sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
044653f9fabdc60013c5ed6f2a0397663674ee1832a160c58728a883147c831d | Python | 29,284 | 728 | """
Author: Mingjian He <mh1@stanford.edu>
Dynamic programming (also known as belief propagation) algorithms for exact inference
"""
import torch
import numpy as np
from scipy.linalg import solve_triangular
def forward_backward(A, py_x, p1=None, compute_edge=False):
"""
Classical forward-backward algorithm ... |
882a23fd3bf0234c7c415dcae8e5d9b75be9ee0ed7d7b02be719c303709a4b60 | Python | 29,288 | 721 | """ Scheduler Tests
Tests for learning rate schedulers in timm.scheduler.
"""
import math
import pytest
import torch
from torch.nn import Parameter
from timm.scheduler import (
CosineLRScheduler,
StepLRScheduler,
MultiStepLRScheduler,
PlateauLRScheduler,
PolyLRScheduler,
TanhLRScheduler,
W... |
e11344e014055dbbd40fdea1ac38ae8a157eeb95aceaa1c6e11bce4d73507c19 | Python | 29,468 | 508 | # -*- coding: utf-8 -*-
"""
@author: bartulem
Read in sync events from all desired data streams.
Neuropixel recordings are saved into a *1D binary vector*, from a 2D array organised as 385 rows (channels) x n columns (samples).
The data are written to file from this matrix in column-major (F) order, i.e., the first... |
71376b3d66751f23d4fa325775e6d840ad04589c3edbf78263d8feec05913f48 | Python | 29,490 | 900 | # # Copyright (C) 2014 Paul Schultz and the SWIPO Project
#
# Authors (this file):
# Stefan Schinkel <stefan.schinkel@gmail.com>
# Paul Schultz pschultz@pik-potsdam.de>
#
#
# References: [Schultz2014]_, [Schultz2014a]_,
#
# ToDo:
# - included Schultz' Predictor and growth algorithm (among others)
"""
Module cont... |
f012ba741a1a962a072083c7208779e17f0dff84095b08d5e0f574994e7467b8 | Python | 29,491 | 890 | """ PP-HGNet (V1 & V2)
SSLD pretrained weights:
* `Beyond Self-Supervision: A Simple Yet Effective Network Distillation Alternative to Improve Backbones` - https://arxiv.org/abs/2103.05959
Reference:
https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/ImageNet1k/PP-HGNetV2.md
The Paddle Implemen... |
2c3827a0b21992e2ea4efd3c8b61e0f94cf79ede167980d664b341d5ebf6ce2d | Python | 29,518 | 573 | from functools import partial
from collections.abc import Callable
import centriole.smooth
import centriole.cpmorphology
import scipy.ndimage
import numpy
from numpy.typing import NDArray
from typing import Optional, Tuple, Annotated, cast
from typing_extensions import TypeAlias
from pydantic import Field, validate_cal... |
477b144b4694bee00ee5a4fa26367dec19055a30ed6266c91e6198863195c380 | Python | 29,592 | 709 | """
Author: "Keitaro Yamashita, Garib N. Murshudov"
MRC Laboratory of Molecular Biology
This software is released under the
Mozilla Public License, version 2.0; see LICENSE.
"""
from __future__ import absolute_import, division, print_function, generators
from servalcat.utils import logger
from servalcat.utils impo... |
ad93a6317171df3ad63edb765831997f7e06467683a35a835bb83ccaa61da225 | Python | 29,597 | 867 | from enum import Enum
import numpy as np
from numpy.random.mtrand import RandomState
import scipy.sparse
import centriole.index
from typing import Tuple
from numpy.typing import NDArray
from ..types import ObjectLabel, ObjectSegmentation
class SPARSE_FIELD(Enum):
label = "label"
c = "c"
t = "t"
z = "z"... |
3e919df1acafd7fea607cd8b743c13332f5581cd8cc9fe16f6d8213d44d0cb80 | Python | 29,638 | 706 | # coding=utf-8
# Copyright 2020 The SimCLR Authors.
#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... |
c2e5b4a507bd22cb110a20f0309bc80453f2916b72cfabb1585b6695d7035d52 | Python | 29,644 | 865 | from os.path import exists, basename, join, dirname
import nibabel as nib
import numpy as np
from scipy.signal import cubic
from scipy.sparse import kron, lil_array
from traitlets import (Instance,
Integer,
Unicode,
Bool,
Dict,... |
cbad1c19e224d28766d61a8461c4bc6efee400dfb26b372f7d7dfbbbbfc05448 | Python | 29,859 | 715 | import logging
import os
import sys
import uuid
import wx
from cellprofiler_core.preferences import report_progress
from cellprofiler_core.setting import FileCollectionDisplay
from ..pipeline import Pipeline
from ..utilities.module_view import edit_control_name
from ...icons import get_builtin_image
LOGGER = logging... |
67e8ba38c84bcf3e7dcdbefc206161071c47eba3261f3741d67b6f2cf23462ba | Python | 29,954 | 607 | # -*- coding: utf-8 -*-
import time
import torch
import torchvision
from torchvision import transforms,datasets
import numpy as np
import os
import sys
import subprocess
#加载tidigits数据集
from python_speech_features import fbank
import numpy as np
import scipy.io.wavfile as wav
from sklearn.preprocessing impo... |
f1089a1f5e4bd646a462dfa6b8af1a8ed0269ed5b75431992e07166792ea92e3 | Python | 29,985 | 884 | """Tests for the ordinal re-coder."""
import itertools
import os
import tempfile
from concurrent.futures import ThreadPoolExecutor
from functools import cache as fcache
from typing import Any, Tuple, Type, TypeVar
import numpy as np
import pytest
from .._typing import EvalsLog
from ..compat import import_cudf
from .... |
f6340b4fdf2cd84687f793996058f5870ad0f0eb4d54e9606b6c9dad4e5278d7 | Python | 30,048 | 796 | """ Vision Transformer (ViT) in PyTorch
A PyTorch implement of Vision Transformers as described in:
* `Exploring Plain Vision Transformer Backbones for Object Detection` - https://arxiv.org/abs/2203.16527
* `Segment Anything` - https://arxiv.org/abs/2304.02643
* `An Image is Worth 16x16 Words: Transformers for Image ... |
ae9b135194d22a63a21968a0c7ed73c4debb734d6a1596dca0fa11f0393d9a3f | Python | 30,077 | 710 | import scanpy as sc
import pandas as pd
import numpy as np
import math
from scipy.sparse import csr_matrix, find
import matplotlib.pyplot as plt
import time
from scipy.stats import norm
from joblib import Parallel, delayed
def which(x):
n = len(x)
m = sum(x)
y = np.zeros(m)
j = -1
for i in range(... |
00290f4bc8da38dfc07d35630e1689a92db33925a7d3d2ee27aeb5b0f50ea0a6 | Python | 30,115 | 521 | #### Master Script 05b: Prepare environment to calculate TimeSHAP for dynAPM_DeepMN models ####
#
# Shubhayu Bhattacharyay
# University of Cambridge
# email address: sb2406@cam.ac.uk
#
### Contents:
# I. Initialisation
# II. Identify transition points in testing set predictions for TimeSHAP focus
# III. Partition signi... |
c8fcd3820b535565683680deffabdf2d2a76f108ca298f7f16d2fa96f6758c7b | Python | 30,144 | 715 | # Pytorch Tabular
# Author: Manu Joseph <manujoseph@gmail.com>
# For license information, see LICENSE.TXT
"""Config"""
import logging
import os
from dataclasses import MISSING, dataclass, field
from typing import Any, Dict, List, Optional
from omegaconf import OmegaConf
logger = logging.getLogger(__name__)
def _rea... |
faac827d17e3822bc908d3b2f783d209332cef20edc7da7b606e78f96357cecf | Python | 30,231 | 925 | import numpy
import six.moves
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import COLTYPE_INTEGER, COLTYPE_FLOAT, NEIGHBORS, R_FIRST_OBJECT_NUMBER, \
R_SECOND_OBJECT_NUMBER
from cellprofiler_core.measurement import RelationshipKey
import cellprof... |
8ee36602a1a1692d5bd4276038e40c353f1aad43cea0288bb32a6707fa81ad74 | Python | 30,314 | 623 | import numpy as np
import scipy as sp
# import pandas as pd
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Activation, Lambda, Dense
from tensorflow.python.keras import backend as K
from tensorflow.keras.datasets import mnist, fashion_mnist
from extra_keras_d... |
cd53cfad5121bffc6b41364a60e52d4175b35e682127abcbbd9f126a28be8a6d | Python | 30,414 | 903 | import numpy as np
import centriole.outline
import cellprofiler_library.functions.segmentation as lib_seg
from cellprofiler_library.functions.segmentation import SPARSE_FIELD
def _check_indices(indices, indices_expected):
assert len(indices) == len(indices_expected)
for labels, labels_expected in zip(indices,... |
61b44039bd6c896b76bf641cd329d2e074169661b47b8d11c1e024bd5329db7e | Python | 30,623 | 673 | """PROVONE-RDF serializers for ProvONEDocument
"""
import base64
from collections import OrderedDict
import datetime
import io
import dateutil.parser
from prov.constants import (
PROV,
PROV_ACTIVITY,
PROV_ALTERNATE,
PROV_ASSOCIATION,
PROV_ATTR_ENDER,
PROV_ATTR_ENDTIME,
PROV_ATTR_INFORMANT,
... |
e4bb95aace35c7e7c94da7cbf243ea124ec29ff52ab5ec3bd3b256851c9c9297 | Python | 30,652 | 898 | """ TinyViT
Papers:
* `TinyViT: Fast Pretraining Distillation for Small Vision Transformers` - https://arxiv.org/abs/2207.10666
Adapted from official impl at https://github.com/microsoft/Cream/tree/main/TinyViT
"""
__all__ = ['TinyVit']
import itertools
from functools import partial
from typing import Dict, List, O... |
8a7455abb28032527ab69f6b386470885fcc3d9ff742458ff5276dda5efdf78d | Python | 30,767 | 728 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Feb 17 17:56:34 2022
@author: Manuel
Set general functions and variables.
"""
__author__ = "Manuel R. Popp"
#### parse arguments-----------------------------------------------------------
import argparse
import urllib.request # in case it i... |
f5e12c46a91325e68504e389c50add30f7bf91d4f28a0bef413f2e7357159b14 | Python | 30,896 | 609 | import torch
import torchvision
import torch.nn.functional as f
import math
from tqdm import tqdm
from utils import radam
import utils.viz_utils as viz_utils
from models.style_networks import StyleEncoderE2VID, SemSegE2VID
import training.base_trainer
from evaluation.metrics import MetricsSemseg
from utils.loss_funct... |
c042710cf1b871e02f0cc0221e4c643aae5e306d1cf251c6c6a940a91d8ab3ec | Python | 31,025 | 738 | from typing import Iterable, Tuple, Union, List, Optional, Sequence, Dict
from numbers import Number
from pathlib import Path
import warnings
from tqdm import tqdm
import numpy as np
import nibabel as nib
import torch
import torchio as tio
from torchio import Subject, RandomAffine, IntensityTransform, CropOrPad, Re... |
bac9e162b1e36249786e0fc5f7049c417c3870ef560bb463e6fee89890b8758c | Python | 31,045 | 820 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
0d17c30c8e77be785224651152a932a8e4e7c78e5d04b1280733ef86c27f9b1b | Python | 31,166 | 638 | # -*- coding: utf-8 -*-
"""
------------------------------------------------------------------------------
Copyright (C) 2019 Université catholique de Louvain (UCLouvain), Belgium.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.... |
bf17deb2cbdb33d6cc7ac3e775fb952460763f4e8f2625f33ea36f2f5a99a4b7 | Python | 31,202 | 901 | import matplotlib as mpl
mpl.use('agg')
from matplotlib.testing.compare import compare_images
from tempfile import NamedTemporaryFile
import os.path
import shutil
import pygenometracks.plotTracks
import sys
ROOT = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_data")
browser_tracks... |
6d7b004badfb625dff380ed382b78981a14a012598a4d650b4e842c90ae4f4f5 | Python | 31,309 | 366 | """Directory for tests of individual modules
"""
import logging
import base64
import hashlib
import numpy as np
import os
import unittest
import tempfile
import functools
import scipy.io.matlab.mio
import numpy
import skimage.io
from urllib.request import URLopener
import cellprofiler_core.utilities.legacy
from cellpr... |
66a0226cca8fb437a54425ce88b779d5d6a929a5d3984360c0882f99a9989c77 | Python | 31,388 | 696 | import math
import dgl
import torch
from torch import nn
from dgl import function as fn
from src.utils.graph_norm import GraphNorm
import sys
def get_non_lin(type, negative_slope):
if type == 'swish':
return nn.SiLU()
else:
assert type == 'lkyrelu'
return nn.LeakyReLU(negative_slope=ne... |
5544b7039096a737fe9886ba4b459118a3d7c4cb42fe73b2e7b9de5365d5a786 | Python | 31,459 | 763 | """ CrossViT Model
Papers:
* `CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification` - https://arxiv.org/abs/2103.14899
@inproceedings{
chen2021crossvit,
title={{CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification}},
author={Chun-Fu (Richard) Chen ... |
50057f227f65e915f3b9dd2a586fae0cf3e2f3e593c9d843120a8c19e3964f9c | Python | 31,610 | 753 | import collections
import io
import logging
import os
import queue
import subprocess
import sys
import tempfile
import threading
import re
import numpy
import psutil
from .event import Finished
from .event import Paused
from .event import Progress
from .event import Resumed
from .event import Started
from . import re... |
a56cc522f0aaad4c337c7b19b9d402ddf8591e83a18dbfbbda9ce3ab94ae3c03 | Python | 31,650 | 771 | """
Author: "Keitaro Yamashita, Garib N. Murshudov"
MRC Laboratory of Molecular Biology
This software is released under the
Mozilla Public License, version 2.0; see LICENSE.
"""
from __future__ import absolute_import, division, print_function, generators
import gemmi
import numpy
import subprocess
import shlex
imp... |
86dd2d505479c05c262f990afa6b179bc4f1518b7c155b8092b3d449169888f3 | Python | 31,742 | 717 | # encoding: utf-8
# Author : Floyed<Floyed_Shen@outlook.com>
# Datetime : 2022/4/28 14:56
# User : Floyed
# Product : PyCharm
# Project : braincog
# File : main_simplified.py
# explain : Simplified training script. Remove support for DDP, IMAGENET, Augment, etc.
import argparse
import time
import ... |
25498edba93982b27face21154a91c677b3382fad9858d8b34610c6e77571718 | Python | 31,856 | 626 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu May 28 09:56:19 2020
@author: nozais
Si les fichiers 4D sont tous dans le même dossier, avec donc des noms différents du type "mySubXXX.nii.gz",
les fichiers de sortie seront placés dans des dossiers nommés "*/mySubXXX_functionnectome/"
Bold paths and... |
3683e74d1e52368daf15cfcb38d6facf5e6b1ec9441112d9159754d0d3bdd172 | Python | 31,920 | 984 | import reprlib
from collections.abc import Iterator, Sequence
from dataclasses import dataclass
from functools import lru_cache
from pathlib import Path
from typing import (
Any,
Literal,
Protocol,
)
import numpy as np
import polars as pl
from sklearn.model_selection import train_test_split
from sklearn.pr... |
dfe65137d65e982d439b0089852e338bea20e642c47c814a25a05c557f6c77d1 | Python | 32,006 | 899 | """
pysteps.noise.fftgenerators
===========================
Methods for noise generators based on FFT filtering of white noise.
The methods in this module implement the following interface for filter
initialization depending on their parametric or nonparametric nature::
initialize_param_2d_xxx_filter(field, **kwar... |
fe23635750e649116863019d6f2f04c097304e9fb5e74eed98919e3a1c4ebcc7 | Python | 32,063 | 898 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
e9b0e81ea0b5f74cb783659f2b8dc731da439d09f09b8abade00ea6920f3062c | Python | 32,070 | 799 | """Knowledge distillation training tasks and components."""
import logging
from typing import Any, Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models import create_model, group_parameters
from timm.utils import unwrap_model
from .classification import res... |
997424374e46ec7981402fc2c7fd596b590d217bd27ae732182397d5fafaf769 | Python | 32,112 | 592 | """
Maked example plots.
@author: bartulem
"""
import os
import sys
import json
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.colorbar as cbar
from scipy.stats import sem
import neural_activity
import select_clusters
plt.rcParams['font.sans-serif'] = ['Helvetica']
class Pl... |
5a665bf3db4e47a2544eaba4c7d09b14a68c86d809cec1650bcfc449fec9d596 | Python | 32,123 | 803 | from __future__ import annotations
import re
import sys
from datetime import date, datetime
from decimal import Decimal
from enum import Enum
from typing import Any, Dict, List, Literal, Optional, Union
from pydantic.version import VERSION as PYDANTIC_VERSION
if int(PYDANTIC_VERSION[0]) >= 2:
from pydantic impor... |
a6e02f34a2a7feb2eeb5f16369e1340eea491e72d17ebb20ca6fdb43e9a43f61 | Python | 32,137 | 684 | # imports #####################################################################
import matplotlib.pyplot as plt
import copy
import pickle
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Activation, Lambda, Dense
from tensorflow.python.keras import backend as ... |
7f6deee0d743a851bb48cd8dd255895a954af0be1def8a1a02f2525c9cd41cab | Python | 32,255 | 945 | """Tests for multi-target training."""
# pylint: disable=unbalanced-tuple-unpacking
import json
import pickle
from types import ModuleType
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import pytest
from sklearn.datasets import (
make_classification,
make_multilabel_c... |
828f7ca64beb11ae06d0ac1972773e94ae09db19b21337d01bf2a983747e16f0 | Python | 32,283 | 972 | """Python implementation of the ProvONE Model Specification
References:
ProvONE: http://vcvcomputing.com/provone/provone.html
"""
import io
import logging
import os
import shutil
import tempfile
from urllib.parse import urlparse
from prov.constants import (
PROV_ASSOCIATION,
PROV_ATTR_COLLECTION,
PROV_AT... |
d590e2a1feabb1eb0b0cc4336b7e6929243cf711f81a352c3c0a070c0a71d31f | Python | 32,321 | 609 | """
Adapted from: https://github.com/uzh-rpg/rpg_ev-transfer
"""
from __future__ import division
import torch
from tqdm import tqdm
tqdm.monitor_interval = 0
import numpy as np
from tensorboardX import SummaryWriter
from utils.saver import CheckpointSaver
from datasets.wrapper_dataloader import WrapperDataset
import... |
08fa385b68d1235edd36a3b979d4cf15cbd2eeccb1837548d48c01560348d749 | Python | 32,325 | 374 | #### Master Script 6c: Calculate metrics for test set performance for sensitivity analysis ####
#
# Shubhayu Bhattacharyay
# University of Cambridge
# email address: sb2406@cam.ac.uk
#
### Contents:
# I. Initialisation
# II. Calculate testing set sensitivity analysis metrics based on provided bootstrapping resample row... |
bfd6f933359b23afed12ffcb43b1fc7db1b35bd5fb8cbdd5d9b0fd8b7edf7828 | Python | 32,331 | 716 | # encoding: utf-8
# Author : Floyed<Floyed_Shen@outlook.com>
# Datetime : 2022/4/28 14:56
# User : Floyed
# Product : PyCharm
# Project : braincog
# File : main_simplified.py
# explain : Simplified training script. Remove support for DDP, IMAGENET, Augment, etc.
import argparse
import time
import ... |
fd59a82269e5cbd1cdc8d35a006a4e2b5352788ff65a29050b68a8012b8941b3 | Python | 32,343 | 811 | import contextlib
import os
import pickle
import tempfile
import numpy
import pytest
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import COLTYPE_FLOAT, COLTYPE_INTEGER
import cellprofiler.modules.classifyobjects
import cellprofiler_core.object
impo... |
9c9ddcd186b45dcd821dd352e725ce173dfea87f962cb94a758b20dcb61171cf | Python | 32,374 | 823 | #!/public/EM/anaconda3/envs/relion-5.0/bin/python
import argparse
import math
import sys, os
from pathlib import Path
import numpy as np
import pandas as pd
import starfile
import torch
import torch.nn as nn
import torch.nn.functional as F
import mrcfile
import matplotlib
matplotlib.use("Agg") # non-GUI backend, no... |
077306461015f73d23b65947d63f291e6f96974982e4fff8ba40e9952be7e72c | Python | 32,422 | 693 | from numpy import identity
import torch
import torch.nn as nn
from torch.nn import init
import functools
from torch.optim import lr_scheduler
import math
###############################################################################
# Helper Functions
##################################################################... |
3fcfcd5c3db07ade233c861612180bc5efb3c8f0ced5a0dac1551b7e5bd07225 | Python | 32,511 | 738 | """This program provides a tool to complete a linear regression on nidm files"""
import csv
import os
from statistics import mean
import sys
import tempfile
import warnings
import click
import numpy as np
import pandas as pd
from patsy.contrasts import ContrastMatrix, Diff, Helmert, Sum, Treatment
from patsy.highlevel... |
a5101aee789ba6d863002fc3087f32402c26de65e97f77e1fde95e9a8dbf52d2 | Python | 32,554 | 983 | import os
import warnings
import numpy as np
import pdb2sql
from deeprank.features import FeatureClass
class AtomicFeature(FeatureClass):
def __init__(self, pdbfile, chain1='A', chain2='B', param_charge=None,
param_vdw=None, patch_file=None, contact_cutoff=8.5,
verbose=False):
... |
9ac57baff414e416aae68aeb3fc9cf73543e0ef5c805d37ec88bd5bd621ace3c | Python | 32,788 | 809 | """
Author: "Keitaro Yamashita, Garib N. Murshudov"
MRC Laboratory of Molecular Biology
This software is released under the
Mozilla Public License, version 2.0; see LICENSE.
"""
from __future__ import absolute_import, division, print_function, generators
import numpy
import scipy.optimize
import pandas
import gemm... |
12cb2af80bc737e15944ec205c02b8b9ac46b509b3e70b664b6f807b7ab862d8 | Python | 32,927 | 815 | import contextlib
import os
import tempfile
import numpy
import pytest
import six.moves
from cellprofiler_core.constants.measurement import COLTYPE_INTEGER
from cellprofiler_core.constants.workspace import DISPOSITION_CONTINUE, DISPOSITION_SKIP
import tests.frontend.modules
import cellprofiler_core.image
import cellp... |
7955e81edc184c2396b0928e7cc396657e94041b0fe773c98e6afce53044a2c7 | Python | 32,967 | 1,057 | import json
import sys
from abc import abstractmethod
from collections.abc import Iterable
from copy import copy
from importlib import import_module
from multiprocessing import cpu_count
from os import getcwd, linesep
from os.path import splitext
import numpy as np
from numpy import arange, split
from traitlets import... |
d3fad9dcc9944588ffac06846b19f3dac975890fe05232d7be98839e7a93d8f2 | Python | 33,183 | 799 | """ Relative Position Vision Transformer (ViT) in PyTorch
NOTE: these models are experimental / WIP, expect changes
Papers:
* `An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale` - https://arxiv.org/abs/2010.11929
* `Swin Transformer V2: Scaling Up Capacity and Resolution` - https://arxiv.org/... |
4f7b5da21510285f1c21e700f4dd13d833d850512b67c5cf4ddad6cd82c2bd31 | Python | 33,226 | 1,097 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 20 22:15:11 2019
@author: Nikolai M Chapochnikov
In this file are functions to simulate the original/default similarity
matching circuit as well as the olfactory circuit.
There are classes for the default similarity matching and the
olfactory circ... |
1e67ce1c298423e1e17ad60aa56f992237dd21ae2407f284c9630114e079b40e | Python | 33,326 | 689 | #!/usr/bin/env python
# MIT License
#
# Copyright (c) 2022 Matthis Ebel, Mario Stanke
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitat... |
0041f44afb0d3480eccd6915c9b666eebf9dea25005a656150e396f3ac263f0c | Python | 33,329 | 950 | import math
import torch
import pandas as pd
import pytorch_lightning as pl
from pathlib import Path
from typing import List, Optional
import torch.nn as nn
import torch.nn.functional as F
from torch.optim.lr_scheduler import OneCycleLR
from pysmilesutils.augment import SMILESAugmenter
from molbart.tokeniser import ... |
762287e34cef2112eaad63fed3d5938d4314bfd86144f881f13c1269aeaf4f6c | Python | 33,346 | 717 | import numpy
from ..constants.image import CT_OBJECTS
from ..constants.measurement import COLTYPE_INTEGER, COLTYPE_VARCHAR, IMAGE
from ..constants.measurement import C_FILE_NAME
from ..constants.measurement import C_METADATA
from ..constants.measurement import C_OBJECTS_FILE_NAME
from ..constants.measurement import C_... |
138edb7aa65cde7ee4a6aadb5a62789a0eb44a368009cd3aa7aefb1c78330d19 | Python | 33,369 | 923 | """ EfficientViT (by MSRA)
Papers:
* `EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention` - https://arxiv.org/abs/2305.07027
Adapted from official impl at https://github.com/microsoft/Cream/tree/main/EfficientViT
"""
__all__ = ['EfficientVitMsra']
import itertools
from collections import... |
e78cf9f4f96ad8436f1e702d9351d406fb5aa92305610cdd3622df94862c17da | Python | 33,490 | 739 | import math
import random
import string
from typing import List, Tuple
from Bio import SeqIO
import esm
import numpy as np
import pandas as pd
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch_cluster
import torch_geometric
import torch_scatter
from atom3d.datasets import LMDBDataset
from... |
6433459f10d958dae9b14e6f53d9d8b1317349ceb33f551c227ab4e9cac68004 | Python | 33,560 | 771 | from __future__ import print_function
import numpy as np
from collections import deque
from allensdk.core.brain_observatory_cache import BrainObservatoryCache
import allensdk.brain_observatory.stimulus_info as si
from scipy.ndimage.interpolation import zoom
import os
import sys
import copy
from scipy.ndimage.filters i... |
8d51ec793d30bee759324b6adf86c19fbc856a5d7f16124a91ee680b71618942 | Python | 33,567 | 962 | """ DaViT: Dual Attention Vision Transformers
Papers:
* `DaViT: Dual Attention Vision Transformers` - https://arxiv.org/abs/2204.03645
* `Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks` - https://arxiv.org/abs/2311.06242
Input size invariant transformer architecture that combines channel... |
03d605c6885e1a75a3e1dc70ffb70daf9b320c9608287e6fef6831be1ed4179c | Python | 33,596 | 969 | """ EfficientFormer-V2
Papers:
* `Rethinking Vision Transformers for MobileNet Size and Speed` - https://arxiv.org/abs/2212.08059
@article{
li2022rethinking,
title={Rethinking Vision Transformers for MobileNet Size and Speed},
author={Li, Yanyu and Hu, Ju and Wen, Yang and Evangelidis, Georgios and Salahi... |
0ed07e6e4c73b21eb7414861173c0975d2026938060adff4cc9d91ea8a93edb2 | Python | 33,659 | 891 | # The help text for various thresholding options whose code resides here is in modules/identify.py
from __future__ import absolute_import
from __future__ import division
import inspect
import math
import numpy as np
import scipy.ndimage
import scipy.sparse
import scipy.interpolate
from .otsu import otsu, entropy, ot... |
1efc1f0fdeac5969bd4027e185079707d51bbee8cfab70ddf58e93738ff76715 | Python | 33,710 | 991 | """Publication figures for the AFIDs Validator education paper.
Regenerates all five manuscript figures from source (the MNI human FCSV
templates and the cached MNI152NLin2009cAsym T1w volume). Outputs 300-dpi PNG
and vector PDF to paper_figures/.
python make_figures.py
The inter-template variability analysis (F... |
8020b15d44096fb9479f818036c6f1dbf760bb1310f297d2c799f6a6dc850d20 | Python | 33,755 | 913 | import os
import sys
import time
import logging
import h5py
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
import numpy as np
import warnings
import tempfile
import torch
import torch.cuda
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import tor... |
96bbb24e1a5a4c37266bac4f1a533e9d84d0a620be9dcc0a377fb781ce56e131 | Python | 33,817 | 1,033 | import functools
import numpy
import numpy.testing
import pytest
import six.moves
import skimage.util
import tests.frontend.modules
import cellprofiler_core.image
import cellprofiler_core.measurement
import cellprofiler_core.module
import cellprofiler.modules.imagemath
import cellprofiler_core.object
import cellpro... |
4180d0f54f990c03abfbd3a5e6632f7f38ddda8d318eae683908b039bbc9107e | Python | 33,926 | 849 | """ NaFlex (NaViT + FlexiViT) Transforms and Collation
Implements PyTorch versions of the transforms described in the NaViT and FlexiViT papers:
- NaViT: https://arxiv.org/abs/2307.14995
- FlexiViT: https://arxiv.org/abs/2212.08013
Enables variable resolution/aspect ratio image handling with efficient patching.
Hack... |
f3685f0a36252556580fad53671c82fa6c4b21d295e17610740c85ead5d5b8cd | Python | 33,964 | 794 | """DeepSeek Vision Transformer
Vision encoder of the DeepSeek-V4 / V4.1 multimodal models from DeepSeek-AI.
Papers:
* `DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression` - https://arxiv.org/abs/2609.19969
A plain pre-norm ViT with RMSNorm, fused QKV with bias, a bias-free SwiGLU MLP and axial 2D RoPE
(... |
b49869ea90b2d7a46ebd1d38b28617960c207138b692f34d8fda8d593c1a7a63 | Python | 34,105 | 734 | """
Author: Mingjian He <mh1@stanford.edu>
traditional module contains traditional methods for switching inference
"""
from somata.basic_models import StateSpaceModel as Ssm
from somata.exact_inference import forward_backward, logdet, inverse
import numpy as np
def switching(ssm_array, y=None, method='static', dwel... |
ff600ae2fede9417f898b0c74aae7ce9de0f8d86a8bc4e86489d59790faa5f92 | Python | 34,172 | 1,234 | import math
import centriole.outline
import numpy
import numpy.testing
import pytest
import skimage.measure
import skimage.segmentation
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import EXPERIMENT, COLTYPE_FLOAT, C_LOCATION
import cellprofiler.mo... |
c5f868739698ae155275b5530b03140848f0d3eba99440cb0b0d949bbf6811fb | Python | 34,175 | 855 | """
Crop
====
**Crop** crops or masks an image.
This module crops images into a rectangle, ellipse, an arbitrary shape
provided by you, the shape of object(s) identified by an **Identify**
module, or a shape created using a previous **Crop** module in the
pipeline.
Keep in mind that cropping changes the size of your... |
3ef7b3f1f28d3068eb82c8372475c977afba1700cfe4aa0ffe60337819f80431 | Python | 34,244 | 894 | """ MLP-Mixer, ResMLP, and gMLP in PyTorch
This impl originally based on MLP-Mixer paper.
Official JAX impl: https://github.com/google-research/vision_transformer/blob/linen/vit_jax/models_mixer.py
Paper:
* `MLP-Mixer: An all-MLP Architecture for Vision` - https://arxiv.org/abs/2105.01601
@article{tolstikhin2021,
... |
f72873879575b527b602e725e93546256e5166dc0e04b26530548b059fc52642 | Python | 34,278 | 788 | from __future__ import print_function
import numpy as np
from collections import deque
from allensdk.core.brain_observatory_cache import BrainObservatoryCache
import allensdk.brain_observatory.stimulus_info as si
from scipy.ndimage.interpolation import zoom
import os
import sys
import copy
from scipy.ndimage.filters i... |
350bd3ccce7e707265f05c9d7fb91100bc6cd898402183de6ae0bc0af054f175 | Python | 34,342 | 887 | """LowFormer
LowFormer: Hardware Efficient Design for Convolutional Transformer Backbones (WACV 2025)
- `LowFormer: Hardware Efficient Design for Convolutional Transformer Backbones` - https://arxiv.org/abs/2409.03460
- code: https://github.com/altair199797/LowFormer
@article{Nottebaum2024LowFormerHE,
title={LowForme... |
a72925e656831f7b9aa52848642f15ba93290f1a989b93b35652013b7b83d63f | Python | 34,554 | 930 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#
# Any... |
0e8f7c6dd70f71af88445dcc5a4b6c2c86972dcda5669127e2ba407548d76cb8 | Python | 34,632 | 842 | import numpy as np
import itertools
class gabor_wavelet_preprocessing_linquad:
def __init__(self,
stimulus,
movie_hz=30,
temporal_window=11,
spatial_frequencies=[0,2,4,8,16],
temporal_frequencies=[0,2,4],
simpl... |
fbe4a9d96e895fc27e53f0ea9e98cff230f464f10edef1f342b95c4bbd8b3d2c | Python | 34,759 | 765 | # -*- coding: utf-8 -*-
"""
@author: bartulem
Compute cluster quality measures for 'good' and 'mua' clusters.
This script computes various cluster quality measures for clusters
labeled as 'good' or 'mua' in the cluster_info.tsv file. Measures include
various waveform metrics (SNR, spike duration, FWHM, PT-ratio), c... |
f3fbaf20191c1d07e67428899a159eeca6c522282968882fa7f0f953d2cfcec6 | Python | 34,794 | 979 | import io
import centriole.threshold
import numpy
import cellprofiler_core.image
import cellprofiler_core.measurement
from cellprofiler_core.constants.measurement import COLTYPE_FLOAT, EXPERIMENT
from cellprofiler_core.constants.module._identify import O_FOREGROUND, O_THREE_CLASS, O_WEIGHTED_VARIANCE, O_TWO_CLASS, \
... |
43454f848f527909647e5b4cc2949bbc2890aa8f36363792116bd03ed947cd89 | Python | 34,814 | 863 | """
Author: "Keitaro Yamashita, Garib N. Murshudov"
MRC Laboratory of Molecular Biology
This software is released under the
Mozilla Public License, version 2.0; see LICENSE.
"""
from __future__ import absolute_import, division, print_function, generators
from servalcat.utils import logger
from servalcat.utils impo... |
859bf441abf8fb1f236efe3e0ea23d5e4282818c353f45a940d6c6c587d6141f | Python | 34,856 | 671 | import random
import sys
import math
import numpy as np
import damask
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from PIL import Image, ImageOps
import time
from dragen.generation.DiscreteRsa3D import DiscreteRsa3D
from dragen.generation.DiscreteTesselation3D import Tesselation3D
from dr... |
a90abe64ee95e0e2fc589b1bc86e2c9ef90f5aa57b07c2961bdbb03b79c942e3 | Python | 34,869 | 863 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
47ce957320cf7d0168575fb0187f3d1868acf72cbf22471379866165147454ce | Python | 34,926 | 971 | import math
import torch
import pandas as pd
import pytorch_lightning as pl
from pathlib import Path
from typing import List, Optional
import torch.nn as nn
import torch.nn.functional as F
from torch.optim.lr_scheduler import OneCycleLR
from pysmilesutils.augment import SMILESAugmenter
from molbart.tokeniser import ... |
2af7b930a05fc7111929bb5872dc4374177dce492be4624e0e3db0608bded4fe | Python | 35,000 | 725 | import os
import pandas as pd
import numpy as np
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt
from matplotlib import gridspec
import matplotlib.transforms as transforms
from matplotlib.colors import LinearSegmentedColormap
from matplotlib import cm
from matplotlib.colors import List... |
0d4ac6f4374e4538bb32ae120da0295e9bbe962d922f3928cb2912db007ee8bc | Python | 35,054 | 900 | """CSATv2
A frequency-domain vision model using DCT transforms with spatial attention.
Paper: TBD
This model created by members of MLPA Lab. Welcome feedback and suggestion, questions.
gusdlf93@naver.com
juno.demie.oh@gmail.com
Refined for timm by Ross Wightman
"""
import math
import warnings
from functools import ... |
026b923a7f047c42623306483ba578404a6b838892030ff2624ffbb3d47a6c9f | Python | 35,076 | 1,006 | # This file is part of pyunicorn.
# Copyright (C) 2008--2026 Jonathan F. Donges and pyunicorn authors
# URL: <https://www.pik-potsdam.de/members/donges/software-2/software>
# License: BSD (3-clause)
#
# Please acknowledge and cite the use of this software and its authors
# when results are used in publications or publi... |
0892d76ea42cc8d64c94cfcf49dc485428e08a9b709fc7d56d96a0e5c913a41d | Python | 35,122 | 698 | import logging
import pytorch_lightning as pl
import torch
import numpy as np
import pandas as pd
from torchvision.transforms import (
Compose,
)
from pytorch_lightning.loggers import TensorBoardLogger
from utils import get_model_by_name
import torch.nn.functional as F
from dataset import COPDGeneSubtyping, Subtypi... |
701a598c5144e57ca5fabbe39289e6aa58ad1c4000b023122ddab5212ef0b289 | Python | 35,139 | 826 | # -*- coding: utf-8 -*-
import datetime
import numpy as np
import pytest
import pysteps
from pysteps import blending, cascade
# fmt:off
steps_arg_values = [
(1, 3, 4, 8, 'steps', None, None, False, "spn", True, 4, False, False, 0, False, None, None, None),
(1, 3, 4, 8,'steps', "obs", None, False, "spn", Tru... |
317c698daa841a956ff9054d1161c5d96eeeedb4b9e3d87ddb588b9257bfeae4 | Python | 35,243 | 882 | import numpy
import scipy.ndimage
from cellprofiler.modules import _help, threshold
from cellprofiler_core.constants.measurement import (
FF_CHILDREN_COUNT,
FF_PARENT,
FTR_CENTER_Z,
FTR_CENTER_Y,
FTR_CENTER_X,
C_LOCATION,
C_NUMBER,
FTR_OBJECT_NUMBER,
C_PARENT,
C_CHILDREN,
C... |
17e88bae22f862d0a447084323d4561561dc5e64694ab183c40ee5009669eabe | Python | 35,256 | 843 | """ NasNet-A (Large)
nasnetalarge implementation grabbed from Cadene's pretrained models
https://github.com/Cadene/pretrained-models.pytorch
Papers:
* `Learning Transferable Architectures for Scalable Image Recognition` - https://arxiv.org/abs/1707.07012
"""
from functools import partial
from typing import List, Opt... |
2e6109fee84a809b9e6db1626d2a1d28fa040983f3b8c207f52042855e8afc65 | Python | 35,266 | 994 | """iFormer
iFormer: Integrating ConvNet and Transformer for Mobile Application (ICLR 2025)
- `iFormer: Integrating ConvNet and Transformer for Mobile Application` - https://arxiv.org/abs/2501.15369
- code: https://github.com/ChuanyangZheng/iFormer
@inproceedings{zheng2025iformer,
title={iformer: Integrating convnet a... |
69e2bb802d43c6783d22a05b0dd918383ce8026107df4c008e9a6e310a2f5fbc | Python | 35,307 | 859 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 19 10:04:52 2022
@author: obernauer
"""
import os
import random
import pickle
import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow import keras
from tqdm import tqdm
from stm import STM
import matplotlib
from ... |
9ab73bb2dbd89d32225597d5ee65fbad323b624a1b871e51623bdb5cdb7ee34e | Python | 35,463 | 990 | import io
import json
import os
import tempfile
import cellprofiler_core.constants.measurement
import cellprofiler_core.constants.modules.images
import cellprofiler_core.constants.modules.metadata
import cellprofiler_core.measurement
import cellprofiler_core.modules.images
import cellprofiler_core.modules.metadata
imp... |
23d0eaa9b39dce7cc8c5c141042d506d4eccb54969f809b7a4516de13df61369 | Python | 35,800 | 619 | #### Master Script 05c: Calculating TimeSHAP for dynAPM_DeepMN models in parallel ####
#
# Shubhayu Bhattacharyay
# University of Cambridge
# email address: sb2406@cam.ac.uk
#
### Contents:
# I. Initialisation
# II. Calculate testing set TimeSHAP values based on provided TimeSHAP partition row index
### I. Initialisat... |
ab4e86988b2fdfbc914a31a0cb3aef573b63ef2615df9d9a0770b9fcd86bd26c | Python | 35,803 | 990 | # -*- coding: utf-8 -*-
"""
pysteps.io.exporters
====================
Methods for exporting forecasts of 2d precipitation fields into various file
formats.
Each exporter method in this module has its own initialization function that
implements the following interface::
initialize_forecast_exporter_xxx(outpath, out... |
e366c0aaf9d99c0e1d8155d8456f07570d0f937e1acf67e3bd6c818baffd88ea | Python | 35,822 | 1,003 | # Usage
#
# (c) TGEN 2020
# requires python 3.0 with pandas, numpy, pysam packages
#
#
print("Importing Packages")
# Configure Enviroment
import pandas as pd
import numpy as np
import pysam
import sys
import os.path
import re
import argparse
from subprocess import call
import itertools
# Variables
minimum_count_thre... |
9a9759f5c71af6381c715371f45c0454b45fde50887b3b13866b5ddd0054e518 | Python | 35,909 | 998 | """ AutoAugment, RandAugment, AugMix, and 3-Augment for PyTorch
This code implements the searched ImageNet policies with various tweaks and improvements and
does not include any of the search code.
AA and RA Implementation adapted from:
https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/au... |
535c0698286b37d3a66fb885f5413c516a696390b24ec97ffb7bcf1d2923731e | Python | 36,262 | 1,098 | #!/usr/bin/python3
def inv_rank(m, tol=1E-8, method='auto', logger=None, mpc=0, qr=0, **ka):
"""Computes matrix (pseudo-)inverse and rank with SVD.
Eigenvalues smaller than tol*largest eigenvalue are set to 0. Rank of inverted matrix is also returned. Provides to limit the number of eigenvalues to speed up computa... |
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