sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
beb05cee1612f1b4e4e6fa8d16e4a56ee8221ba3b055af4c0ed02ab384ad7a60 | Python | 8,163 | 232 | """ Multi-Head Attention module """
import math
import torch
import torch.nn as nn
from bioseq2seq.utils.misc import generate_relative_positions_matrix,\
relative_matmul
# from bioseq2seq.utils.misc import aeq
class MultiHeadedAttention(nn.Module):
"""Multi-Head Attention module from "... |
4e64d4744d032c8bfac41395210f84c8dace84977caafc2d26cb985e2804cae1 | Python | 8,165 | 277 | """Pytorch communication tools"""
import functools
import logging
import pickle
import numpy as np
import torch
import torch.distributed as dist
def get_world_size():
"""Get DDP world size"""
if not dist.is_available():
return 1
if not dist.is_initialized():
return 1
return dist.get_wor... |
cc98a07fa79229bf941b0c38ab8e5e1c110dbc87b67852398940851d77fd6226 | Python | 8,167 | 209 | """
This script takes plink LD lists and simulates summary statistics for multiple populations with sample size imbalance.
Requires 2 populations, can take up to 4.
"""
import argparse
from contextlib import ExitStack
import numpy as np
import scipy.stats as stats
import os
class Main():
def __init__(self):
se... |
5abb31b7fd0621f56538af6e7ed2d2042db6fb5e7729d31de918be501b570cf0 | Python | 8,170 | 220 | """
Behavioural phenotypes (rover / sitter) derived from the generic Drosophila DEB model.
The generic model is the species-specific AmP parameter set for
*Drosophila melanogaster* -- ``models/amp/Drosophila_melanogaster.json``, taken
verbatim from the Add-my-Pet database. It stands for the average representative
indi... |
5da44151b2a3dcef3494fc576440ed346e4d550850787193fcbf57c1101c3ac7 | Python | 8,173 | 130 | """General-purpose training script for image-to-image translation.
This script works for various models (with option '--model': e.g., pix2pix, cyclegan, colorization) and
different datasets (with option '--dataset_mode': e.g., aligned, unaligned, single, colorization).
You need to specify the dataset ('--dataroot'), e... |
a541e4e532fe6f5dfb2c58a971a886a33f072495a461aba0ab4b6f91b7641b3f | Python | 8,173 | 209 | """F12 pins: live skin palettes (N4), ramps, the N17 neutral fill, and the
CVD accessibility gates.
FORK-2 discipline: the machinery is LIVE but every shipped skin keeps
pixel-identical palettes (the render-identity golden pins them); the
Okabe-Ito set ships as data with its accessibility evidence attached, and
the le... |
ef30bc929a61248e693f943d4ca9288c18e7a9b084f5597d7b7c3159eb449cb1 | Python | 8,174 | 215 | """4. Dive Deep into Training I3D mdoels on Kinetcis400
=======================================================
This is a video action recognition tutorial using Gluon CV toolkit, a step-by-step example.
The readers should have basic knowledge of deep learning and should be familiar with Gluon API.
New users may first... |
01551ab6d88809fa8cf8ebdb8d455725ad7dc81e28a9adefd56b86123206a423 | Python | 8,176 | 220 | """A Sphinx extension for linking to your project's issue tracker.
Copyright 2014 Steven Loria
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 limitation th... |
17e7a8cc8948dde4e4782d3f454ed52b3846030c883df1f699027e2ff535d9a4 | Python | 8,177 | 130 | """General-purpose training script for image-to-image translation.
This script works for various models (with option '--model': e.g., pix2pix, cyclegan, colorization) and
different datasets (with option '--dataset_mode': e.g., aligned, unaligned, single, colorization).
You need to specify the dataset ('--dataroot'), e... |
1650cd02606240449264b3960bcc9e1a739ea214efa8f4971e03de6c5efb7a17 | Python | 8,181 | 174 | # Third party libraries imports
import matplotlib.pyplot as plt
import numpy as np
from numpy.lib.arraysetops import isin
import torch
from torch.functional import split
import torch.nn as nn
import torch.fft
import torch.nn.functional as F
import pathlib, glob, re
import logging
import FrEIA.framework as Ff
import FrE... |
14e63555b10c8abf3999de0f43618db822bcf38d852b1afe8ecf41f2e2bfe6cc | Python | 8,182 | 227 | import torch
from tqdm.auto import tqdm
from .._settings import settings
import xarray as xr
import numpy as np
from tqdm.auto import tqdm
from seqexplainer.gia._perturb import tile_pattern_seq
from seqexplainer.gia._complex_perturb import embed_deepstarr_distance_cooperativity
from seqexplainer.gia._gia import deepsta... |
310967192eae3f5f5eacad8908d3b2418a18caaba4dcf003aeaaeb8a7aaa2ed0 | Python | 8,184 | 221 | from distutils.util import convert_path
from distutils import log
from distutils.errors import DistutilsError, DistutilsOptionError
import os
import glob
import io
from setuptools.extern import six
import pkg_resources
from setuptools.command.easy_install import easy_install
from setuptools import namespaces
import s... |
7e2028910a8cd788e63657959eeef4ca893bddee6796da2f196f9d2eddbc0e2b | Python | 8,184 | 184 | """
Tests for independence_tests.py.
"""
from __future__ import print_function
import numpy as np
import pytest
from scipy import stats
from tigramite.independence_tests.parcorr import ParCorr
from tigramite.independence_tests.robust_parcorr import RobustParCorr
from tigramite.independence_tests.pairwise_CI import Pai... |
b0ae9a56f063f22b8df60d62e42727e80b62605da2d5be0e250f1005495a1f5b | Python | 8,184 | 223 | """Functions for generating boilerplate code."""
from xcp_d.utils.confounds import _modify_motion_filter
from xcp_d.utils.doc import fill_doc
from xcp_d.utils.utils import list_to_str
@fill_doc
def describe_motion_parameters(
*,
motion_filter_type,
motion_filter_order,
band_stop_min,
band_stop_ma... |
f5b8ecb6209181c4c781f1ff045272bab41716ae69ac0d5264f0341ed0125767 | Python | 8,185 | 207 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
@author: Pramod Bharadwaj Chandrashekar
@email: pchandrashe3@wisc.edu
"""
import torch
import pandas as pd
import numpy as np
import argparse
from captum.attr import IntegratedGradients, LayerConductance, NeuronConductance
from torch.utils.data import TensorDataset, Da... |
2937ba2aa829d2ede2d34efd2bd5ab11c481a8d391348ddde9a366cde3984bf1 | Python | 8,186 | 217 | from typing import Dict, List, Optional, Tuple, Union
from PIL.Image import Image
from torch import Tensor
from lightly.transforms.gaussian_blur import GaussianBlur
from lightly.transforms.multi_view_transform import MultiViewTransform
from lightly.transforms.rotation import random_rotation_transform
from lightly.tra... |
f39b86071d1d41c0c0161d3ca9db81675fa4b79850374d14bb50f8e72a32c46d | Python | 8,186 | 200 | # adapted from https://github.com/facebookresearch/detectron2/blob/master/detectron2/data/samplers/distributed_sampler.py
import itertools
import math
from collections import defaultdict
from typing import Optional
import torch
from torch.utils.data.sampler import Sampler
from ....utils import comm
class TrainingSam... |
25d3b076cf600ad3a7bb015621c0bff62df8ddb44a322f28d1e3243cb46bedce | Python | 8,187 | 162 | """Shared closed-grammar sanitizer for attacker-controlled portable device strings.
A ``.tlspec`` manifest is *data*, not authority: a hostile artifact may carry any
bytes in the plaintext ``manifest.json`` ``logical_device`` / ``device_at_save``
fields. Round 54 ``sec_2`` (HIGH) showed the tinygrad payload codec pass... |
1ec159cdf88b35d43887e9ebac82f989cd6abb1e9a560a37bad1d924db574d61 | Python | 8,188 | 210 | #!/usr/bin/env python3
import argparse
import datetime
import json
import re
import sys
from pathlib import Path
from typing import Any, Dict, List
def get_opencc_version() -> str:
try:
script_dir = Path(__file__).resolve().parent
repo_root = script_dir.parent
package_json_path = repo_root... |
78adfeee605ca07f6141057b1034d99c8ca28efe2f58e25b4004d3767b0a28d7 | Python | 8,193 | 246 | import torch.utils.data as data
from torch.utils.data import Dataset
from torchvision import transforms
from PIL import Image
import os
import os.path
import sys
def has_file_allowed_extension(filename, extensions):
"""Checks if a file is an allowed extension.
Args:
filename (string): path to a fil... |
9811d2027006fa395b8d6e1653979271d0a18e8a50dbb269b8b11632f5a7f896 | Python | 8,195 | 198 | """F11 ceiling-replacement gates (collapse memo item 8 / D5).
Admission is U-gated and estimator-tiered; over-budget requests degrade to
the deterministic fallback planner, never an uncollapsed wall; the watchdog
abandons only TO the fallback and is disclosed as an estimator bug.
"""
from __future__ import annotation... |
814b3517318683c25354c1577ac340b5e68a88dbc7877843fd8fbaa0eb47abe1 | Python | 8,197 | 189 | # ------------------------------------------------------------------------------
# Based on:
# apex
# Copyright (c) NVIDIA
# Licence under The BSD 3-Clause "New" or "Revised" License
# https://github.com/NVIDIA/apex
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modificati... |
f852052be71098726b0f3ee0afbe6aaf1654fc49c014fbbc6d51da9d55b4f7b1 | Python | 8,198 | 264 | import io
import gc # garbage collector
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
import numpy as np
import PIL
def get_cmap(colors=None, classes=None, epsilon: float = 1e-2, framing_color: str = 'white', plot: bool = False):
"""
Creates a colormap from gi... |
84cf7f1eced72184ecd16ae47610decd9409fe0bd961b6ccdd597b760778f8bc | Python | 8,201 | 228 | """Scripts for visualization"""
from collections import Counter
import io
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
from scripts.utils.constants import CSV_ORG_OVERVIEW
from scripts.utils.io_utils import get_masks, get_orig_imgs
from scripts.u... |
887475df427accedecd4385d4158367807c052183c5f0834748ac83ba2172a71 | Python | 8,201 | 197 | """
Based on the fMRI scripts used in Kell et al. 2018 with minor changes.
"""
import h5py
import numpy as np
import pickle
import sklearn
from sklearn import *
import scipy
import os
def compute_median_across_predictions(combine_predictions):
"""
Computes a summary median metric from a set of predictions ... |
d0cb1611a0431bdb06d2b74075523b2ac7cc8a3e1f60914087a0dc1651c48927 | Python | 8,201 | 248 | #!/usr/bin/env python
"""
sess_download_util.py
This module contains functions for downloading the dataset from the Dandi
archive.
Dandiset 000037 is the Credit Assignment Project dandiset. It comprises data
for 50 sessions. The asset (session file) sizes are in the following ranges:
- Basic data (with everything ... |
4ed4bf264e679a2bfe8c0ac721638e07e83d41054b6447de09b3e4e382308401 | Python | 8,202 | 230 | # SOURCE: vendored from xbpeng/MimicKit @ main
# https://raw.githubusercontent.com/xbpeng/MimicKit/main/mimickit/learning/ppo_model.py
# https://raw.githubusercontent.com/xbpeng/MimicKit/main/mimickit/learning/nets/fc_2layers_1024units.py
# https://raw.githubusercontent.com/xbpeng/MimicKit/main/mimickit/learning/distri... |
d2122c8eb3bda3a644b87d300ed62747fbe0d606d2eff66880e41b5d4df51056 | Python | 8,203 | 242 | import os
import re
import shutil
import statistics
import subprocess
import sys
import time
from functools import lru_cache
from typing import Dict
from codecarbon.core.util import detect_cpu_model
from codecarbon.external.logger import logger
@lru_cache(maxsize=1)
def is_powermetrics_available() -> bool:
try:
... |
2622879cc7e23aabbe26de47e85060ff71ddaca5552aa75e0850d0b949291d67 | Python | 8,205 | 190 | from __future__ import generators
import logging
import glob, os, functools
import sys
import SimpleITK as sitk
from scipy.signal import medfilt
import numpy as np
from numpy import median
import scipy
import nibabel as nib
import skimage
import matplotlib.pyplot as plt
import scipy.misc
from scipy import ndimage
from... |
b3d868c37538b35bfa636e1a36c1ee720103f504f984e3d5f7ad5258c7ed2ead | Python | 8,205 | 244 | # Allen Institute Software License - This software license is the 2-clause BSD
# license plus a third clause that prohibits redistribution for commercial
# purposes without further permission.
#
# Copyright 2019. Allen Institute. All rights reserved.
#
# Redistribution and use in source and binary forms, with or withou... |
c5b66767228abad15a9dfee9732897a86a234167f8ff4fab3e53c6dadf862a94 | Python | 8,206 | 218 | #!/usr/bin/env python
# =============================================================================
# MODULE DOCSTRING
# =============================================================================
"""
Test objects and functions in tfep.nn.conditioners.masked.
"""
# =============================================... |
2adfc8ab14e95959017259681b4febadefc2281c5c8694e49b2f3dda8a32b1b1 | Python | 8,207 | 183 | """
Simulating Neural Power Spectra
===============================
Creating simulated power spectra.
"""
###################################################################################################
# Import functions for creating simulated power spectra
from specparam.sim import sim_power_spectrum, sim_group... |
76cf5a0b13fb02515f4c887d8d9e1def7977513e27e1326cb8bf9b9acf0d1d7b | Python | 8,207 | 188 | """
This module is largely responsible for impainting the distance map,
a.k.a. removing possible undefined values inside the image.
"""
import scipy.sparse
import numpy
class NanInpainter():
"""
This module is a Python-port of the inpaint_nans in MATLAB from
John d'Errico:
https://www.mathworks.com/ma... |
4387e37049cd388e8e762c797783408bb8278869cd1ad72cc8d3619cf7363641 | Python | 8,208 | 239 | # Register stacks/collections of images
import itertools as itt
from functools import partial
import numpy as np
from imfun import core
from imfun import fseq
try:
from pathos.pools import ProcessPool
_with_pathos_ = True
except ImportError:
print("""Can't load `pathos` package, parallel maps won't work.... |
75220f3808fe78134cd219fc4857eeaf1f8eb53b482584636c77403458f5eab4 | Python | 8,208 | 198 | # Sentence model specification - CUB image feature version
import json
import os
import numpy as np
import torch
import torch.distributions as dist
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
from torch.utils.data import DataLoader
from src.datasets import CUBSentences
from src.utils... |
ab0a2aed58a8a97e576b379b4cd8ccba48fa6ae86cd0688301484cc56d345fcf | Python | 8,208 | 215 | # LICENSE
#
# _This file is Copyright 2018 by the Image Processing and Analysis Group (BioImage Suite Team). Dept. of Radiology & Biomedical Imaging, Yale School of Medicine._
#
# BioImage Suite Web is licensed under the Apache License, Version 2.0 (the "License");
#
# - you may not use this software except in complian... |
7522bbb0768d7d9076a5a1cba80de46cfe4f24e73f4272a26e2329ccdff26d8b | Python | 8,209 | 199 | # Sentence model specification - real CUB image version
import os
import json
import numpy as np
import torch
import torch.distributions as dist
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.data
from torch.utils.data import DataLoader
from src.datasets import CUBSentences
from src.utils im... |
e5ed4196f9bc1ad90d9f72e80ce6d137d4c72514555609a9e0e16dd1e8750093 | Python | 8,209 | 273 | """Utilities for safely pickling exceptions."""
import datetime
import numbers
import sys
from base64 import b64decode as base64decode
from base64 import b64encode as base64encode
from functools import partial
from inspect import getmro
from itertools import takewhile
from kombu.utils.encoding import bytes_to_str, saf... |
1ba5316a3d038275373dbec0587458c71eec342730b308f862d9769734f79483 | Python | 8,213 | 180 | """
In the main, you need to configure experiment name, decay times, decay distributions and model folder by hand.
This script generates the folder structure for the entire analyzer skripts and compute the spike rates by calling spikerate_kfold_multi().
"""
import os
from copy import deepcopy
import numpy as np
import... |
6893cdc546ebd4d948e6945ff5c263a53c088b42fc0fea58cf767329a27c002c | Python | 8,213 | 223 | import math
from collections import OrderedDict
from torch import nn
import torch.utils.model_zoo as model_zoo
from .custom_modules import SequentialWithArgs, FakeReLU
HASH = '1d3f7974'
class Flatten(nn.Module):
"""
Helper module for flattening input tensor to 1-D for the use in Linear modules
"""
... |
82a26c3503845f487e531a56b34f1a43bb8ddafa80f8456fff8cc039dfa7e3d2 | Python | 8,217 | 229 | import os
os.environ['DTORROOT'] = '/DATA/forLishan/randomddd'
#os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from dtor.utilities.utils_stats import stats_from_results,roc_and_auc
from sklearn.metrics import roc_curve, auc
import numpy as np
import argparse
import torch
from dtor.utilities.utils import set_plt_config
from d... |
b758eed7e8a8e0a59ea2ded744f2ede4de37c1db7d2d42115dd84ec13dfc03fd | Python | 8,218 | 235 | #!/usr/bin/env python
import argparse
from collections import namedtuple
import os
import socket
import sys
from time import sleep
import threading
import SocketServer
import external_image
import nibabel as nb
import numpy as np
from sklearn.externals import joblib
SocketServer.TCPServer.allow_reuse_address = Tru... |
557132c296b8bb49b176d9d82b45213368a5d0655a06a4e857fe1f6324fed0e6 | Python | 8,219 | 229 | from unittest.mock import MagicMock, Mock, sentinel
from urllib.parse import urlparse
import pytest
from kombu.utils.encoding import str_to_bytes
from celery import states, uuid
from celery.app import backends
from celery.backends import couchdb as module
from celery.backends.couchdb import CouchBackend
from celery.e... |
05b540f80c1938e4fccde317e9575edcb4e2d1ee5f8932a2eba9c5563cbef74d | Python | 8,220 | 230 | # ---
# jupyter:
# jupytext:
# formats: ipynb,py:light
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.14.5
# kernelspec:
# display_name: Python 3 (ipykernel)
# language: python
# name: python3
# ---
# # Deconvol... |
f45f559eefd222f7c35fafa8b771d3289b49bb72c97f433647255cbc4af0f6ea | Python | 8,222 | 214 | # Copyright 2019 Novartis Institutes for BioMedical Research Inc. 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... |
d9bd133732a6fe15be3fa5317f98be67176ca49d16a13d3ceea67dee5cb689ae | Python | 8,224 | 204 | """Class to collect all TMD related info used in TNS"""
import copy
from collections import OrderedDict
import numpy as np
from tns.basic import round_num
from tns.utils import TNSError
class Barcode:
"""Class to generate the barcode structure
which is essential for the TMD based growth
algorithms.... |
17f45c61c230b1b674b2691c2addef5158ee7a82b3a8a811ad96a78ccc75ce23 | Python | 8,226 | 211 | # FAITHFUL REIMPLEMENTATION from Krishnamoorthi, "Quantizing deep convolutional
# networks for efficient inference: A whitepaper" (arXiv:1806.08342, 2018);
# Jacob et al., "Quantization and Training of Neural Networks for Efficient
# Integer-Arithmetic-Only Inference" (CVPR 2018); and Howard et al., "Searching
# for Mo... |
59eea9bd9a395a4fc211216a9ff3860aac680edea08d707d529dcda1839d5515 | Python | 8,226 | 169 | """
Perform cross-validation of regression between brain response and feature vectors under different setups.
"""
import sys
sys.path.append('..')
from config import fname, subjects
from doit import get_var
DOIT_CONFIG = dict(verbosity=2, sort='definition')
tr = get_var("tr", -1)
cum = get_var("cum", -1)
tc = get_var... |
608a99b4d762796447bf39f779334191b1dac5bd6104221273a9de031ae0e603 | Python | 8,227 | 226 | #!/usr/bin/env python3
# pylint: disable=invalid-name
import csv
import os
import subprocess
import tarfile
import unicodedata
from glob import glob
from multiprocessing import Pool
import progressbar
from deepspeech_training.util.downloader import SIMPLE_BAR, maybe_download
from deepspeech_training.util.importers im... |
a6e1d9f9f8d9691b57cf744fb2af23ece3a6079aad7084a258045353dd69f7f4 | Python | 8,227 | 264 | import numpy as np
import seaborn as sns
from .. import settings
from os import PathLike
import matplotlib.pyplot as plt
from sklearn.metrics import (
confusion_matrix,
roc_curve,
auc,
precision_recall_curve,
average_precision_score,
)
from typing import Union, Sequence
from sklearn.preprocessing im... |
f1b7800105b1634e0a07c44908ef1beb437f69a5df7162917c697809d8076b10 | Python | 8,227 | 244 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Nov 24 17:11:46 2022
@author: Audrey Mazancieux
This script performes group-level "event-related" analyses. Prior steps are:
- extraction of time series from the LC in native space using the
extract_timeSerie_singleSubj script
- extracti... |
316d64d21ad441310d49aca8eaf4293fd50e3a8513879096edcc6134275be4dc | Python | 8,228 | 193 | """F29: the two gallery transcripts, byte-reproducible (the lane's row gate).
Transcript 1 (flagship, MCP-shaped): gpt2 clean vs middle-block-ablated --
the agent recovers the KNOWN intervention boundary and the direction of
downstream change from two real artifacts without executing code, parsing
prose, or receiving ... |
0656ff25b900f97d3d2d33f849e15228f5937545f2174948b91a90732fe4b025 | Python | 8,230 | 225 | import numpy as np
import torch
import torch.nn as nn
from torch.autograd import grad, Variable
import pandas as pd
from sklearn.preprocessing import StandardScaler
def data_preprocessing(data_name, data_dir, device):
df = pd.read_csv(data_dir+data_name+".csv")
time_column = df.columns[0]
data_column... |
cd3f12cd9225565306fbb9dc507c0d1983b82fed316bed5bd2e95bb65f03e248 | Python | 8,230 | 239 | """Regression coverage for raw and transformed transform storage."""
from pathlib import Path
from typing import Any
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens.options import CaptureOptions, SaveOptions, StreamingOptions
class _TinyModel(nn.Module):
"""Small model wit... |
2d192535c7419899af27052832e2cc274946ccf3553d515fc2d4ebd496c5ac51 | Python | 8,232 | 224 | #!/usr/bin/env python3
"""
File: filter_vcf_files.py
Created: 2024/01/19
Last Changed:
Author: M.Vochteloo
Copyright (C) 2020 University Medical Center Groningen.
A copy of the BSD 3-Clause "New" or "Revised" License can be found in the
LICENSE file in the root directory of this source tree.
"""
... |
b6f62939f8c1f018ad870a62785d94debd50b752bc384c2398cd7012a8b2d9bd | Python | 8,232 | 195 | __author__ = 'quentin'
from .tracking_unit import TrackingUnit
import logging
import traceback
import json
from ethoscope.utils.description import DescribedObject
class Monitor(DescribedObject):
_description = {"overview":
"""
A monitor orchestrates the different software modules
and implements the... |
c632dc37ddf3ca8f328e8f234b065e3164a4f8062e818c8a04bc125a59a3eef9 | Python | 8,234 | 263 | # -*- coding: utf-8 -*-
#
# face-rhythm documentation build configuration file.
#
# For the full list of configuration options, see
# https://www.sphinx-doc.org/en/master/usage/configuration.html
from __future__ import annotations
import os
import re
import sys
import types
from datetime import datetime
from pathlib ... |
460736addb04bfae0aeee0a982359478fa1c15a1b2889a8a0979790eea8a2967 | Python | 8,235 | 158 | """C.4: инфраструктура теста порядка развития (решающий критерий этапа 3).
Интернализация по Выготскому требует, чтобы у агента момент, когда его метки
начинают влиять на ДРУГИХ, наступал РАНЬШЕ момента, когда его собственные
метки начинают влиять на НЕГО САМОГО (STAGE3_DESIGN §3).
Меряем две кривые как функцию возра... |
16ee90678c482581ed288858f79a8746519a61a173fd84a74559ded5495eaf00 | Python | 8,239 | 235 | """C02 safety tranche: bounded reprs, honest units, coherent index bases.
Lane C02 (2026-08-27), M(lovely) item 1 -- the measured bug sites:
the Recording auto-repr that OOMed an 8 GiB box at four saved sites (bug 1),
the doubled duration unit (bug 2), auto-reprs on run products (bug 9),
Bundle's quoted-'None' baselin... |
1afa64f44636d3229a31388a81067cc85104a6876a560558b5f7a4a2273562db | Python | 8,239 | 301 | # This file is dual licensed under the terms of the Apache License, Version
# 2.0, and the BSD License. See the LICENSE file in the root of this repository
# for complete details.
from __future__ import absolute_import, division, print_function
import operator
import os
import platform
import sys
from setuptools.exte... |
2065679c43e870537bc2a0ecc1799039d0139172f6b0f08c50d4367d6b569f23 | Python | 8,239 | 258 | #!/usr/bin/python3
import os
import numpy as np
from biomedisa.features.biomedisa_helper import unique
from biomedisa.matching import assign_labels, remove_small_particles2
from platformdirs import user_data_dir
from pathlib import Path
from tqdm import tqdm
import requests
import time
biomedisa_dir = Path(user_data_d... |
367ddf7168d0fed788ba4e55ac455973cb2fe727a48ce5c5ba4f6947122dee96 | Python | 8,241 | 220 | """Tier T4: headless-browser semantic smoke over the served artifact (D-09).
The ONLY layer that catches the silent-hang class (the function-cycle crash
shows an error dialog, renders nothing, and logs NOTHING to the console)
and the panel-content class (the ``module`` name collision was invisible
until a real click o... |
9631f289fffa1a4550e5c28b47c5b4fae12835cea768716de01f6a5882950e0e | Python | 8,242 | 176 | import os, sys
import numpy as np
from tifffile import imread
from biomedisa.features.biomedisa_helper import *
import numba
@numba.jit(nopython=True)
def assign_labels(ref, result, labels_matrix):
zsh, ysh, xsh = ref.shape
for z in range(zsh):
for y in range(ysh):
for x in range(xsh):
... |
9835fc33fc520e46b70598f00af798014c65416c8cee660090db79bc6202e935 | Python | 8,242 | 259 | # -*- coding: utf-8 -*-
"""
Created on Tue Jan 25 16:34:41 2022
@author: Andrea Bassi @ Polimi
"""
from qtpy.QtWidgets import QLabel, QFormLayout, QSpinBox, QDoubleSpinBox, QCheckBox, QComboBox
from qtpy.QtCore import Qt
from enum import Enum, EnumMeta
class Settings:
"""
Auxiliary class to create an numeric... |
1133cff1db5f95f6ffc0bf43b02ec718be6f43ffbfe3efebbc10b8e9e9d8807e | Python | 8,243 | 218 | import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.utils.data
from src.getdata import getdata_from_csv, get_cold_data_from_csv
from src.utils import DrugTargetDataset, collate, AminoAcid, ci
from src.models.DAT import DAT3
import random
parser = argparse.ArgumentParser()
parser.add_argu... |
694ebd048baed925a569593dbd1ac6d4547a8030cdff34985cdfe20e6e8ffb7b | Python | 8,243 | 205 | '''
Sweep of hyperparams
* Bajar el número de iteraciones y layers
author: obanmarcos
'''
import os
import os, sys
from config import *
sys.path.append(where_am_i())
import lightning as pl
import argparse
import pickle
import numpy as np
import matplotlib.pyplot as plt
from utilities import dataloading_utilities as... |
e8707a777854d3a46a2d98612ca6055711d5c522d86fa23f9e9f3f8788abd378 | Python | 8,243 | 241 | import math
import os
import shutil
import sys
import time
import numpy as np
import torch
import torch.distributions as dist
import torch.nn.functional as F
from src.datasets import CUBImageFt
# Classes
class Constants(object):
eta = 1e-6
log2 = math.log(2)
log2pi = math.log(2 * math.pi)
logceilc = ... |
eff390558f30824d663cf413dcb8848aede1489464f084d86571ae0846bfc838 | Python | 8,244 | 242 | """
Model (implemented in Pytorch Lightning) demonstrating how to use augmentations
during training. Modified evoaug
"""
import torch
from pytorch_lightning import LightningModule
import numpy as np
class RobustModel(LightningModule):
"""PyTorch Lightning module to specify how augmentation should be applied to a... |
1714b484322d3930772dc47b09d421548f8b9e8b6bf61656ece68fc592360bb5 | Python | 8,248 | 231 | #!/usr/bin/env python3
import csv
import os
import subprocess
import tarfile
import unicodedata
from glob import glob
from multiprocessing import Pool
import progressbar
from deepspeech_training.util.downloader import SIMPLE_BAR, maybe_download
from deepspeech_training.util.importers import (
get_counter,
get... |
509411a85e3029236225642a9972847ca4d1747858fa1e4dbaa72f936d99107f | Python | 8,249 | 270 | import numpy as np
import matplotlib.pyplot as plt
from matplotlib_venn import venn3
from modular_splicing.utils.plots.plot_psam import clean, render_psam
from .difference_classifier import bag_to_set, venn3_intersect_bag_sizes
def display_difference(
results,
matches_test,
amount,
*,
motif_name... |
784a1e6be5fa07c5662490cb4855b2cc738e3ae216d41ccfbe601292b7206c52 | Python | 8,250 | 204 | import time
import pytest
import torch
from transformers import AutoTokenizer, GPTBigCodeConfig
from transformers.models.gpt_bigcode.modeling_gpt_bigcode import GPTBigCodeForCausalLM
from flash_attn.models.bigcode import bigcode_config_to_gpt2_config, inv_remap_state_dict_hf_bigcode
from flash_attn.models.gpt import ... |
824f14693cb57d638c0aab6858f0d3330a1e98511d41a5d904ffa3c9506bccf4 | Python | 8,250 | 215 |
import os
os.environ['KMP_DUPLICATE_LIB_OK'] = 'True'
import numpy as np
import torch
import torch.nn as nn
import scipy.io as sio
import h5py
from time import time
import torchkbnufft as tkbn
from torch.utils.data import TensorDataset, DataLoader
from functions.utils import trajGR, normabs, MCNUFFT
import... |
c1eff4355bb8db9b5ed4d2fedbcded3833971356ccf4978018391e168099ace3 | Python | 8,252 | 215 | import os
import pickle
import tarfile
from typing import Callable, Optional, Sequence, Tuple
import torch
from torch import Tensor
from pl_bolts.datasets import LightDataset
from pl_bolts.utils import _PIL_AVAILABLE
from pl_bolts.utils.warnings import warn_missing_pkg
if _PIL_AVAILABLE:
from PIL import Image
el... |
caed0e4e37326b9bb5b404e4184b2eb1729b5804e43f80743b9a3a3c7be96203 | Python | 8,252 | 206 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 30 15:25:51 2025
@author: rico
"""
import pandas as pd
import os
from pathlib import Path
from matplotlib import pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
import numpy as np
import matplotlib.pyplot as plt
from sklearn.m... |
88674b5c442f1acaa481484504392032c65dc10413d8a425faec20919203c54a | Python | 8,253 | 220 | """Layer site accessors: ``site_key`` (typed ambiguity, I-S3'),
``site_peers`` (live index, typed legacy refusal), and ``shape_summary``
(derived across-pass data string with its pinned character class).
"""
from __future__ import annotations
import pytest
import torch
import torch.nn as nn
import torchlens as tl
fr... |
3d2833cec32429c4c4cf9726130fb1d77c8a830793b5f3c7f7ed896ef70ff388 | Python | 8,254 | 236 | import numpy as np
import pandas as pd
from sklearn import metrics
import scanpy as sc
import ot
from sklearn.decomposition import PCA
def mclust_R(adata, num_cluster, modelNames='EEE', used_obsm='emb_pca', random_seed=2020):
"""\
Clustering using the mclust algorithm.
The parameters are the sa... |
47a739d97b3a9769fb913788af02942c60b0d740fa57608361e2480895fbe184 | Python | 8,254 | 223 | import warnings
from keras.src import backend
from keras.src.api_export import keras_export
from keras.src.backend.common import standardize_dtype
from keras.src.backend.common import standardize_shape
from keras.src.layers.layer import Layer
from keras.src.ops.node import Node
@keras_export("keras.layers.InputLayer... |
863a921ea82704c9a9d88b616ad4374ece1b652aee44db7344e6cbc37276844a | Python | 8,258 | 304 | """Predefined configurations for different (groups of) envs."""
def make_config(batch_size=128, c_entropy=0.01, c_value=1, clip=0.2, cpu=False, debug=False, discount=0.99,
env='CartPole-v1', epochs=3, eval=False, export_file=None, grad_norm=0.5, horizon=2024,
iterations=100, lam=0.97, ... |
800a8e3c50e51959d1a1a60312cd35b7fe4c066e3cb5ebd7b7d7c0956f2180dd | Python | 8,261 | 205 | '''
Sweep of hyperparams
* Bajar el número de iteraciones y layers
author: obanmarcos
'''
import os
import os, sys
from config import *
sys.path.append(where_am_i())
import pytorch_lightning as pl
import argparse
import pickle
import numpy as np
import matplotlib.pyplot as plt
from utilities import dataloading_util... |
2d54aacdd1f6cf2cb8e9434ad14ac4ac5a287956580007156441bc8a713fd381 | Python | 8,262 | 142 | import argparse
import os
from util import util
import torch
import models
import data
class BaseOptions():
"""This class defines options used during both training and test time.
It also implements several helper functions such as parsing, printing, and saving the options.
It also gathers additional opti... |
5b3c7a7abbb0704d5daa7f0c966b65aca0b3cf42f2bc297d74d6d46283135c8a | Python | 8,262 | 196 | """
Functions for index and blast alignment.
Copyright (C) 2021 Tham Cheng Yong
This file is part of NanoVar.
NanoVar is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your... |
24118ec1e6a7614cceb6ab3b9fc8d83c0542320c700ee3aaace4b2293bed1af2 | Python | 8,263 | 197 | """
Centralized path configuration for the AD confirmatory tool testsuite.
Two filesystem roots are required to run this codebase:
AWARENESS_DATASETS — directory containing raw EEG cohort data
(ds004504/, ds006036/, Brain_Lat/, figshare_5450293/,
ds003775/, LEM... |
87232c1d319f0981e8be9f6f1c58c7827226e3b78b1c9b446b9eafd5c43dccd5 | Python | 8,263 | 162 | """Utils for auto SSD estimator"""
import os
import mxnet as mx
from mxnet import gluon
from mxnet import autograd
from ....data.batchify import Tuple, Stack, Pad
from ....data.transforms.presets.ssd import SSDDefaultTrainTransform
from ....data.transforms.presets.ssd import SSDDefaultValTransform
from ....data.tran... |
e395695620b6e2c13e1c0a125b95d88fd9dfd1a6f047c3788387a5fb4d882186 | Python | 8,263 | 227 | """
Motion estimation module for MOT
"""
# pylint: disable=unused-argument,arguments-differ,missing-class-docstring
import time
import logging
from abc import ABC, abstractmethod
import numpy as np
class MotionEstimator(ABC):
@abstractmethod
def initialize(self, first_frame, first_frame_motion_pred_data):
... |
17c7a5ff507a47d585ffce9b5e698f8ef87003273339b9eb2dcfd793331fd977 | Python | 8,265 | 167 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from pathlib import Path
from ultralytics.utils import LOGGER, QNN_HTP_TARGETS, WINDOWS
from ultralytics.utils.checks import check_requirements
def qnn_library_paths() -> tuple[str | None, str]:
"""Resolve th... |
2e35b34851df7392f7116fcf3785a0ce55ea60cac8b9ed2e25e7e65a58289101 | Python | 8,268 | 210 | import argparse
import math
import os
import random
import numpy as np
from numpy import fft
import matplotlib.pyplot as plt
from scipy.ndimage import zoom
import torch
def image(img_path1, img_path2, obj_size):
"""
:param img_path1: amplitude
:param img_path2: phase
:param obj_size... |
5b56195cc278f8cfd768523835d58e965f33a0687c5ac614cfb7a101d8d79f42 | Python | 8,268 | 212 | import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
def import_expdata(path):
"""
Import expression data from CSV files in the specified directory.
Parameters
path
Path to the expression data directory.
Returns
... |
e5aff74d24f09d7b411e81c6816fc52a3122aafda24778e2799c7d0befd29262 | Python | 8,268 | 278 | """Regenerate the checked-in smart-collapse reference gallery.
Run from the repository root:
PYTHONPATH=$PWD python scripts/render_collapse_reference.py
The default destination is ``docs/images/collapse``. The script also copies
the finished gallery to ``/tmp/collapse_renders`` for visual review.
"""
from __fu... |
ad56dcb8d680f89105a195dec71fbaa58fc80cfc75e6d74e5dfa7e71f80ba958 | Python | 8,269 | 215 | """F02 selection-batch ``do()`` v1 (edits memo D33; row B6 analog).
One atomic ACT-only transaction: all-or-nothing attachment, ONE envelope with
the batch disclosure and kind-specific staged-store slots, per-pair ACT audit
rows, donor-group sharing by plan object identity (D8), cross-kind capability
refusal, and the ... |
db73e78dee5f3d6c6ac69550d7aef37ba101bc1cce5369501a02e41c5a6e2761 | Python | 8,269 | 269 | """
===============================================================================
Classifier comparison
===============================================================================
A comparison of several classifiers on low-dimensional synthetic datasets,
adapted to SPD matrices from [1]_.
The point of this examp... |
fed6effeeeb9816fabedeeff078a91a4f4a94e0e1292516dba30916a693620c6 | Python | 8,271 | 239 | import os
from importlib import import_module
import torch
import torch.nn as nn
import torch.nn.parallel as P
import torch.utils.model_zoo
class Model(nn.Module):
def __init__(self, args, ckp):
super(Model, self).__init__()
print('Making model...')
self.scale = args.scale
self.id... |
a1138331b9cc021cbc69b69cc3c5989ec7591c4574c64694b13b400ee4aacc91 | Python | 8,273 | 215 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
###########################################################################
# Copyright (c) 2020 Qingfeng Xia <qingfeng.xia@ukaea.uk> #
# #
# This file is part of the FreeCAD CAx dev... |
e03615ed9de42caae6ee5a87b0789044213c3fec6b9b64004f9b1be93c0bc96e | Python | 8,273 | 216 | """6. Dive Deep into Training SlowFast mdoels on Kinetcis400
============================================================
This is a video action recognition tutorial using Gluon CV toolkit, a step-by-step example.
The readers should have basic knowledge of deep learning and should be familiar with Gluon API.
New users... |
96019905ef16457d355fa84eececeb41ce99b294f2ff23c04e76db8126a571f2 | Python | 8,274 | 223 | """Tests for Trace-level profile and audit convenience reports."""
from __future__ import annotations
import torch
from torch import nn
import torchlens as tl
class ProfileModel(nn.Module):
"""Small nested model with two parameterized child modules."""
def __init__(self) -> None:
"""Initialize the... |
9a9080e19ba304b220edf22c7266f014f3d14f9b65ae46a123414533523beac8 | Python | 8,275 | 158 | #!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright © 2010 University of Zürich
# Author: Rico Sennrich <sennrich@cl.uzh.ch>
# For licensing information, see LICENSE
from __future__ import division, print_function
import sys
import os
import getopt
def usage():
bold = "\033[1m"
reset = "\033[0;0m"
ital... |
63938269920e854df6d7e49f58c043382003ae2f44b749f68bb61a4ffc2ffa1e | Python | 8,276 | 189 | """
Frequency-by-Frequency Errors
=============================
Check the error of power spectrum models across frequencies.
"""
###################################################################################################
# sphinx_gallery_thumbnail_number = 2
# Import numpy for some utility functions
import ... |
fc659fb99c49c914bbca8e995ca3cd58de40ced5c5b93815c3e8f91c45ec6bb9 | Python | 8,281 | 317 | import json
import pathlib
import numpy as np
import pytest
from impose import data
from impose.structure import StructureComposite, StructureLayer
from impose.geometry import shapes
data_path = pathlib.Path(__file__).parent / "data"
def test_append_duplicate_label():
sl1 = StructureLayer(
label="test ... |
c7e15c80242dde830ed419e1a388fb6b8b996fa22abfb3a7f755ec6a51cb38ae | Python | 8,283 | 235 | import torch
import torch.nn.functional as F
import numpy as np
import os
from ovseg.utils.io import load_pkl
from ovseg.networks.resUNet import UNetResEncoder
from ovseg.prediction.SlidingWindowPrediction import SlidingWindowPrediction
FLIP_AND_ROTATE_IMAGE = True
def ClaraWrapperOvarian(data_tpl,
... |
a556b433b000694dc17320a016c7064ebabd39e78d50f1c6f69b466233b4c3a5 | Python | 8,288 | 236 | from typing import Literal
from warnings import warn
import numpy as np
from anndata import AnnData
from mudata import MuData
from scanpy._utils import view_to_actual
from scipy.sparse import csr_array, csr_matrix, dia_array, issparse, spmatrix
# Computational methods for preprocessing
def tfidf(
data: AnnData ... |
5a9f0cd6ab5ff5e1e2f854c3111e242c76e4ca0012d430f7cd4b8a46c081bfc3 | Python | 8,289 | 206 | """Behavioral tests for repgeom input-validation and refusal semantics."""
from __future__ import annotations
import numpy as np
import pytest
import torch
import torchlens as tl
def _distances(n: int = 8) -> np.ndarray:
"""Return a valid Euclidean distance matrix over ``n`` distinct points."""
rng = np.r... |
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