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# ------------------------------------------------------------------------------ # DeepLabV3+ decoder. # Written by Bowen Cheng (bcheng9@illinois.edu) # ------------------------------------------------------------------------------ from collections import OrderedDict import torch from torch import nn from torch.nn im...
Cream/CDARTS/CDARTS_segmentation/segmentation/model/decoder/deeplabv3plus.py/0
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# ------------------------------------------------------------------------------ # Reference: https://github.com/facebookresearch/detectron2/blob/master/detectron2/engine/hooks.py#L195 # Modified by Bowen Cheng (bcheng9@illinois.edu) # ------------------------------------------------------------------------------ from...
Cream/CDARTS/CDARTS_segmentation/segmentation/solver/utils.py/0
{ "file_path": "Cream/CDARTS/CDARTS_segmentation/segmentation/solver/utils.py", "repo_id": "Cream", "token_count": 448 }
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from datasets.BaseDataset import BaseDataset class CamVid(BaseDataset): @classmethod def get_class_colors(*args): return [[128, 0, 0], [128, 128, 0], [128, 128, 128], [64, 0, 128], [192, 128, 128], [128, 64, 128], [64, 64, 0], [64, 64, 128], [192, 192, 128], [0, 0, 192]...
Cream/CDARTS/CDARTS_segmentation/tools/datasets/camvid/camvid.py/0
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from __future__ import division import os import sys import time import glob import json import logging import argparse from tqdm import tqdm import torch import torch.nn as nn import torch.utils import torch.nn.functional as F import torch.optim as optim import torch.distributed as dist from tensorboardX import Summa...
Cream/CDARTS/CDARTS_segmentation/tools/utils/cal_model.py/0
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from __future__ import division import os import sys import time import glob import json import logging import argparse import numpy as np import matplotlib as mpl import matplotlib.pyplot as plt import seaborn as sns import warnings; warnings.filterwarnings(action='once') class NpEncoder(json.JSONEncoder): def d...
Cream/CDARTS/CDARTS_segmentation/train/cal_model.py/0
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import torch.nn as nn import torch.nn.functional as F import torch class CrossEntropyLoss2d(nn.Module): def __init__(self, weight=None, size_average=True, ignore_index=-100): super(CrossEntropyLoss2d, self).__init__() self.nll_loss = nn.NLLLoss(weight, size_average, ignore_index) def forward(...
Cream/CDARTS/CDARTS_segmentation/train/loss.py/0
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import torch import torch.nn as nn from utils import utils from datasets import data_utils from models.loss import CrossEntropyLabelSmooth def train(train_loader, model, optimizer, epoch, writer, logger, config): device = torch.device("cuda") if config.label_smooth > 0: criterion = CrossEntropyLabelSmo...
Cream/CDARTS/benchmark201/core/pretrain_function.py/0
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""" CNN cell for network augmentation """ import torch import torch.nn as nn from lib.models import ops import lib.utils.genotypes as gt class AugmentCell(nn.Module): """ Cell for augmentation Each edge is discrete. """ def __init__(self, genotype, C_pp, C_p, C, reduction_p, reduction, bn_affine=True)...
Cream/CDARTS/lib/models/augment_cells.py/0
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# Test Workspace
Cream/Cream/experiments/workspace/test/README.md/0
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# 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 torch from ptflops import get_model_complexity_info class FlopsEst(object): def __init__(self, model, input_shape=(2, 3, 224, 224), ...
Cream/Cream/lib/utils/flops_table.py/0
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dataset_type = 'CityscapesDataset' data_root = 'data/cityscapes/' img_norm_cfg = dict( mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True) train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations', with_bbox=True), dict( type='Resize', img_scale=[(2048,...
Cream/EfficientViT/downstream/configs/_base_/datasets/cityscapes_detection.py/0
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_base_ = [ './_base_/models/mask_rcnn_efficientvit_fpn.py', './_base_/datasets/coco_instance.py', './_base_/schedules/schedule_1x.py', './_base_/default_runtime.py' ] model = dict( pretrained=None, backbone=dict( type='EfficientViT_M4', pretrained="/root/efficientvit_m4....
Cream/EfficientViT/downstream/configs/mask_rcnn_efficientvit_m4_fpn_1x_coco.py/0
{ "file_path": "Cream/EfficientViT/downstream/configs/mask_rcnn_efficientvit_m4_fpn_1x_coco.py", "repo_id": "Cream", "token_count": 634 }
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#include <c10/cuda/CUDAGuard.h> #include <torch/extension.h> #include <THC/THCAtomics.cuh> #include <vector> using index_t = int; const int HIP_MAX_GRID_NUM = 65535; const int HIP_MAX_NUM_THREADS = 512; inline int HIP_GET_NUM_THREADS(const int n) { return std::min(HIP_MAX_NUM_THREADS, ((n + 31) / 32) * 32); } in...
Cream/MiniViT/Mini-DeiT/rpe_ops/rpe_index_cuda.cu/0
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MODEL: TYPE: swin_minivit_distill NAME: swin_tiny_patch4_window7_224_minivit DROP_PATH_RATE: 0.0 SWIN: EMBED_DIM: 96 DEPTHS: [ 2, 2, 6, 2 ] NUM_HEADS: [ 3, 6, 12, 24 ] WINDOW_SIZE: 7 MINIVIT: SEPARATE_LAYERNUM_LIST: [1, 1, 1, 1]
Cream/MiniViT/Mini-Swin/configs/swin_tiny_patch4_window7_224_minivit_sharenum6.yaml/0
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import torch import torch.distributed as dist from utils import reduce_tensor class AverageMeter: """Computes and stores the average and current value""" def __init__(self): self.reset() def reset(self): self.val = 0 self.avg = 0 self.sum = 0 self.count = 0 def...
Cream/MiniViT/Mini-Swin/my_meter.py/0
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import json import logging import os import pathlib import re from copy import deepcopy from pathlib import Path from typing import Optional, Tuple import torch from .constants import OPENAI_DATASET_MEAN, OPENAI_DATASET_STD from .model import CLIP, convert_weights_to_fp16, resize_pos_embed from .openai import load_op...
Cream/TinyCLIP/src/open_clip/factory.py/0
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import torch from torch import nn import torch.nn.functional as F from collections import OrderedDict class Bottleneck(nn.Module): expansion = 4 def __init__(self, inplanes, planes, stride=1): super().__init__() # all conv layers have stride 1. an avgpool is performed after the second convol...
Cream/TinyCLIP/src/open_clip/resnet.py/0
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from torch import optim import logging class EmptyOptimizer: def __init__(self): self.param_groups = [] def step(self, *args, **kwargs): pass def state_dict(self): return dict() def load_state_dict(self, *args, **kwargs): pass def zero_grad(self): pass ...
Cream/TinyCLIP/src/training/optimizer.py/0
{ "file_path": "Cream/TinyCLIP/src/training/optimizer.py", "repo_id": "Cream", "token_count": 1798 }
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import logging from .constants import * _logger = logging.getLogger(__name__) def resolve_data_config(args, default_cfg={}, model=None, use_test_size=False, verbose=False): new_config = {} default_cfg = default_cfg if not default_cfg and model is not None and hasattr(model, 'default_cfg'): defau...
Cream/TinyViT/data/augmentation/config.py/0
{ "file_path": "Cream/TinyViT/data/augmentation/config.py", "repo_id": "Cream", "token_count": 1235 }
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""" A dataset parser that reads single tarfile based datasets This parser can read datasets consisting if a single tarfile containing images. I am planning to deprecated it in favour of ParerImageInTar. Hacked together by / Copyright 2020 Ross Wightman """ import os import tarfile from .parser import Parser from .cl...
Cream/TinyViT/data/augmentation/parsers/parser_image_tar.py/0
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"""Model Inference.""" import torch import numpy as np from PIL import Image from models.tiny_vit import tiny_vit_21m_224 from data import build_transform, imagenet_classnames from config import get_config config = get_config() # Build model model = tiny_vit_21m_224(pretrained=True) model.eval() # Load Image fname...
Cream/TinyViT/inference.py/0
{ "file_path": "Cream/TinyViT/inference.py", "repo_id": "Cream", "token_count": 299 }
331
from .multi_head_attention import RPEMultiheadAttention from . import irpe
Cream/iRPE/DETR-with-iRPE/models/rpe_attention/__init__.py/0
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""" Plotting utilities to visualize training logs. """ import torch import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt from pathlib import Path, PurePath def plot_logs(logs, fields=('class_error', 'loss_bbox_unscaled', 'mAP'), ewm_col=0, log_name='log.txt'): ''' Func...
Cream/iRPE/DETR-with-iRPE/util/plot_utils.py/0
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from __future__ import absolute_import from __future__ import division from __future__ import print_function import os.path as op import yaml from yacs.config import CfgNode as CN from lib.utils.comm import comm _C = CN() _C.BASE = [''] _C.NAME = '' _C.DATA_DIR = '' _C.DIST_BACKEND = 'nccl' _C.GPUS = (0,) # _C.LOG...
CvT/lib/config/default.py/0
{ "file_path": "CvT/lib/config/default.py", "repo_id": "CvT", "token_count": 2530 }
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from __future__ import absolute_import from __future__ import division from __future__ import print_function import torch.nn as nn import torch.optim as optim from timm.optim import create_optimizer def _is_depthwise(m): return ( isinstance(m, nn.Conv2d) and m.groups == m.in_channels and...
CvT/lib/optim/build.py/0
{ "file_path": "CvT/lib/optim/build.py", "repo_id": "CvT", "token_count": 2459 }
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import argparse import logging import os import pathlib import sr_detector import numpy as np import pandas as pd from error_messages import * from constants import * from azureml.studio.core.io.data_frame_directory import load_data_frame_from_directory, save_data_frame_to_directory PACKAGE_NAME = 'spectral_residual_a...
anomalydetector/aml_component/invoker.py/0
{ "file_path": "anomalydetector/aml_component/invoker.py", "repo_id": "anomalydetector", "token_count": 2135 }
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""" This file is referenced from https://github.com/iopsai/iops/blob/master/evaluation/evaluation.py """ import numpy as np from sklearn.metrics import f1_score, precision_score, recall_score def get_range_proba(predict, label, delay=7): predict = np.array(predict) label = np.array(label) splits = np.wh...
anomalydetector/srcnn/competition_metric.py/0
{ "file_path": "anomalydetector/srcnn/competition_metric.py", "repo_id": "anomalydetector", "token_count": 2271 }
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from abc import abstractmethod from overrides import EnforceOverrides class TrainerBase(EnforceOverrides): """Abstract class for trainers. The `TrainerBase` class provides an abstract interface for training a model. The user is re...
archai/archai/api/trainer_base.py/0
{ "file_path": "archai/archai/api/trainer_base.py", "repo_id": "archai", "token_count": 835 }
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from __future__ import annotations import itertools import logging import os import pathlib import time from collections import OrderedDict from types import TracebackType from typing import Any, Dict, List, Optional, Union import yaml from ar...
archai/archai/common/ordered_dict_logger.py/0
{ "file_path": "archai/archai/common/ordered_dict_logger.py", "repo_id": "archai", "token_count": 4092 }
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# 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 Food101 from torchvision.transforms import ToTensor from archai.api.dataset_provider import DatasetProvi...
archai/archai/datasets/cv/food101_dataset_provider.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from typing import Dict, List, Optional, Union from datasets import load_dataset as hf_load_dataset from datasets import load_from_disk as hf_load_from_disk from datasets.arrow_dataset import Dataset from datasets.dataset_dict import DatasetDict...
archai/archai/datasets/nlp/hf_dataset_provider.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import random from pathlib import Path from typing import List, Optional from overrides import overrides from archai.common.ordered_dict_logger import OrderedDictLogger from archai.discrete_search.api.archai_model import ArchaiModel from archai...
archai/archai/discrete_search/algos/random_search.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from typing import List, Optional from overrides import overrides from torch import nn from archai.discrete_search.api.archai_model import ArchaiModel from archai.discrete_search.api.model_evaluator import ModelEvaluator class NonEmbeddingPar...
archai/archai/discrete_search/evaluators/nlp/parameters.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import random import re import warnings from pathlib import Path from typing import Any, List, Optional import nats_bench import numpy as np import torch import yaml from overrides import overrides from archai.discrete_search.api.archai_model i...
archai/archai/discrete_search/search_spaces/benchmark/natsbench_tss.py/0
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# coding=utf-8 # Copyright 2020 The Trax Authors and The HuggingFace Inc. team. # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at...
archai/archai/discrete_search/search_spaces/nlp/tfpp/ops/lsh_utils/modeling_reformer.py/0
{ "file_path": "archai/archai/discrete_search/search_spaces/nlp/tfpp/ops/lsh_utils/modeling_reformer.py", "repo_id": "archai", "token_count": 26144 }
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from typing import Union, Tuple, Optional import numpy as np from archai.discrete_search.search_spaces.config import ( ArchParamTree, repeat_config, ConfigSearchSpace, DiscreteChoice ) from .model import LanguageModel from .ops import OPS from .utils import get_attn_head_simplex def to_tuple(x: Union[Tuple[i...
archai/archai/discrete_search/search_spaces/nlp/tfpp/search_space.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import copy from typing import Optional, Tuple import torch from archai.quantization.qat import prepare_with_qat class MixedQAT(torch.nn.Module): """Mixed QAT (Quantization-Aware Training) model, which can be fine-tuned using a linear...
archai/archai/quantization/mixed_qat.py/0
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# 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.darts.mixed_op import MixedOp from archai.supergraph.nas.model_desc import ( CellType, ConvM...
archai/archai/supergraph/algos/darts/darts_model_desc_builder.py/0
{ "file_path": "archai/archai/supergraph/algos/darts/darts_model_desc_builder.py", "repo_id": "archai", "token_count": 1076 }
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from typing import Optional import torch import torch.nn.functional as F 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 impor...
archai/archai/supergraph/algos/gumbelsoftmax/gs_arch_trainer.py/0
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import logging from typing import List import torch from torch import nn from archai.common import ml_utils from archai.supergraph.algos.nasbench101.model import Network from archai.supergraph.algos.nasbench101.model_spec import ModelSpec EXAMPLE_VERTEX_OPS = ['input', 'conv1x1-bn-relu', 'conv3x3-bn-relu', 'conv3x3-...
archai/archai/supergraph/algos/nasbench101/model_builder.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from overrides import overrides from archai.supergraph.algos.random.random_model_desc_builder import ( RandomModelDescBuilder, ) from archai.supergraph.nas.arch_trainer import TArchTrainer from archai.supergraph.nas.exp_runner import Experim...
archai/archai/supergraph/algos/random/random_exp_runner.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import os 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 ( Dat...
archai/archai/supergraph/datasets/providers/aircraft_provider.py/0
{ "file_path": "archai/archai/supergraph/datasets/providers/aircraft_provider.py", "repo_id": "archai", "token_count": 1104 }
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import os from collections import OrderedDict import torch import torch.nn as nn import torch.nn.functional as F __all__ = ['DenseNet', 'densenet121', 'densenet169', 'densenet201', 'densenet161'] class _DenseLayer(nn.Sequential): def __init__(self, num_input_features, growth_rate, bn_size, drop_rate): su...
archai/archai/supergraph/models/densenet.py/0
{ "file_path": "archai/archai/supergraph/models/densenet.py", "repo_id": "archai", "token_count": 3535 }
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from abc import ABC from typing import Iterable, Iterator, Optional, Tuple from overrides import EnforceOverrides from torch import nn from archai.supergraph.nas.arch_params import ArchParams, NNTypes class ArchModule(nn.Module, ABC, EnforceO...
archai/archai/supergraph/nas/arch_module.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from typing import Optional, Tuple from graphviz import Digraph from archai.common.ordered_dict_logger import get_global_logger from archai.common.utils import first_or_default from archai.supergraph.nas.model_desc import CellDesc, CellType, Mo...
archai/archai/supergraph/nas/vis_model_desc.py/0
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# Copyright (c) 2019-2020, NVIDIA CORPORATION. # Licensed under the Apache License, Version 2.0. # https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/LanguageModeling/Transformer-XL/pytorch/lamb.py # # Copyright (c) 2019 cybertronai. # Licensed under the MIT license. from typing import Iterable, Option...
archai/archai/trainers/lamb_optimizer.py/0
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__include__: "darts.yaml" # just use darts defaults nas: eval: loader: train_batch: 96 search: loader: val_ratio: 0.0 # don't need val during search in gs trainer: epochs: 1 model_desc: max_final_edges: 1 cell: gs: num_sample: 1
archai/confs/algos/gs.yaml/0
{ "file_path": "archai/confs/algos/gs.yaml", "repo_id": "archai", "token_count": 147 }
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autoaug: model: type: pyramid depth: 272 alpha: 200 bottleneck: True loader: aug: fa_reduced_cifar10 cutout: 16 batch: 64 epochs: 1800 lr_schedule: type: 'cosine' optimizer: type: sgd lr: 0.05 nesterov: True decay: 0.00005
archai/confs/aug/pyramid272_cifar10_b64.yaml/0
{ "file_path": "archai/confs/aug/pyramid272_cifar10_b64.yaml", "repo_id": "archai", "token_count": 138 }
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import os import json from glob import glob from IPython.display import display, Image from shutil import copyfile, rmtree from archai.common.store import ArchaiStore def get_results(store : ArchaiStore, blob_path, output_folder): """ Fetch ...
archai/docs/advanced_guide/cloud/azure/notebooks/multi_node_search/scripts/utils.py/0
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Computer Vision =============== .. toctree:: :maxdepth: 2 Dataset Provider <cv/cv_dataset_provider.ipynb> PyTorch-Lightining Trainer <cv/pl_trainer.ipynb>
archai/docs/getting_started/notebooks/cv.rst/0
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<jupyter_start><jupyter_text>Creating NLP-based DataIn this notebook, we will use a dataset provider-based abstraction that interfaces with Hugging Face's `datasets`. Such a library provides access to a large number of NLP-based datasets, including text classification, question-answering, and language modeling, among o...
archai/docs/getting_started/notebooks/nlp/hf_dataset_provider.ipynb/0
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Transforms ========== Brightness ---------- .. automodule:: archai.datasets.cv.transforms.brightness :members: :undoc-members: Custom Cutout ------------- .. automodule:: archai.datasets.cv.transforms.custom_cutout :members: :undoc-members: Lighting -------- .. automodule:: archai.datasets.cv.transfor...
archai/docs/reference/api/archai.datasets.cv.transforms.rst/0
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Natural Language Processing =========================== .. toctree:: :maxdepth: 2 archai.discrete_search.search_spaces.nlp.tfpp archai.discrete_search.search_spaces.nlp.transformer_flex
archai/docs/reference/api/archai.discrete_search.search_spaces.nlp.rst/0
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Petridish ========= Evaluater --------- .. automodule:: archai.supergraph.algos.petridish.evaluater_petridish :members: :undoc-members: Experiment Runner ----------------- .. automodule:: archai.supergraph.algos.petridish.petridish_exp_runner :members: :undoc-members: Model Description Builder --------...
archai/docs/reference/api/archai.supergraph.algos.petridish.rst/0
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Contact ======= If you have any questions or feedback about the Archai project or the open problems in Neural Architecture Search (NAS), please feel free to contact us using the following information: * Email: archai@microsoft.com * Website: https://github.com/microsoft/archai/issues We welcome any questions, feedba...
archai/docs/support/contact.rst/0
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# Copyright (c) EleutherAI. # Licensed under the MIT license. # https://github.com/EleutherAI/lm-evaluation-harness/blob/master/main.py from __future__ import annotations from typing import Any, Optional REQUEST_RETURN_LENGTHS = { "generate": None, "greedy_until": None, "loglikelihood": 2, "loglikeli...
archai/research/lm_eval_harness/lm_eval_harness/utils/request_factory.py/0
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set -e -o xtrace bash dist_main.sh --full --no-search --algos darts --datasets cifar10 --nas.eval.final_desc_filename confs/darts_modelsdarts_genotype.yaml --common.apex.min_world_size 2 --nas.eval.trainer.apex.enabled True
archai/scripts/supergraph/dist_test.sh/0
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import logging import statistics from archai.supergraph.algos.nasbench101.nasbench101_dataset import Nasbench101Dataset def main(): logging.getLogger().setLevel(logging.DEBUG) # create dataset nsds = Nasbench101Dataset("~/dataroot/nasbench_ds/nasbench_full.pkl") vars = [ statistics.variance...
archai/scripts/supergraph/nasbench101/bad_data.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import argparse import os import pathlib import subprocess import sys try: from runstats import Statistics except: subprocess.check_call([sys.executable, '-m', 'pip', 'install', 'runstats']) from runstats import Statistics def main...
archai/scripts/supergraph/reports/old_logs.py/0
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[flake8] ignore = E111,E402,E722,W503,W504,F405,F403 max-line-length = 120
archai/tasks/face_segmentation/aml/.flake8/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import argparse import os import sys from archai.common.store import ArchaiStore CONNECTION_NAME = 'MODEL_STORAGE_CONNECTION_STRING' def upload(con_str, experiment_name, args): parser = argparse.ArgumentParser(description='Upload a named mo...
archai/tasks/face_segmentation/aml/azure/upload.py/0
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conda activate snap pushd $SNPE_ROOT source bin/envsetup.sh -o ~/anaconda3/envs/snap/lib/python3.6/site-packages/onnx popd
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from typing import Optional, List, Dict import torch @torch.no_grad() def get_confusion_matrix(pred_labels: torch.LongTensor, true_labels: torch.LongTensor, num_labels: int, ignore_index: int = 255) -> torch.LongTensor: pred_labels, true_labels = pred_labels.view(...
archai/tasks/face_segmentation/training/metrics.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import csv import subprocess """Train the models that are in the pareto front""" # Please change the following variables to your own path data_dir = "face_synthetics/dataset_100000" output_dir = "./output" csv_file = "search_results.csv" # Rea...
archai/tasks/facial_landmark_detection/train_candidate_models.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import os from archai.common.config import Config def test_config(): # Asserts that it can load keys from a YAML file config_filepath = "config.yaml" with open(config_filepath, "w") as f: f.write("test_key: test_value") ...
archai/tests/common/test_config.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import pytest from overrides import overrides from archai.datasets.nlp.tokenizer_utils.token_config import SpecialTokenEnum from archai.datasets.nlp.tokenizer_utils.tokenizer_base import TokenizerBase @pytest.fixture def tokenizer_base(): ...
archai/tests/datasets/nlp/tokenizer_utils/test_tokenizer_base.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. from overrides import overrides from archai.discrete_search.api.search_results import SearchResults from archai.discrete_search.api.searcher import Searcher class MySearcher(Searcher): def __init__(self) -> None: super().__init__()...
archai/tests/discrete_search/api/test_searcher.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import pytest import torch from transformers import PretrainedConfig from archai.onnx.config_utils.gpt2_onnx_config import GPT2FlexOnnxConfig, GPT2OnnxConfig @pytest.fixture def dummy_config_gpt2(): class DummyConfig(PretrainedConfig): ...
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import torch from archai.quantization.quantizers import FakeDynamicQuant def test_fake_dynamic_quant(): x = torch.randn(4) # Assert the quint8 quantization type with 8-bit fake_quant = FakeDynamicQuant(dtype=torch.quint8, bits=8) ...
archai/tests/quantization/test_quantizers.py/0
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# Copyright (c) Microsoft Corporation. # Licensed under the MIT license. import pytest import torch from archai.trainers.lamb_optimizer import JITLamb, Lamb def test_lamb_init(): # Assert default parameter values lamb = Lamb([torch.randn(10, 5)]) assert lamb.param_groups[0]["lr"] == 1e-3 assert lamb...
archai/tests/trainers/test_lamb_optimizer.py/0
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[![Python package](https://github.com/microsoft/azure-devops-python-api/workflows/Python%20package/badge.svg)](https://github.com/microsoft/azure-devops-python-api/actions) [![Python](https://img.shields.io/pypi/pyversions/azure-devops.svg)](https://pypi.python.org/pypi/azure-devops) # Azure DevOps Python API This re...
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # 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/build/__init__.py/0
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # 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/pipelines_checks/__init__.py/0
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# -------------------------------------------------------------------------------------------- # 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/provenance/models.py/0
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# -------------------------------------------------------------------------------------------- # 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/security/security_client.py/0
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # 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/work_item_tracking_process/__init__.py/0
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# -------------------------------------------------------------------------------------------- # 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/cix/__init__.py/0
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# -------------------------------------------------------------------------------------------- # 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/dashboard/__init__.py/0
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# -------------------------------------------------------------------------------------------- # 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/feed/feed_client.py/0
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# -------------------------------------------------------------------------------------------- # 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/identity/identity_client.py/0
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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# -------------------------------------------------------------------------------------------- # 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/service_endpoint/service_endpoint_client.py/0
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# -------------------------------------------------------------------------------------------- # 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/test/models.py/0
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# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------...
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@REM init section. Set _echo=1 to echo everything @IF NOT DEFINED _echo ECHO OFF IF EXIST "%BUILD_BINARIESDIRECTORY%\python.3.6.2\tools\python.exe" ( REM Build step installs Python here. SET PYTHONEXE=%BUILD_BINARIESDIRECTORY%\python.3.6.2\tools\python.exe ) ELSE ( SET PYTHONEXE=python.exe ) "%PYTHONEXE%"...
azure-devops-python-api/scripts/windows/sdist.cmd/0
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# coding=utf-8 ## # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. ## from ._chained import * from ._default import _DefaultAzureCredential from ._token import _TokenFileCredential
azure-quantum-python/azure-quantum/azure/quantum/_authentication/__init__.py/0
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# ------------------------------------ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ """Customize generated code here. Follow our quickstart for examples: https://aka.ms/azsdk/python/dpcodegen/python/customize """ from typing import List __all__: List[...
azure-quantum-python/azure-quantum/azure/quantum/_client/operations/_patch.py/0
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## # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. ## import re import abc from typing import Optional from datetime import date, datetime, timezone from azure.quantum._client.models import JobStatus class FilteredJob(abc.ABC): """ Mixin for adding methods to fi...
azure-quantum-python/azure-quantum/azure/quantum/job/filtered_job.py/0
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"""Defines targets and helper functions for the Pasqal provider""" ## # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. ## __all__ = [ "InputParams", "Pasqal", "PasqalTarget", ] from dataclasses import dataclass from enum import Enum from typing import Union, A...
azure-quantum-python/azure-quantum/azure/quantum/target/pasqal/target.py/0
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{ "arguments": [ { "name": "bitwidth", "value": 32, "type": "Int" } ] }
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namespace QSharpBellState { open Microsoft.Quantum.Intrinsic; operation BellState_File() : (Result,Result) { use q0 = Qubit(); use q1 = Qubit(); H(q0); CNOT(q0, q1); return (M(q0), M(q1)); } }
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