | 349 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import os
import json
import sys
from archai.common.store import ArchaiStore
CONNECTION_NAME = 'MODEL_STORAGE_CONNECTION_STRING'
def cleanup_stale_pods(store: ArchaiStore):
""" This script looks for kubernetes pods that are no longer runni... | archai/tasks/face_segmentation/aml/azure/cleanup_stale_pods.py/0 | {
"file_path": "archai/tasks/face_segmentation/aml/azure/cleanup_stale_pods.py",
"repo_id": "archai",
"token_count": 824
} | 350 |
<#
.SYNOPSIS
.
.DESCRIPTION
This is a handy powershell script that can cleanup old images from your azure container registry.
You can find the password in your Azure portal for the container registry under the tab named Access Keys.
.PARAMETER password
Specifies a password.
#>
param(
[Parameter(Ma... | archai/tasks/face_segmentation/aml/docker/quantizer/cleanup.ps1/0 | {
"file_path": "archai/tasks/face_segmentation/aml/docker/quantizer/cleanup.ps1",
"repo_id": "archai",
"token_count": 492
} | 351 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import os
import json
from pathlib import Path
from typing import List, Optional, Union
from overrides import overrides
from archai.discrete_search.api.archai_model import ArchaiModel
from archai.discrete_search.api.model_evaluator import AsyncMo... | archai/tasks/face_segmentation/aml/training/aml_training_evaluator.py/0 | {
"file_path": "archai/tasks/face_segmentation/aml/training/aml_training_evaluator.py",
"repo_id": "archai",
"token_count": 2468
} | 352 |
search:
search_space:
name: hgnet
params:
num_classes: 18
img_size: [256, 256] # (w, h)
in_channels: 3
op_subset: ['conv3x3', 'conv5x5', 'conv7x7']
stem_strides: [2]
# Number of downsampling blocks (without counting stem conv)
num_blocks: 5
# Maxi... | archai/tasks/face_segmentation/confs/cpu_search.yaml/0 | {
"file_path": "archai/tasks/face_segmentation/confs/cpu_search.yaml",
"repo_id": "archai",
"token_count": 393
} | 353 |
# Text Generation
At Archai, we recognize the significance of discovering the optimal neural architecture to attain the highest performance in text generation. For this purpose, we have created an advanced neural architecture search method known as the Lightweight Transformer Search (LTS). This innovative method enabl... | archai/tasks/text_generation/README.md/0 | {
"file_path": "archai/tasks/text_generation/README.md",
"repo_id": "archai",
"token_count": 2944
} | 354 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import os
from archai.common.ordered_dict_logger import OrderedDictLogger
def test_ordered_dict_logger():
# Assert that the default attributes are defined
logger = OrderedDictLogger(file_path="log.yaml", delay=0.0)
assert logger.fi... | archai/tests/common/test_ordered_dict_logger.py/0 | {
"file_path": "archai/tests/common/test_ordered_dict_logger.py",
"repo_id": "archai",
"token_count": 405
} | 355 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import numpy as np
import pytest
from overrides import overrides
from archai.discrete_search.api.predictor import MeanVar, Predictor
@pytest.fixture
def surrogate_model(search_objectives):
class DummyPredictor(Predictor):
def __ini... | archai/tests/discrete_search/algos/fixtures/surrogate_model.py/0 | {
"file_path": "archai/tests/discrete_search/algos/fixtures/surrogate_model.py",
"repo_id": "archai",
"token_count": 406
} | 356 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import pytest
from archai.discrete_search.evaluators.nlp.transformer_flex_memory import (
TransformerFlexOnnxMemory,
)
from archai.discrete_search.search_spaces.nlp.transformer_flex.search_space import (
TransformerFlexSearchSpace,
)
@... | archai/tests/discrete_search/evaluators/nlp/test_transformer_flex_memory.py/0 | {
"file_path": "archai/tests/discrete_search/evaluators/nlp/test_transformer_flex_memory.py",
"repo_id": "archai",
"token_count": 222
} | 357 |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
from archai.common import utils
class A:
def __init__(self):
self.a1 = 3.14
class B:
def __init__(self):
self.a = A()
self.i = 3
self.s = "eeee"
self.d = {"k": {"kk": 5}}
def test_state_dict()... | archai/tests/supergraph/test_state_dict.py/0 | {
"file_path": "archai/tests/supergraph/test_state_dict.py",
"repo_id": "archai",
"token_count": 257
} | 358 |
include LICENSE.txt
| azure-devops-python-api/azure-devops/MANIFEST.in/0 | {
"file_path": "azure-devops-python-api/azure-devops/MANIFEST.in",
"repo_id": "azure-devops-python-api",
"token_count": 6
} | 359 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# -------------------------------------------------------------------... | azure-devops-python-api/azure-devops/azure/devops/released/member_entitlement_management/__init__.py/0 | {
"file_path": "azure-devops-python-api/azure-devops/azure/devops/released/member_entitlement_management/__init__.py",
"repo_id": "azure-devops-python-api",
"token_count": 493
} | 360 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# -------------------------------------------------------------------... | azure-devops-python-api/azure-devops/azure/devops/released/work_item_tracking/__init__.py/0 | {
"file_path": "azure-devops-python-api/azure-devops/azure/devops/released/work_item_tracking/__init__.py",
"repo_id": "azure-devops-python-api",
"token_count": 1035
} | 361 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# -------------------------------------------------------------------... | azure-devops-python-api/azure-devops/azure/devops/v7_0/npm/npm_client.py/0 | {
"file_path": "azure-devops-python-api/azure-devops/azure/devops/v7_0/npm/npm_client.py",
"repo_id": "azure-devops-python-api",
"token_count": 14386
} | 362 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# -------------------------------------------------------------------... | azure-devops-python-api/azure-devops/azure/devops/v7_1/client_factory.py/0 | {
"file_path": "azure-devops-python-api/azure-devops/azure/devops/v7_1/client_factory.py",
"repo_id": "azure-devops-python-api",
"token_count": 8654
} | 363 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# -------------------------------------------------------------------... | azure-devops-python-api/azure-devops/azure/devops/v7_1/elastic/__init__.py/0 | {
"file_path": "azure-devops-python-api/azure-devops/azure/devops/v7_1/elastic/__init__.py",
"repo_id": "azure-devops-python-api",
"token_count": 227
} | 364 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# -------------------------------------------------------------------... | azure-devops-python-api/azure-devops/azure/devops/v7_1/file_container/file_container_client.py/0 | {
"file_path": "azure-devops-python-api/azure-devops/azure/devops/v7_1/file_container/file_container_client.py",
"repo_id": "azure-devops-python-api",
"token_count": 3019
} | 365 |
# --------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# -------------------------------------------------------------------... | azure-devops-python-api/azure-devops/azure/devops/v7_1/location/location_client.py/0 | {
"file_path": "azure-devops-python-api/azure-devops/azure/devops/v7_1/location/location_client.py",
"repo_id": "azure-devops-python-api",
"token_count": 4313
} | 366 |
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