sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5c9be7c66dc10eaff05b4281c81ffaf195263b5e29cda15db368afa3bbd21b49 | Python | 6,434 | 176 | import torch
import torch.nn as nn
import copy
import numpy as np
from scipy.io import mmread
from scipy.io import mmwrite
from sys import getsizeof
# user specificed dataset name vector used to train autoencoder and impute
datasets = ['jurkat', 'monocyte','mbrain','pbmc','lymphoma','293t','bmmc','human_mix',... |
74bfc85bc20ec52be599d25f5f61a24bec1af1b036e8615ecc54f643c582de83 | Python | 6,434 | 190 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from __future__ import annotations
from dataclasses import asdict
import pytest
from torch import eye, ones, randn_like, tensor, zeros
from torch.distri... |
be5b78dc7c590285f3bab9618c6dde7bdeb804907d547975c53f9f41d89a09b9 | Python | 6,444 | 163 | # -*- coding: utf-8 -*-
"""
Created on Wed Jun 16 15:13:25 2021
@author: fhu14
Module for visualizing information stored in the loss tracker framework
"""
#%% Imports, definitions
import pickle
import numpy as np
Array = np.ndarray
import os
import matplotlib.pyplot as plt
from matplotlib.ticker import AutoMinorLoca... |
0764761a79fbcd8dc0856dfef63c2420c0bac68d701dcf4dd3c4a9c4b60f4f98 | Python | 6,450 | 210 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import mmcv
import numpy as np
import pytest
import torch
from mmpose.apis import (extract_pose_sequence, inference_interhand_3d_model,
inference_mesh_model, inference_pose_lifter_model,
... |
437085d121eb2ea8fba7579e815c27ea7a0ab0048fc914777064fb6423bf50cb | Python | 6,450 | 226 | _base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/panoptic_body3d.py'
]
checkpoint_config = dict(interval=1)
evaluation = dict(interval=1, metric='mAP', save_best='mAP')
optimizer = dict(
type='Adam',
lr=0.0001,
)
optimizer_config = dict(grad_clip=None)
# learning policy
... |
944586ed09e89c4d4adfaa6972f55cfedf3ea8190475e75011d4881c016df96f | Python | 6,460 | 168 | import os
import sys
import pandas as pd
# from shutil import rmtree
import numpy as np
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit.Geometry import Point3D
# from rdkit.Chem.Draw.IPythonConsole import drawMol3D
from ppqm import XtbCalculator
import psi4
import time
from datetime import datetime
f... |
e1bc4fcd947703f4e528b2bd12051ca959b075c34c9563096aef366df0198b3e | Python | 6,460 | 184 | # Copyright (C) 2022-2025 ETH Zurich, Marc Lehner and other DASH contributors.
from typing import Tuple, Union
import numpy as np
import pandas as pd
from numba import njit
from serenityff.charge.tree.atom_features import AtomFeatures
from serenityff.charge.tree_develop.develop_node import DevelopNode
from sereni... |
426f1fe6c0938d82680054a78e1cd84a0b6dfe3745120b848fef3759eadc8d8f | Python | 6,461 | 171 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmcv.ops.nms import batched_nms
from mmdet.core.bbox.iou_calculators import bbox_overlaps
def multiclass_nms(multi_bboxes,
multi_scores,
score_thr,
nms_cfg,
max_num=-1,
... |
eef6797a1e8dbd5715f5dffc47dfc65e1196ef7d639b272549d9003b2b14f092 | Python | 6,461 | 110 | import os
import time
import json
from pathlib import Path
import pandas as pd
import numpy as np
import calendar
from A_config import a10_config
from B_preprocess import b100_load
from D_modelling import d100_modeller
from F_post_processsing import F110_process_opeForecast_output
import manager_0_user_params as upar
... |
3bbfa303ee13e1413c952510167e70eefceb183eec9aaa04a81ca61d3b599241 | Python | 6,463 | 168 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
from __future__ import annotations
import torch
from torch import Tensor, nn
from sbi.neural_nets.estimators.base import ConditionalEstimator
class Ra... |
9a1aa57e4adc0dfdeefe40d650e64b55bc95de1d78373770244a18196fc2e0ba | Python | 6,463 | 173 | from tensorflow.keras.layers import Layer
from tensorflow.keras import initializers
import tensorflow as tf
# https://stackoverflow.com/questions/65195956/keras-custom-batch-normalization-layer-with-an-extra-variable-that-can-be-change
# https://github.com/dksakkos/BatchNorm/blob/main/BatchNorm.py
@tf.keras.utils.reg... |
ae5c781b7f3a7aa9ecb36e1e995fb7a1214931e4ac70d2bdc065fa2adebfc061 | Python | 6,463 | 145 | import os
os.environ['FOR_DISABLE_CONSOLE_CTRL_HANDLER'] = '1'
import hane
import tools
import pickle
import glob
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
def parse_args():
parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter,
conflict_handler=... |
7a76774634e8d86818cdf1f10ff0d0b763552ff51b2bebdd8f2171108264ea91 | Python | 6,464 | 193 | # Copyright (c) OpenMMLab. All rights reserved.
import os
import warnings
from argparse import ArgumentParser
import cv2
import mmcv
from mmpose.apis import (collect_multi_frames, inference_top_down_pose_model,
init_pose_model, process_mmdet_results,
vis_pose_result)
... |
f4e629b813562eff03817f7214407eadcd9d196378965d4e8863c27784a51b11 | Python | 6,464 | 151 | import logging
import os
import h5py
import numpy as np
import torch
import torch.utils.data as data
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
client_ids_train = None
client_ids_test = None
DEFAULT_TRAIN_CLIENTS_NUM = 3400
DEFAULT_TEST_CLIENTS_NUM = 3400
DEFAULT_BATCH_SIZE = 20... |
585189aedb8eafa2dbd65c37309ec625a0860bca6bdb32a13edf695a36ce3492 | Python | 6,465 | 136 | import numpy as np
import imageio
import os
import time
import torch
from torch.utils.data import DataLoader
from torch.utils.data.distributed import DistributedSampler
from data import set_up_data
from utils import get_cpu_stats_over_ranks
from train_helpers import set_up_hyperparams, load_vaes, load_opt, accumulate_s... |
4d45ea652c5a9444abd40fd755c563adaaaf4fc7da76ac42dfbaa4cb57ef7698 | Python | 6,469 | 174 | from jax import lax
import jax.numpy as jnp
from functools import partial
from einshape import jax_einshape as einshape
from collections import namedtuple
import jax
jax.config.update("jax_enable_x64", True)
def tridiagonal_solve(dl, d, du, b):
"""Pure JAX implementation of `tridiagonal_solve`."""
prepend_zero =... |
b13b6169076c72c0e04a0e8f31cb39cea4b1b2fda3ac77851c9ce8580f281913 | Python | 6,471 | 167 | import logging
import torch.utils.data as data
import numpy as np
import h5py
import os
from .data_utility import init_transform, count_samples, build_pairs
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def get_transforms():
transforms_train = ["Resize", "RandomCrop", "Rando... |
0c9cdf9d89d1e1af7558e6d512e50f95946867e6a7f6f97f9dd1357e036d0855 | Python | 6,479 | 139 | from collections import namedtuple
def make_list(length, prefix):
return [f'{prefix} {i}' for i in range(length)]
our_atoms = ['B', 'C', 'N', 'O', 'F', 'P', 'S', 'Cl', 'Br', 'I', 'other']
our_neighs = make_list(6, 'N') # max 5 neighbours
our_hydro = make_list(5, 'H') # max 4 hydrogens
charge = 'charge'
ringne... |
78643bfa42851af4b3351a8a1c6784d309c53337c5e9cd7c2cbd662911f102a2 | Python | 6,481 | 164 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from mmdet.core.mask import BitmapMasks, PolygonMasks
from mmdet.datasets.builder import PIPELINES
from .utils import check_result_same, construct_toy_data
def test_shear():
# test ... |
04910608f0084639a48b22fd074f7ef81c061f00565c1342dc24f11ed7c93bfd | Python | 6,483 | 186 | # Copyright (c) OpenMMLab. All rights reserved.
import time
import uuid
import warnings
from typing import Callable, Dict, List, Optional
import numpy as np
Filter = Callable[[Dict], bool]
class Message():
"""Message base class.
All message class should inherit this class. The basic use of a Message
in... |
3d6e751825b736325299a3026ff27361651a80e0b5227da4d297eac0ae5ec66b | Python | 6,487 | 197 | from p4.p4exceptions import P4Error
from p4.tree import Tree
from p4.nexus import Nexus
from p4.var import var
import sys
import os
import string
import io
import copy
class TreeFileLite(object):
"""Get trees in big files without reading the lot into memory.
P4 Tree objects are a little obese, and large tr... |
9b405772463412bab8ed532747c42a0000215c92dc20ef800ae72772c4703192 | Python | 6,489 | 194 | # -*- coding: utf-8 -*-
"""Upsampling module.
This code is modified from https://github.com/r9y9/wavenet_vocoder.
"""
import numpy as np
import torch
import torch.nn.functional as F
from parallel_wavegan.layers import Conv1d
class Stretch2d(torch.nn.Module):
"""Stretch2d module."""
def __init__(self, x_... |
e40dbe35d3b868832b2c0c8d8839b162d1d59c0543c86373b89dfe2fa122e87b | Python | 6,489 | 153 | import pandas as pd
from A_config import a10_config
import os
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from F_post_processsing import F100_analyze_hindcast_output
"""
Compare two results (e.g. without SF vs with SF)
"""
# configuration files and run names
baseDir = r'... |
50d8034609d890a19d309ab53fb0914db8752bd7d70291f504ed48b8e856fca5 | Python | 6,498 | 230 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 28 16:49:14 2021
@author: baris
"""
from pydentate import neuron_tools
from grid_model import grid_simulate
import shelve
import copy
import time
import numpy as np
from pydentate_integrate import granule_simulate
import os
import glob
"""Setup""... |
7e0baf85be3e7224e26a92a28ed584d6d686c4dd69def87eb220bee86fcbbedf | Python | 6,502 | 188 | from torchmdnet.priors.base import BasePrior
from torchmdnet.models.utils import Distance
import torch as pt
from torch_scatter import scatter
class D2(BasePrior):
"""Dispersive correction term as used in DFT-D2
Reference
---------
Grimme, Stefan. "Semiempirical GGA-type density functional constructe... |
a693fe9da6769126d99080a9e7058a98c1790468ee9604542c30dd63463aee67 | Python | 6,505 | 161 | # -*- coding: utf-8 -*-
"""
Created on Tue Apr 26 23:30:09 2022
@author: fhu14
Module for handling table-level operations for computing deltas and other
elements. This will take advantage of pandas functionality. Dictionaries
will be generated from the json files that output files are parsed into
"""
#%% Imports, de... |
13d6de885bd55de8b403aed1c02fa207bbe3ea3f067914348d56ce5c46523213 | Python | 6,507 | 137 | ############################################
# Imports
############################################
import os
from oligo_designer_toolsuite._exceptions import ConfigurationError
from oligo_designer_toolsuite.database import OligoDatabase, ReferenceDatabase
from oligo_designer_toolsuite.oligo_specificity_filter import... |
cb4896f9ee879335ba127274c7043e54393351c0beb7adf10a8ee05b636797a3 | Python | 6,517 | 188 | import torch
import torch.nn as nn
from models.resnet import resnet18, resnet50, resnet101
from functools import partial
from utils.constants import DEVICE, FC_DIM, NUM_CLASSES
class SegmentationModule(nn.Module):
"""
Segmentation Module class
"""
def __init__(self, net_encoder, net_decoder):
... |
25b47cd733be2c7d813935c3a0885c5e970da04e8a3634e8b6263471fd3f6dc9 | Python | 6,520 | 188 | import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import seaborn as sns
def plot_val_test_predictions(df_val_, df_test_, av_rmse_val_, r2s_val_, av_rmse_test_, r2s_test_,
xlabels_, ylabels_, filename_val='', filename_test=''):
axes_min = np.floor(np.min(df_val_[:... |
406c8b3c4ea31bd42f5e2e0733e6264a22632478fcd013ae6b0904b90237709d | Python | 6,521 | 158 | import sys
sys.path.append("./")
import time
import traceback
import os
import gc
import time
import traceback
import h5py
import numpy as np
import pandas as pd
from allensdk.core.brain_observatory_cache import BrainObservatoryCache
from allensdk.brain_observatory.brain_observatory_exceptions import EpochSeparatio... |
938d01083d2bd84568ff50fafca056d3292040991a335e78a8058913716a34ba | Python | 6,525 | 201 | # Copyright (c) OpenMMLab. All rights reserved.
import mmcv
import numpy as np
import pytest
import torch
from mmpose.models import build_posenet
def _create_inputs(joint_num_in,
joint_channel_in,
joint_num_out,
joint_channel_out,
seq_len,
... |
61dea247dc755caf108bcc85f0f843624949beaa37ab278a553b07cc45bba16a | Python | 6,527 | 201 | import os
import os.path
import torch.utils.data as data
from PIL import Image
def has_file_allowed_extension(filename, extensions):
"""Checks if a file is an allowed extension.
Args:
filename (string): path to a file
Returns:
bool: True if the filename ends with a known image extension... |
b2cd981d609a76b6a2d9aa03ae7ebf391accd1a3daf15944c709f3cc7a0adb25 | Python | 6,530 | 182 | """test_merge_layers.py
This file is part of the test suite for keras2c
Implements tests for merge layers
"""
#!/usr/bin/env python3
import unittest
from tensorflow import keras
from keras2c import keras2c_main
import time
from test_core_layers import build_and_run
__author__ = "Rory Conlin"
__copyright__ = "Copyrig... |
e840c6531555cb71c6260e51f87fb62a3d1035b3b08c52203a2ddd649ee3c7ec | Python | 6,530 | 180 | _base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/h36m.py'
]
evaluation = dict(interval=10, metric=['mpjpe', 'p-mpjpe'], save_best='MPJPE')
# optimizer settings
optimizer = dict(
type='Adam',
lr=1e-3,
)
optimizer_config = dict(grad_clip=None)
# learning policy
lr_config =... |
741bc0e74c57c5fb641ffdde29612a26ec62ffaa1513954f384937761b77727d | Python | 6,532 | 136 | import pandas as pd
import numpy as np
import os
import glob
import matplotlib.pyplot as plt
from utils.processSuite2pOutput import correct_suite2p_outputs
class Run:
def __init__(self, summary, exp_id):
self.fishID = summary.fishlabel[exp_id]
self.runID = summary.run[exp_id]
self.date = ... |
952b64e02ed9728736c716605b46ff2eff793f841dba1c2a9f463004dfad9a5a | Python | 6,535 | 164 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import warnings
from mmcv.cnn import VGG
from mmcv.runner.hooks import HOOKS, Hook
from mmdet.datasets.builder import PIPELINES
from mmdet.datasets.pipelines import LoadAnnotations, LoadImageFromFile
from mmdet.models.dense_heads import GARPNHead, RPNHead
fr... |
18f2c1646f5cfe4135e9df66857782bf2a0b47e95eb4b0f7e81b8071e991dbdf | Python | 6,538 | 133 |
random_seed = 234
from utils.rnd import set_random_seeds
set_random_seeds(random_seed = random_seed)
from pipeline.crossvalidation_pipeline import CrossvalidationPipeline
from pipeline.one_split import OneSplitPipeline
from utils.logs import set_logging
import logging
import datetime
import imp
import os
import sys
... |
740e27b8c1e5bce5886c43e870757e1cf3d1d09fcc6fd5d633e9dd7f05488b17 | Python | 6,540 | 118 | """
Run the postprocessing from Shiva on arbitrary input data.
Typically expects a binarised cluster mask (from some predictor), a brain parcellation (or mask),
and the type of prediction corresponding to the cluster mask (e.g. WMH, PVS, CMB, LAC).
The postprocessing will then compute the different statistics for the c... |
e5297740637fada4b0402bdda5db4e5ec4c78afc303c1e365968d94df0cffb07 | Python | 6,549 | 170 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
"""Run labels, results files and the results table of mini SBIBM."""
import re
import subprocess
from pathlib import Path
from typing import Callable
fro... |
2d9b6e4b74c8f2bd1ac0fb014845923a299580cea7cbbf1312b8e2218c70e649 | Python | 6,550 | 214 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Variable
from torch.nn.parameter import Parameter
import math
import utils
import argparse
import data_loader
from ipdb import set_trace
from sklearn import metrics
SEQ_LEN = 48
def binary_cros... |
85adc1e361c3975c2f6854cb513bcccb89c416a21cb1bb6dd1fe293f21d15349 | Python | 6,561 | 175 | import os
import numpy as np
from os.path import join, exists
from sklearn import metrics
from config_path import PLOTS_PATH
from matplotlib import pyplot as plt
from sklearn.metrics import confusion_matrix
from paper_analysis_revision2.plot_utils import plot_auc_all, plot_auc_bootstrap, plot_prc_all, plot_confusion_m... |
7e99990a8b8543868f73b842d7f78e6feca2d9c40882d9e4d7f7dae4755b2c5c | Python | 6,567 | 185 | # Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
import tempfile
import warnings
from collections import defaultdict
import json_tricks as json
import numpy as np
from mmcv import Config
from ...builder import DATASETS
from .gesture_base_dataset import GestureBaseDataset
@DATASETS.reg... |
4d2014a47d1c4023fc455f8d597a75680448e34c657a6b6901b0f2a0d43d9ea3 | Python | 6,568 | 163 | # Copyright (c) OpenMMLab. All rights reserved.
import math
import torch
import torch.nn as nn
from mmcv.cnn.bricks.transformer import POSITIONAL_ENCODING
from mmcv.runner import BaseModule
@POSITIONAL_ENCODING.register_module()
class SinePositionalEncoding(BaseModule):
"""Position encoding with sine and cosine ... |
3e63406e795fb87ebf8f42c4bba23079577bf62f08626be209f3caa3a86d4a35 | Python | 6,576 | 203 | from multiprocessing import shared_memory
import random
import pickle
import time
import copy
import torch
import torch.distributed as dist
from lib.cfg_holder import cfg_unique_holder as cfguh
def singleton(class_):
instances = {}
def getinstance(*args, **kwargs):
if class_ not in instances:
... |
4808ba81e11e5acfe24ef33bb4dcc25b4b538c1e6d2f448941f01a0c3ab78e3e | Python | 6,576 | 168 | """
This Python script packages the eye tracking data into `BASE_DIR`.
`BASE_DIR` can be supplied in the argumemts: e.g., python package_eye_data.py /path/to/target/dir
Specifically, it generates the following file structure (inside the target directory):
`BASE_DIR`/data/[...].npy: Stores .npy files for eye tracki... |
f67f1cb407405ccd864a224b0b3611994a28c470ad85cc655f4de9a26bcd3a54 | Python | 6,577 | 158 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.ops.merge_cells import GlobalPoolingCell, SumCell
from mmcv.runner import BaseModule, ModuleList
from ..builder import NECKS
@NECKS.register_module()
class NASFPN(BaseModule):
"""NAS-FPN.
Implemen... |
011039991d2ad56564dcff7bf3f922b10b1d14f40d9501d9b88d67c03cb5df46 | Python | 6,580 | 144 | """Sample splitting for DoubleML models with independent or clustered observations."""
from abc import abstractmethod
from doubleml.utils._checks import _check_sample_splitting
from doubleml.utils.resampling import DoubleMLClusterResampling, DoubleMLDoubleResampling, DoubleMLResampling
class SampleSplittingMixin:
... |
6e5cc9d0d1d381e662e0b795e8c4cda7ed7c46dd3f74cd625b391e695de4b34c | Python | 6,585 | 188 | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch.nn as nn
from .. import builder
from ..builder import POSENETS
from .base import BasePose
try:
from mmcv.runner import auto_fp16
except ImportError:
warnings.warn('auto_fp16 from mmpose will be deprecated from v0.15.0'
... |
ca43e2513d528ed2ba1142ada98c1467e5257926dde35ce4051f4e9526e7f5bf | Python | 6,590 | 235 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 28 16:49:14 2021
@author: baris
"""
from pydentate import neuron_tools
from grid_model import grid_simulate
import shelve
import copy
import time
import numpy as np
from pydentate_integrate import granule_simulate
import os
import glob
start = ti... |
a6ce93919d609ad04e8134a84d4b0f263ffa7d8610aff79103e0478819c6cd7c | Python | 6,591 | 169 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule, caffe2_xavier_init
from mmcv.ops.merge_cells import ConcatCell
from mmcv.runner import BaseModule
from ..builder import NECKS
@NECKS.register_module()
class NASFCOS_FPN(BaseModule):
... |
f132c79ddd2d7628c51495e63fe3310d58d3e7a3114fc1c52afe90dadde4fdf7 | Python | 6,594 | 117 | # -*- coding: utf-8 -*-
import yaml
def caption_parse_rules(offset,position_key,separate,char_type,char_num):
"""
Create matching rules and based on custom characteristics of caption text described in input vars
:param offset: characters used to set off material that is amplifying or explanatory
:para... |
9612413c65b6f1cb6572a3a5f3f05bc9c4a6002c3c371b736d2bf59e64e668a7 | Python | 6,595 | 178 | import os
import numpy as np
from scipy.interpolate import InterpolatedUnivariateSpline
# interface
class SkfInfo(object):
def __init__(self, name, paramPath):
elem1, elem2 = name.split('-')
self.__homo = (elem1 == elem2)
self.name = name
with open(os.path.join(paramPath, name + '... |
bed290cf791d0659abbdd687b2f820e53c56a4288e8dd76fd6879800d6211576 | Python | 6,596 | 171 | import argparse
import glob
import os
import math
import pandas as pd
import pickle
from tensorflow.core.util import event_pb2
from tensorflow.data import TFRecordDataset
# Parsing script for random-search-based hyperparameter optimization.
# DEFINE PARSER
def init():
parser = argparse.ArgumentParser(description... |
0e2ab139de3bab244eac0b7b7c0f693b30d8270ee6136e5d82e201ba966e9473 | Python | 6,597 | 158 | # This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
import warnings
from typing import Optional
import torch
from torch import Tensor, nn
from sbi.neural_nets.embedding_nets.fully_connected import FCEmbed... |
956033ea4c6f725420c3a5701c11b904af0fedf7e5d1e1bad55d159b9552610f | Python | 6,600 | 172 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from mmdet.core.mask import BitmapMasks, PolygonMasks
from mmdet.datasets.builder import PIPELINES
from .utils import check_result_same, construct_toy_data
def test_rotate():
# test... |
45c89c11c612f5164d074090a450aa7e54a50890453ce020711371f3ad3889ad | Python | 6,606 | 225 | import glob
from pathlib import Path
import mne
import numpy as np
import torch
from scipy.signal import resample_poly
from sklearn.preprocessing import RobustScaler
from anysleep_no_hydra import AnySleep
def load_edf(input_file: str, channels_to_include, resample_rate):
"""
Load and preprocess an EDF file ... |
b224e341e7ad7b6fdd46c1186f568e8e5af6c477e00d7462441f1a9c4d19cef2 | Python | 6,607 | 222 | _base_ = [
'../../../../_base_/default_runtime.py',
'../../../../_base_/datasets/h36m.py'
]
checkpoint_config = dict(interval=20)
evaluation = dict(
interval=10, metric=['mpjpe', 'p-mpjpe', 'n-mpjpe'], save_best='MPJPE')
# optimizer settings
optimizer = dict(
type='Adam',
lr=1e-3,
)
optimizer_confi... |
97b7b5ebf512baa2fae63fae5ca38bb24a04524bcfd16a8e44b176373a1bb02a | Python | 6,608 | 189 | # Copyright (c) OpenMMLab. All rights reserved.
import torch.nn as nn
from .. import builder
from ..builder import POSENETS
@POSENETS.register_module()
class MultiTask(nn.Module):
"""Multi-task detectors.
Args:
backbone (dict): Backbone modules to extract feature.
heads (list[dict]): heads t... |
5319f95f670b45c382ada2cd3d609e3e1c372358d5f6839fc5725c049a3fb7d4 | Python | 6,613 | 162 | import logging
import os
import h5py
import torch
import torch.utils.data as data
from . import utils
logging.basicConfig()
logger = logging.getLogger()
logger.setLevel(logging.INFO)
client_ids_train = None
client_ids_test = None
DEFAULT_TRAIN_CLIENTS_NUM = 715
DEFAULT_TEST_CLIENTS_NUM = 715
DEFAULT_BATCH_SIZE = 4
... |
ac9b0c4333f73c57c85e01bf88db89baed64671d455e5ab175c4cf471267ab04 | Python | 6,617 | 310 | import re, sys
from VCF import VCF
ZYG={'0/1':'HET', '1/1':'HOMO', './.':'UNKNOWN', '0/0':'REF'}
class LUMPY (VCF):
def __init__ (self, name):
super (LUMPY, self).__init__(name)
def filter_func(self, chrom, beg, end, type, E):
#if re.search ('0/0', E[-1]): return True
if i... |
8a046a05243418445540d0f743a1db96ace40b5e8b5de4c1d250ee7ade689db4 | Python | 6,630 | 160 |
import pickle
import numpy as np
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.pyplot as plt
import pickle
from absl import flags, app
cmap_1 = 'Blues'
cmap_2 = 'Reds'
# cmap_1 = 'bwr'
def calculate_error(pred, label, mask):
'''
pred: [batch, len, 1]
label: [batch, len, 1]
mas... |
de726e8385baec13da8e050b3dc26817e4c8049d5b66171e88cbce9c2b20c025 | Python | 6,632 | 165 | import pandas as pd
from A_config import a10_config
import os
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from F_post_processsing import F100_analyze_hindcast_output
"""
Compare two results (e.g. without SF vs with SF)
"""
# configuration files and run names
# baseDir = ... |
282370bc480f18c9e53997cf12fb0af862da3b73f7b3c6cc6aa186864b6b66b4 | Python | 6,638 | 176 | # -*- coding: utf-8 -*-
"""Process all the options"""
__author__ = "Sean Benson"
__copyright__ = "MIT"
import json
import argparse
norms = {
'torchvision_3d': ([0.43216, 0.394666, 0.37645],
[0.22803, 0.22145, 0.216989]),
'torchvision_2d': ([0.485, 0.456, 0.406],
... |
94c55f4df1efd576b49f053adba604a5d22a627419b9a5ac643c057e742af39c | Python | 6,638 | 180 | # Copyright (c) OpenMMLab. All rights reserved.
import copy
import logging
import torch.nn as nn
from mmcv.cnn import ConvModule
from torch.nn.modules.batchnorm import _BatchNorm
from ..builder import BACKBONES
from .base_backbone import BaseBackbone
from .utils import InvertedResidual, load_checkpoint
@BACKBONES.r... |
2dd1dbbfb3461c7ad919921f8885f9923ed3f424a6b9f2fa34634ae3c4ea93c3 | Python | 6,639 | 153 | # -*- coding: utf-8 -*-
"""
Created on Mon Jul 5 12:50:30 2021
@author: fhu14
"""
#%% Imports, definitions
import os
import pickle
from DFTBPlus import (
filter_dataset,
find_all_used_configs,
read_detailed_out,
run_organics,
)
from .helpers import auorg_dir, get_dftbplus_executable, mio_dir, test_... |
4dc67207ef903bbfc0ed65a0fe2dd65c9c5111824168320f3b197efcf8b79e45 | Python | 6,642 | 180 | #!usr/bin/env python
#coding:utf-8
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import argparse
import os
import numpy as np
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import ModelCheckpoint, EarlyStopping
f... |
8fcc42055238768c361ac88dccb3a3afeb2180bc20ecfc658371c57cb51b121a | Python | 6,645 | 171 | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch
from mmdet.core import bbox2result
from ..builder import DETECTORS, build_backbone, build_head, build_neck
from .base import BaseDetector
@DETECTORS.register_module()
class SingleStageDetector(BaseDetector):
"""Base class for single-st... |
32e125f08fc29431f39cc545e92e5b5b03204a912e29ec2c24e2d4f7051d45d3 | Python | 6,647 | 159 | from scipy.sparse import csgraph
from theano import tensor as T
from utils import graph_to_adj
import networkx as nx
import numpy as np
import scipy.sparse as sparse
import theano
# For dynamic loading: name of this method should be the same as name of this python FILE.
def netmf(ctrl, graph):
'''Use NetMF as the... |
992fb40d7caceddd727bfa840ff733c3c97ee49b0df2e36bf10a9678d657af44 | Python | 6,649 | 201 | """
Predict sleep stages from an EDF file and visualize the hypnogram.
This script demonstrates how to use the standalone AnySleep model to:
1. Load and preprocess EEG/EOG data from an EDF file
2. Run inference to get sleep stage predictions
3. Save raw logits and visualize the predicted hypnogram
The script handles ... |
209ef88bf67138bffe1e1c37c1e46b6fc998cc7636eede42b3dccd0fb092e630 | Python | 6,654 | 170 | import os
import numpy as np
from scipy.interpolate import InterpolatedUnivariateSpline
# interface
class SkfInfo(object):
def __init__(self, name, paramPath):
elem1, elem2 = name.split('-')
self.__homo = (elem1 == elem2)
self.name = name
with open(os.path.join(paramPath, name ... |
f35b2c845ca95beeed46aef2362b9ada6db5c0abeef1be30a0254508a7ce512c | Python | 6,654 | 155 | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from mmdet.core import bbox2roi
from mmdet.models.losses import SmoothL1Loss
from ..builder import HEADS
from .standard_roi_head import StandardRoIHead
EPS = 1e-15
@HEADS.register_module()
class DynamicRoIHead(StandardRoIHead):
"""R... |
8517980abb8d5a9d8ec5b967eae345a554a298817beaf4e186b5c75a385c3753 | Python | 6,656 | 160 | # Copyright (c) OpenMMLab. All rights reserved.
from mmdet.core import bbox2roi
from ..builder import HEADS
from ..losses.pisa_loss import carl_loss, isr_p
from .standard_roi_head import StandardRoIHead
@HEADS.register_module()
class PISARoIHead(StandardRoIHead):
r"""The RoI head for `Prime Sample Attention in Ob... |
b63fedd0d563db68de137b9d388a397116598cb8c32363ee469413a09609132f | Python | 6,662 | 198 | import glob
from pathlib import Path
import mne
import numpy as np
import torch
from scipy.signal import resample_poly
from sklearn.preprocessing import RobustScaler
from anysleep_no_hydra import AnySleep
def load_edf(input_file: str, channels_to_include, resample_rate):
"""
Load and preprocess an EDF file ... |
9fc5f021108e26762407b53c696d0abef7ea3254b8b2587ca0e8d4b6039f8a1f | Python | 6,665 | 146 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..builder import BBOX_ASSIGNERS
from ..match_costs import build_match_cost
from ..transforms import bbox_cxcywh_to_xyxy
from .assign_result import AssignResult
from .base_assigner import BaseAssigner
try:
from scipy.optimize import linear_sum_assig... |
7f851569e8033d17e7a2612c4012853cf92c8c09513b2b4ef67f0c8125201ebd | Python | 6,666 | 173 | '''
* Copyright (c) 2022, salesforce.com, inc.
* All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
* For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause
* By Junnan Li
'''
import argparse
import os
import ruamel_yaml as yaml
import numpy as np
imp... |
b2a6be228fed3f3dd4f696c187c418bcc62c6717c53c72637b8ba54945516f2a | Python | 6,667 | 210 | import random
import cvxpy as cp
import numpy as np
import torch
from scipy.linalg import ldl
# ambuguous RNA letters: GAUCRYWSMKHBVDN
rna_letters = [letter for letter in '-.GAUCRYWSMKHBVDN']
rna2index = {letter: index for index, letter in enumerate(rna_letters)}
rna2index['START_TOKEN'] = len(rna2index)
rna2index['... |
f2b4d8fc8e31268b4c6b3c84b7dfd187ee19d76fc93f25bf031878b202c8ffb7 | Python | 6,668 | 179 | from typing import Type, Union
import warnings
import datetime
import unittest
import logging
import os
import pandas as pd
import numpy as np
log_file = os.path.join(os.path.abspath("./logs"),
"cohort.log")
with open(log_file, 'w') as fi:
fi.write(f'Logs {datetime.datetime.... |
c6ea56d0e3d73e5e133449c41c0ca1669f6032e23909a50c9a9a30ea3e29a2ab | Python | 6,675 | 155 | # Copyright (c) OpenMMLab. All rights reserved.
import warnings
import torch
import torch.nn as nn
from mmcv.runner import ModuleList
from ..builder import HEADS
from ..utils import ConvUpsample
from .base_semantic_head import BaseSemanticHead
@HEADS.register_module()
class PanopticFPNHead(BaseSemanticHead):
""... |
76c7ae7788ea72c1240b2b01174d168b564125f50f4bfb22bb08214d5ad97a67 | Python | 6,684 | 156 | """ NNabla metadata script """
import json
import os
import sys
import mako.template
import yaml
def _write(path, content):
with open(path, "w", encoding="utf-8") as file:
file.write(content)
def _read_yaml(path):
with open(path, encoding="utf-8") as file:
return yaml.safe_l... |
14fe3fb7fde4b8265eb1c769e073da16c6602484174f7ce4a05a08ce640cd02d | Python | 6,697 | 146 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from ..builder import BBOX_ASSIGNERS
from ..iou_calculators import build_iou_calculator
from .max_iou_assigner import MaxIoUAssigner
@BBOX_ASSIGNERS.register_module()
class ApproxMaxIoUAssigner(MaxIoUAssigner):
"""Assign a corresponding gt bbox or back... |
75258ffa14ec4a3976e0bdd37ca783b18b38328c8213437f39a3dbc44af6c37e | Python | 6,703 | 188 | import torch
import torch.nn as nn
import torch.nn.functional as F
from fedml_api.model.cv.darts.genotypes import PRIMITIVES, Genotype
from fedml_api.model.cv.darts.operations import OPS, FactorizedReduce, ReLUConvBN
class MixedOp(nn.Module):
def __init__(self, C, stride):
super(MixedOp, self).__init__(... |
5a3a880acf3d66706525d7e175e2b9543c1c714dbc3a99e492ea9de67adae002 | Python | 6,705 | 155 | from GUI_and_data_processing.Create_GUI import *
from GUI_and_data_processing.Data_processing import *
from Root_Morales_lab_codes.FibPhoEpocAveraging import *
from Analysis_types.Whole_recording import *
from Analysis_types.Peri_events import *
from Root_Morales_lab_codes.FibPhoEpocAveraging_between_events import... |
67ef5b1efd7e9d2a29e167913318dd00dcf5ea0cd38d7df0b4fc496f0c5e7d54 | Python | 6,709 | 137 |
import pickle
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from jax.config import config
import tensorflow as tf
import os
os.environ['XLA_PYTHON_CLIENT_PREALLOCATE'] = 'false'
tf.config.set_visible_devices([], device_type='GPU')
from collections import OrderedDict
from ppri... |
c95020e84f3fd9c08748df12a4ac73a518de2425c39141935a5ce4b71ecd718e | Python | 6,710 | 218 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import numpy as np
import pytest
from mmcv import bgr2rgb, build_from_cfg
from mmpose.datasets import PIPELINES
from mmpose.datasets.pipelines import Compose
def check_keys_equal(result_keys, target_keys):
"""Check if all elements in target_k... |
c1e13f09752fba602a4fbe7b4a7b84173f1562f46739890650c3839b628d936d | Python | 6,711 | 222 | """Provide pytest fixtures for the entire test suite.
These fixtures create data and data modules that can be reused by other tests.
"""
import os
import pytest
import subprocess
import torch
from typing import Callable
import yaml
from daart.data import DataGenerator
from daart.utils import build_data_generator
... |
ec6826de578bf32657e400fc7a187d7d9aca7b90a65193a8363d133dd7cadd30 | Python | 6,715 | 109 | #!/usr/bin/env python
from os import path
import pandas as pd
import sys
from picrust2.util import (prune_tree, read_fasta_ids)
def get_lowest_nsti(nsti_table_dom1_path,
nsti_table_dom2_path,
dom1_name,
dom2_name,
verbose=False):
'... |
8646e82bc38a2cd4bad3a9c12f09b8db48b0e9107376743e2e730d727117546f | Python | 6,719 | 201 | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch.nn as nn
from mmcv.cnn import normal_init
from mmpose.core.evaluation import (keypoint_pck_accuracy,
keypoints_from_regression)
from mmpose.core.post_processing import fliplr_regression
from mmpose.model... |
7e7159af6e6f4336a3bec778c7cf629b36f8b5103d71c6c0b9713822aa943a36 | Python | 6,739 | 176 | # Copyright Universitat Pompeu Fabra 2020-2023 https://www.compscience.org
# Distributed under the MIT License.
# (See accompanying file README.md file or copy at http://opensource.org/licenses/MIT)
from os.path import join
from tqdm import tqdm
import torch
from torch.utils.data import Subset
from torch_geometric.lo... |
7d0df21362c72c570610e54d12ce1093885864ec6f7ef1c06b06da54dd942876 | Python | 6,744 | 158 | # Copyright (c) OpenMMLab. All rights reserved.
import numpy as np
import torch
from ..builder import BBOX_SAMPLERS
from .random_sampler import RandomSampler
@BBOX_SAMPLERS.register_module()
class IoUBalancedNegSampler(RandomSampler):
"""IoU Balanced Sampling.
arXiv: https://arxiv.org/pdf/1904.02701.pdf (CV... |
740d606c989da846f69085459e27aa3008ccbe2733cd8d16b8e8a8a341c840b4 | Python | 6,746 | 198 | import glob
from pathlib import Path
import mne
import numpy as np
import torch
from anysleep_no_hydra import AnySleep
from scipy.signal import resample_poly
from sklearn.preprocessing import RobustScaler
def load_edf(input_file: str, channels_to_include, resample_rate):
"""
Load and preprocess an EDF file f... |
6b6a2deac6017ecd2f90d74e8e37e7c0e8e0bdd54dd7310cde6887a968d6dbbe | Python | 6,747 | 212 | import os
import shutil
import subprocess
from pathlib import Path
from genomad import database, utils
class MMseqs2:
def __init__(
self,
mmseqs2_output: Path,
mmseqs2_directory: Path,
proteins_output: Path,
genomad_db: database.Database,
use_minimal_db: bool = Fal... |
21c00f899694a9da8c1dc66d86ecdd9d95ffebe04631bd14907db8ecd65fba2b | Python | 6,749 | 157 | import sys
import os
import numpy as np
from Bio import SeqIO
import multiprocessing
## Se añaden estas dos librerias para generar un indentificador único en los archivos 2d.npy y poder ejecutar varios análisis al tiempo.
import random
import string
N = 5
uniqueID = ''.join(random.choices(string.ascii_uppe... |
1656afd51e072a5550da0106df92a6881dc566103e60933d28661f30ace59321 | Python | 6,756 | 167 | # Copyright (c) OpenMMLab. All rights reserved.
import torch
from mmdet.core.evaluation.bbox_overlaps import bbox_overlaps
from mmdet.models.dense_heads import CornerHead
def test_corner_head_loss():
"""Tests corner head loss when truth is empty and non-empty."""
s = 256
img_metas = [{
'img_shape... |
041d14193f5eff427c3bfddfac3f24f8fac0941b92823475c2cd8e9716ae91fb | Python | 6,766 | 191 | # Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
import warnings
from collections import OrderedDict
import numpy as np
from mmcv import Config, deprecated_api_warning
from ...builder import DATASETS
from ..base import Kpt2dSviewRgbImgTopDownDataset
@DATASETS.register_module()
c... |
0ed085365005b9ca535ca29686dc6d2025f8ae09626632c0e59b52dd75b339b0 | Python | 6,766 | 196 | ##############################################################################
# Kivy Launcher Interface #
# by: Daniel Palmer PhD #
# Version: 2.0 #
####... |
f1ac6ff9dfc54567d3dc003f45d821307b5ffb4bd1fb02be6416db9413162e59 | Python | 6,766 | 178 | # -*- coding: utf-8 -*-
"""
Created on Wed Oct 12 13:38:23 2022
@author: Daniel
"""
from phase_to_rate.neural_coding import load_spikes, rate_n_phase, load_spikes_DMK
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import os
import sys
import matplotlib as mpl
import pdb
... |
6529196fe293e34fa854e133c97dff092d7fa3fd96ce579589bc75e475a42805 | Python | 6,768 | 187 | import numpy as np
from tqdm.auto import tqdm
import torch
from torch_geometric.data import Data
from rdkit import Chem
from rdkit.Chem.rdForceFieldHelpers import MMFFOptimizeMolecule
import torchmdnet.datasets.geom_utils.utils
def get_rmsd_confusion_matrix(data: Data, useFF=False):
data.pos_ref = data.pos_ref.... |
f3bd63694d38d94c5ebb1befcde846b3c708b7357ae699fa862815a9f8e7f942 | Python | 6,771 | 199 |
import os
os.environ['XLA_PYTHON_CLIENT_PREALLOCATE'] = 'false'
from pprint import pprint
import jax
import jax.numpy as jnp
import jax.tree_util as tree
import numpy as np
from functools import partial
import haiku as hk
import optax
from absl import app, flags, logging
from collections import namedtuple
from tqdm i... |
f38ad34f0952e8ac9b2d34beb74e6330f74f047033088dec0c99dd44d20d82a5 | Python | 6,780 | 186 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import copy
import os
import os.path as osp
import time
import warnings
import mmcv
import torch
from mmcv import Config, DictAction
from mmcv.runner import get_dist_info, init_dist
from mmcv.utils import get_git_hash
from mmdet import __version__
from m... |
2dcb53c33b4299345db79dbf83daaa512ba4965a0dd1224787f8c18b2fc5f878 | Python | 6,782 | 189 | from collections import defaultdict
import itertools
import random
import igraph as ig
import numpy as np
class Sequence:
def __init__(self, header, seq):
self._header = header
self._seq = seq
@property
def header(self):
return self._header
@property
def id(self):
... |
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