sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
8f55fe0f0f28cd2414e0afca5da8f68c4c6997594d4bbbb708a16f2fc9231d88 | Python | 17,353 | 437 | """L4 until= battery: truncation term, positive-claim cap, prefix projection.
Pinned per the design-review-converged L4 design memo (sec 2-3) and S2 ratification
sec 2: truncation is a run-result term, never a capture outcome; a truncated
run never settles a positive claim; the prefix projection never loosens; the
two... |
ff71f56a65a8056f066b5c1ea179600a58eb1926eb456cd88f9fbe233ea123a0 | Python | 17,359 | 434 | #! /usr/bin/env python
import os
import sys
import pandas as pd
import numpy as np
import time
from sqlalchemy import create_engine
from sqlalchemy.pool import NullPool
import multiprocessing
import tqdm
from itertools import repeat
def get_gene_fragments(gene_df, restriction_enzymes, db, pchic=False):
db.dispos... |
c7b9a5f4a2c457bafc72e984a03f276fbcc6b70b2b0f780880815a50975b5237 | Python | 17,366 | 229 | """3. Inference with Quantized Models
=====================================
This is a tutorial which illustrates how to use quantized GluonCV
models for inference on Intel Xeon Processors to gain higher performance.
The following example requires ``GluonCV>=0.5`` and ``MXNet-mkl>=1.6.0b20191010``. Please follow `our ... |
bfd8b7e5193ded344d156a242a2b1eac765141fa5183897ca6fa4b30ff64c641 | Python | 17,369 | 445 | """
The training function used in the finetuning task.
"""
import csv
import logging
import os
import pickle
import time
from argparse import Namespace
from logging import Logger
from typing import List
import numpy as np
import pandas as pd
import torch
from torch.optim.lr_scheduler import ExponentialLR
from torch.ut... |
6e11d4f7de9db0093c51ddf0c5b635cf37f20a965bbb9b35ec10d8258f22e7d2 | Python | 17,379 | 436 | """
ori_analys.py
This module contains functions to run analyses of ROI orientation selectivity
in the data generated by the Allen Institute OpenScope experiments for the
Credit Assignment Project
Authors: Colleen Gillon
Date: October, 2018
Note: this code uses python 3.7.
"""
import copy
from joblib import Pa... |
24542433bc4b374e9a558c3f68704cb583952bf6e259a1998cc5042c0ad6de75 | Python | 17,381 | 426 | __author__ = "quentin"
import logging
import cv2
try:
from cv2.cv import CV_AA as LINE_AA
from cv2.cv import CV_FOURCC as VideoWriter_fourcc
except ImportError:
from cv2 import LINE_AA, VideoWriter_fourcc
import os
class BaseDrawer:
def __init__(
self,
video_out=None,
draw_... |
2d22e09fa53f4b32cfbe628071ccf559da489110bf16a9ffc5cfcad07e490b16 | Python | 17,381 | 469 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
import time
import os
import sys
from tqdm import tqdm
from pathlib import Path
import numpy as np
import nibabel as nib
import pandas as pd
import torch
import torch.nn as nn
from torch.utils.data import DataLoader
from utilities.adversarial_loss i... |
8b9124db681e90ff02d44044a704c676f06d6bec31b7e9ab68bddf35ee9d6285 | Python | 17,381 | 464 | import io
import json
import logging
import os
import re
from collections import defaultdict
import humanfriendly
import numpy as np
import pandas as pd
from autouri import GCSURI, AbsPath, AutoURI, URIBase
from .dict_tool import recurse_dict_value
logger = logging.getLogger(__name__)
def get_workflow_root_from_ca... |
e5cdc5af652f1cbf203f5090569a5b88a43a7e3385060911ae4295525e408b74 | Python | 17,384 | 536 | import warnings
from pathlib import Path
from typing import (
Any,
Dict,
Hashable,
Iterable,
Literal,
Mapping,
MutableMapping,
Optional,
Tuple,
Union,
cast,
)
import numpy as np
import pandas as pd
import polars as pl
import xarray as xr
import zarr
from numcodecs import Blo... |
1cdf6f1370a913959f190f474f4e0df4c508613f52867792e364526d6ee484a2 | Python | 17,386 | 479 | # Copyright 2025 Google.
#
# 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 agreed to in writing, soft... |
eca455a5626260b18c3e36b91eb6563d7fd43520fd61f6914f312df591a37588 | Python | 17,387 | 428 | from datetime import datetime, timedelta, timezone
from threading import Event, Thread
from time import monotonic, sleep
from uuid import uuid4
from zoneinfo import ZoneInfo
import pytest
from dateutil import tz as dateutil_tz
from celery import beat
from celery.schedules import crontab
from t.integration.tasks impor... |
724e55be98dce79b5c6aeb68031f17aa85bd8c1e9f75bd2567bdc29826f2e920 | Python | 17,391 | 551 | """JAX backend derived-gradient preview tests."""
from __future__ import annotations
from typing import Any, cast
import pytest
import torchlens as tl
from torchlens.backends import BackendUnsupportedError
from torchlens.backends.jax import GradOptions
from torchlens.backends.jax.backend import (
_experimental_... |
ecc9cd86040f7f81cc69464bb1886c72e4f1dd09d93c50f3bbffd4af3f81bbf8 | Python | 17,392 | 383 | """
For analyses of flatmaps
"""
import numpy
import math
import random
import voxcell
import matplotlib.pyplot as plt
from voxel_maps import coordinates_to_image
import os
import pandas as pd
from scipy.spatial.distance import pdist, squareform
# Function below provides a wrapper that turns a function with multipl... |
e81f9b089638cd9549d121bb447c5acf47f6af9318808d2e114c2448927dffe6 | Python | 17,394 | 511 |
__author__ = 'quentin'
from collections import deque
from math import log10, sqrt, pi
import cv2
try:
CV_VERSION = int(cv2.__version__.split(".")[0])
except:
CV_VERSION = 2
import numpy as np
from scipy import ndimage
from ethoscope.core.variables import XPosVariable, YPosVariable, XYDistance, WidthVariabl... |
00a05d6d85c3e6a0d3704d73e12c1608f90956a70962d1dc00655b2aeef73354 | Python | 17,395 | 452 | """W051-IO: load-time integrity anchors the loader never checked (AUD-CODE 3.0).
(a) forged ``Op.edge_substitutions`` carriers, (b) manifest <-> metadata
anchors and op-graph coherence, (d) TorchLens-owned annotation families,
(e) an absent ``root_entry_point`` on a tlspec v9+ artifact. Tampering is
done on the bytes ... |
ce08b39324f4bfb24a7519f2e7f989eb5c3a19d75bdaa68cc83f2ed76032e4ec | Python | 17,397 | 323 | from os.path import join
import numpy as np
import matplotlib.pyplot as plt
import os
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
from pycircstat import mean as cmean
from library.comput_utils import circular_density_1d
from library.script_wrappers import best_worst_analysis, exin_analysis
from library... |
4322b59d19a095273ab3ce7c7c3c40a716f11efdf81d30f4ddda9bdb8d870a6c | Python | 17,398 | 467 | import matplotlib.pyplot as plt
from joblib import load
import scipy.cluster.hierarchy as sch
import pandas as pd
import figutils
import sequence_logo
from quad_model import *
def get_link_midpoint(
link_function, midpoint=0.5, epsilon=1e-5, lb=-100, ub=100, max_iters=50
):
"""Assumes monotonicity and smoot... |
24fdf747b45ac62d4b8d0cb7491703b95192a29b626171030007b3a4578ef332 | Python | 17,400 | 503 | import numpy as np
import os
import json
import itertools
import copy
import multiprocessing
import pandas as pd
import networkx as nx
import PIL.Image
import warnings
from pathlib import Path
from typing import List
from nway.pairwise_matching import PairwiseMatching
from nway.schemas import NwayMatchingSchema, NwayMa... |
dfe3dbfd8652a881799edabb58ba2af4b5010e7ff0a3399391ad35ec9d6d844e | Python | 17,408 | 459 | # Copyright 2022 Deepfold Team
#
# 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 agreed to in writin... |
94a0e5d8d1ef023ac621e5eab126cbe1b106d53c7499eaa488aa6e88fc7d6149 | Python | 17,411 | 413 | """
To Test:
- upgrading with missing secret raise exception
- upgrading removes old secrets
- upgrading with partial variables keeps the old one
- upgrading with no variables works just fine
- upgrading and missing variables raises exception
"""
import logging
from uuid import uuid4
from pydantic import UUID4
from ... |
bbac1a0739dddf2871a981adb02e56f99fafe4081cd94e71eb684afbc9af6639 | Python | 17,412 | 514 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import numpy
import torch
import torch.nn as nn
import torch.nn.functional as F
from slowfast.models.common import DropPath, Mlp
from torch.nn.init import trunc_normal_
def attention_pool(tensor, pool, thw_shape, has_cls_... |
5e50d1401fc2e0e797be93ae1f4a30a9af8e621c243ee05ada3ac83b8089f61e | Python | 17,424 | 551 | """Adapted interfaces from Niworkflows."""
import os
import shutil
from json import dump, loads
import filelock
import nibabel as nb
import numpy as np
from bids.layout import Config
from nipype import logging
from nipype.interfaces.base import (
BaseInterfaceInputSpec,
Directory,
DynamicTraitedSpec,
... |
7c670d362c06f66bcccd1e717857737dbafad30dbe561f1eb45c7559b616e791 | Python | 17,425 | 491 | # SOURCE: vendored from ujscjj/DPTNet @ master
# https://github.com/ujscjj/DPTNet/blob/master/models.py
# https://github.com/ujscjj/DPTNet/blob/master/transformer_improved.py
# https://github.com/ujscjj/DPTNet/blob/master/utils.py
#
# DPTNet (Chen, Mao & Liu, Interspeech 2020, arXiv:2007.13975) speech
# separation: a d... |
28b0fa1cdca9b5b76deee75c5266f2414ced17ac1908b6a1884318dfbf7c9686 | Python | 17,433 | 480 | """Adapted from: https://github.com/facebookresearch/moco.
Original work is: Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
This implementation is: Copyright (c) PyTorch Lightning, Inc. and its affiliates. All Rights Reserved
This implementation is licensed under Attribution-NonCommercial 4.0 In... |
e7df69ee50b9436774457dda1cd5be2af080de7c9f187ef8e0de726c14e3be8a | Python | 17,434 | 345 | # pylint: disable=line-too-long,too-many-lines,missing-docstring,arguments-differ,unused-argument
__all__ = ['I3D_InceptionV3', 'i3d_inceptionv3_kinetics400']
from mxnet import nd
from mxnet import init
from mxnet.context import cpu
from mxnet.gluon.block import HybridBlock
from mxnet.gluon import nn
from mxnet.gluon... |
d30629f0a955b0caedf3aabf41384b9ff45e1ff172ae3ec0d5cb9ce0cf21967e | Python | 17,438 | 447 | # coding=utf-8
# Copyright 2023 The Google Research 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 applicab... |
63fae672b96ef57e7d8c81c6e6a9ab7932f8d1397d8f4ac6bbd2b7639dd28ad5 | Python | 17,442 | 442 | import datetime
from tqdm import tqdm
import operator
from collections import defaultdict, Counter
import pandas as pd
import numpy as np
from ..utils import constants
import random
latitude = constants.LATITUDE
longitude = constants.LONGITUDE
date_time = constants.DATETIME
user_id = constants.UID
class MarkovDiaryG... |
9be3549717301c17c7cca7aa7e12f53d818d3b3f5e8a2952a40a4baee15d5b80 | Python | 17,457 | 529 | """Tests for failed-forward partial fastlog Recordings."""
from __future__ import annotations
from pathlib import Path
from typing import Any
import pytest
import torch
from torch import nn
import torchlens as tl
import torchlens._state as torchlens_state
import torchlens.capture.projections as fastlog_state
from t... |
830e96d519e80c41730a8eaaddeffd31d69c33c924b4186781cabd19f14dcb08 | Python | 17,459 | 438 | import warnings
from keras.src import backend
from keras.src import layers
from keras.src.api_export import keras_export
from keras.src.applications import imagenet_utils
from keras.src.models import Functional
from keras.src.ops import operation_utils
from keras.src.utils import file_utils
BASE_WEIGHT_PATH = (
"... |
66ffc8c81bbc952483cf5a2c984cc3682670a07d969220d3601cc9be5c86e7ef | Python | 17,470 | 440 | # -*- coding: utf-8 -*-
"""
the main app for part classification
"""
_debug = True
_using_saved_model = True # use the checkpoint
_calculating_gflops = False # calc computation cost
BATCH_SIZE = 200 # if dataset is small, make this bigger
EPOCH_COUNT = 50
INIT_LEARN_RATE = 5e-3 # batch_normalization ne... |
38622d3c0889db793685966431aaabbee02d8ff409770e454ffdd33f999d7020 | Python | 17,472 | 440 | """Basic class for TreeGrower Algorithms for space colonization"""
import logging
import numpy as np
from numpy.core.umath import clip
from tns.morphmath import sample
from tns.generate.algorithms.tmdgrower import TMDAlgo
from tns.generate.algorithms.common import section_data
from tns.morphmath.bifurcation import di... |
b767958d12888ff9460fd626c6dcc89c19a07da6b098819ad9aab2c91b6a80bd | Python | 17,474 | 469 | import logging
from contextlib import contextmanager
from unittest.mock import ANY, Mock, patch
import pytest
from kombu.utils.limits import TokenBucket
from celery import Task, signals
from celery.app.trace import LOG_RECEIVED
from celery.exceptions import InvalidTaskError
from celery.utils.time import rate
from cel... |
1ece2b4cf88807b7da10469196042bb19dad83005e907b6a73bf136932258199 | Python | 17,478 | 340 | # -*- coding: utf-8 -*-
import os
import time
from tokenize import group
from joblib import parallel_backend
import torch
import torchvision
import torchvision.transforms as transforms
import platform
import matplotlib.pyplot as plt
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
from optical_l... |
f725a362465ab3fa94fa12c1aba2ef775720a462ad306aaae4c51b1aabce6e00 | Python | 17,479 | 488 | from torch_geometric.data.data import Data
import torch
import copy
import numpy as np
import random
import time
class ensemble(object):
"""
The class ensemble represents the main user API for the
Ensemble_GNN package.
"""
def __init__(self, gnnsubnet=None, method="chebnet", epoch_nr: int = 50, ni... |
0300ff0a37d5cd7eb9de75b8fe2d14e1b9053021b86482e83198b1c8bf02678a | Python | 17,490 | 500 | """
This module provides helpers for C++11+ projects using pybind11.
LICENSE:
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>, All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
1. Redistributions... |
c62e75522b2b16937e9b13131f520406c0f41e83aaba2db2a9d075be51b2832a | Python | 17,494 | 380 | # ------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# ------------------------------------------------------------------------------
from __future__ import absolute_import
from __future__ import d... |
32ae8dbe732c4bde8430dc1df973a89132736dfe8430b207215f932abd3675a6 | Python | 17,497 | 393 | """
Author: Derek van Tilborg -- TU/e -- 23-05-2022
A collection of random functions that are used in different places
- Data: Class that holds all data, featurizes it, and can augment it
- featurize_data()
- shuffle()
- augment()
- get_config(): functio... |
4c986eb258efd801aba9c83109cd65476a1a16503ea0f1cbe24057b57535331e | Python | 17,498 | 505 | r"""
Comprehensive DEB prediction pipeline with multi-scenario analysis, k_X sensitivity,
closed vs. stepped engine comparison, and environment-coupled gut integration.
This module orchestrates:
1. Instar moult calculations (t1, t2, L1, L2) from MATLAB DEBtool formulas
2. Multiple functional response values (f, f_DR, ... |
f5baa9eacabfdf27a670cd527dd07b7b933a3f1406fe94f4d07d036f3d9893aa | Python | 17,514 | 411 | # pylint: disable=missing-function-docstring, line-too-long, unused-argument
"""
SlowFast Networks for Video Recognition
ICCV 2019, https://arxiv.org/abs/1812.03982
Code adapted from https://github.com/open-mmlab/mmaction and
https://github.com/decisionforce/TPN
"""
from mxnet import init
from mxnet.context import cpu
... |
7022aa427918870062eb3c43f0c04c0cc703d62a9438639746c4b5505ab25bb5 | Python | 17,521 | 445 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Label(_BaseLayoutHierarchyType):
_parent_path_str = "layout.shape"
_pat... |
142d00ba1d79e4835256bd2dd552e99483a459878e6c7864f52029c342a362bf | Python | 17,529 | 419 | """F26: the tier-P/M watch engine -- step law, cadence, loud failures.
Realism rule: the tier-M rows run against a REAL config-built GPT-2
(transformers), zero network; tier-P rows use a real MLP + AdamW loop.
"""
from __future__ import annotations
import pytest
import torch
import torchlens.trackers as trk
from to... |
9ddfe2fe16e4ca3ce27522a3154aff1c7e9c589f055bf4d2c319f42d2c142889 | Python | 17,535 | 489 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.nn import GCNConv, GATConv, global_max_pool as gmp, global_add_pool as gap,global_mean_pool as gep,global_sort_pool
from torch_geometric.utils import dropout_adj
# GCN based model
class GNNNet(torch.nn.Module):
def __init__(s... |
cc7ab65d58e8447aea5bf7e7456f1c0ede7a9f937a7d7177f181fa102503d36a | Python | 17,536 | 477 | """
Test to verify that rapl_include_dram and rapl_prefer_psys parameters work correctly.
"""
import logging
import sys
import pytest
from codecarbon.core.cpu import IntelRAPL
@pytest.mark.skipif(not sys.platform.lower().startswith("lin"), reason="requires Linux")
def test_rapl_include_dram_default_false(tmp_path)... |
97b9573b7133f21ae754a8e20b4bfb233f32cd0fbd6eeb39c5d426fb999ecbad | Python | 17,539 | 449 | import sys
from lmfit import Model, Parameters
import math
import numpy as np
import powerlaw
from scipy import stats
from scipy.stats import mannwhitneyu
from scipy.optimize import curve_fit
import utils
def Linear(x, m, b):
return m*x+b
def PRW3D(t, S, P):
return 3*((S)**2)*((P)**2)*(np.exp(-t/P) + t/P - ... |
9a1cf69f831fced199330e5652e867866e040613d737b90842e7633db07e9290 | Python | 17,541 | 471 | """Source-embedding privacy policy for portable saves (split from scrub.py).
Every source-file reference in a bundle is relativized to a bare basename
(absolute paths embed the producer's ``$HOME``, OS username, and filesystem
layout -- host PII with no portable value), and ``include_source=False``
drops source text, ... |
8e3325d372d8bd591e7afe848a7f379d5b1bc162537f84a5ec49e7a15d7153a8 | Python | 17,545 | 367 | import csv
import torch.nn as nn
import torch.nn.functional as F
import torch
from torch import optim
from torch.autograd import Variable
from torch.utils.tensorboard import SummaryWriter
import cv2
from skimage import segmentation
import numpy as np
import openslide
import matplotlib.pyplot as plt
import... |
61afdd7a98b2abdc8b578b408393bfa113bb5d4ba2a4f62f35ef7107a408a675 | Python | 17,546 | 406 | """
Tests for pcmci.py, including tests for run_pc_stable, run_mci, and run_pcmci.
"""
from __future__ import print_function
from collections import defaultdict
from distutils.version import LooseVersion
import numpy as np
import pytest
from scipy.special import comb
from tigramite.pcmci import PCMCI
from tigramite.in... |
886365b66c9abd2dd9f29e34f0589f9ab8b610ee04a618794e94dacb28cb9a62 | Python | 17,553 | 415 | import functools
from keras.src import ops
from keras.src.ops import linalg
from keras.src.quantizers.calibrator import Calibrator
from keras.src.quantizers.quantizers import compute_quantization_parameters
from keras.src.quantizers.quantizers import dequantize_with_zero_point
from keras.src.quantizers.quantizers impo... |
c99f51e13cf538c768e3ba022a08673e2c18f3953e4e64f0c36cd062b6c64458 | Python | 17,560 | 564 | """Convert BDD100K to COCO format."""
import argparse
import json
import os
from functools import partial
from multiprocessing import Pool
from typing import Dict, List, Tuple
import numpy as np
from PIL import Image
from scalabel.common.parallel import NPROC
from scalabel.common.typing import NDArrayI32
from scalabe... |
23037e12a7b4b6075cef38c3c71e594784898e8fe8d1848a2dc2635c391c8fa9 | Python | 17,569 | 574 | """
R objects as Python objects.
The module is structured around the singleton r of class R,
that represents an embedded R.
License: GPLv2+
"""
import array
import os
import types
import typing
import warnings
import rpy2.rinterface as rinterface
import rpy2.rinterface_lib.embedded
import rpy2.rinterface_lib.openrl... |
a34d4be2b9b04981a64d779831a00449eab4f367a2b3554ee67c2a5bad190992 | Python | 17,569 | 424 | """Flash-Linear-Attention token-mixing layers (faithful recurrent reference forms).
Source: fla-org/flash-linear-attention (``fla/layers/*.py``, ``fla/ops/*``).
These are linear-attention / gated-RNN sequence mixers that replace softmax
attention with an explicit recurrent state update. Each block here reproduces
the... |
bc22f332498e369d1416913ce538b96b1dba5144252ff6c1c14e058dce4a86e5 | Python | 17,573 | 441 | import os
import numpy as np
import pickle as pkl
import nibabel as nib
from os.path import join as pjoin
from scipy.stats import pearsonr, zscore
from magicbox.io.io import CiftiReader, save2cifti
from cxy_visual_dev.lib.predefine import proj_dir, Atlas,\
s1200_avg_eccentricity, LR_count_32k, get_rois,\
s1200_... |
471b2c482248d782b93881c5e834c0edc23c1e7e6f42a437e4c096b9d8ed4c3e | Python | 17,580 | 367 | from functools import partial
from typing import Any, Callable, List, Optional, Sequence, Tuple, Union
from torch import nn, Tensor
import torch.nn.functional as F
from torchvision.ops.misc import ConvNormActivation
from torch.hub import load_state_dict_from_url
import urllib.parse
from models.mn.utils import cnn_out_... |
b09e7ffd992d87ef74c226225662b242cf229352acddd442cf21a86579cabbbd | Python | 17,593 | 461 | # -*- coding: utf-8 -*-
"""
Created on Sun Aug 3 15:18:38 2014
@author: Dan Denman and Josh Siegle
Loads .continuous, .events, and .spikes files saved from the Open Ephys GUI
Usage:
import OpenEphys
data = OpenEphys.load(pathToFile) # returns a dict with data, timestamps, etc.
"""
import os
import numpy as np... |
bba2f233ecbb12200cd94cc5fc8f6098f4b38ead91369f90e91f8b6e4efa063f | Python | 17,593 | 542 | #!/usr/bin/env python
"""
run_paper_figures.py
This script produces paper figures for this project.
Authors: Colleen Gillon
Date: January, 2021
Note: this code uses python 3.7.
"""
import argparse
import copy
import inspect
from pathlib import Path
import time
import warnings
# try to set cache/config as early ... |
bb9856eae0a5c40d010eacd0b066e7a93a40bae195c6e67da2583ca53d6692fd | Python | 17,601 | 498 | """
module to handle detectron2 integration of CAP (requires detectron2 installation)
"""
# from google.colab.patches import cv2_imshow
from detectron2.config import configurable
from detectron2.engine.defaults import DefaultTrainer
from detectron2.data.build import build_detection_train_loader
from detectron2.d... |
44035b2ef945e0b4b50f97ac4ad3caeedb014fdd98bbfbaa7ee7c6e32130ce8a | Python | 17,602 | 451 | from keras.src import activations
from keras.src import backend
from keras.src import constraints
from keras.src import initializers
from keras.src import ops
from keras.src import regularizers
from keras.src.api_export import keras_export
from keras.src.layers.input_spec import InputSpec
from keras.src.layers.layer im... |
85428621a91f3c484ebb879e703790fcb070a2e660ecd344b9917274330f4df9 | Python | 17,613 | 405 | import os
import math
import random
from functools import reduce
import torch
import torch.nn as nn
import re
import numpy as np
from transformers import *
from src.utils.util import device
class adapet(torch.nn.Module):
def __init__(self, config, tokenizer, dataset_reader):
'''
ADAPET model
... |
ac4d2cab3f72ea0f9217860a55dca413ed69f936ce0322efebc1c9ae050285b8 | Python | 17,613 | 497 | import locale
locale.setlocale( locale.LC_ALL, 'en_US.UTF-8' )
import re
import dateparser
try:
from local_extractor.utils import common_utils
from local_extractor.utils.table_concatenation import concatenate_tables
except ImportError:
import sys, os, pathlib
path = pathlib.Path(__file__).absolute().p... |
ad8348a16efca92f0acca8e42d8ce5d0e9941c2fdb5157b931f4528878c94263 | Python | 17,614 | 496 | from typing import Callable
from hypo_x import hebb_update, fsm_step
from dataclasses import dataclass, field
import jax
import jax.numpy as jnp
from functools import partial
import numpy as np
from data_gen_x import gen_data_x
"""
Condition Functions
"""
def an_cond(i, _):
"""Active nothing condition
:param ... |
112967c62dd867a02962573ecc9e00b9fe4fd563bd8eba38cc9ba32bafb76ab8 | Python | 17,615 | 380 | import argparse
from loader import MoleculeDataset, load_data
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from sklearn import metrics
from sklearn.metrics import roc_auc_score,accuracy_score,precision_score,recall_score,precision_recall_curve,f1_score
from skle... |
43592845e40bcd66fb395024e630aa2bf693fc69a923cce42c381acca621452b | Python | 17,616 | 386 | from ...core.trajectorydataframe import TrajDataFrame
from ...utils import constants, gislib
from ...measures import individual
import numpy as np
import pandas as pd
import math
from collections import Counter
import operator
import pytest
earth_distance_km = gislib.getDistance
latitude = constants.LATITUDE
longi... |
2fdf62ee393ab66f9338a45f96e2dfd74f4a776498e8f8ca4441e10d9960eb47 | Python | 17,618 | 537 | """Tests for the Explore app: the zero-configuration entry point."""
from __future__ import annotations
from concurrent.futures import Future
from html import escape
from queue import SimpleQueue
from types import SimpleNamespace
from unittest.mock import PropertyMock
import panel as pn
import pytest
from larvaworl... |
7b23e244f2f354beb43ae5548b5ca57dd864215da6f3a215ed32974d97a33c59 | Python | 17,621 | 476 | #!/usr/bin/env python
"""
run_logreg.py
This script runs and analyses logistic regressions predicting stimulus
information based on ROI activity for data generated by the Allen Institute
OpenScope experiments for the Credit Assignment Project
Authors: Colleen Gillon
Date: October, 2018
Note: this code uses pytho... |
7297a5042c7987a1a13d763f1c9d20e7c9b22fdf5b2f62e906e44a7b2c378a7f | Python | 17,624 | 437 | import random
from typing import Optional
import mujoco
import numpy as np
from angorapy.common.const import N_SUBSTEPS
from angorapy.tasks.envs.dexterity.consts import DEFAULT_INITIAL_QPOS
from angorapy.tasks.envs.dexterity.consts import FINGERTIP_SITE_NAMES
from angorapy.tasks.envs.dexterity.core import BaseShadowH... |
c6c52dd3e458f0c7065eead8ba9b267df5c3e13f6d9d109d0d772b6db60edf83 | Python | 17,624 | 367 | from __future__ import generators
import logging
import glob, os, functools
import sys
sys.path.append('../TM2_segmentation')
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 sci... |
03fb6a69ec7af0f738924eaaca93eea3973e471e2b14d04c6144761a4d864b56 | Python | 17,627 | 432 | """model.py - Model and module class for EfficientNet.
They are built to mirror those in the official TensorFlow implementation.
"""
# Author: lukemelas (github username)
# Github repo: https://github.com/lukemelas/EfficientNet-PyTorch
# With adjustments and added comments by workingcoder (github username) and Alex... |
eca1923f55dc9c1f671fbbd0322ca01f5ea067ad3671b7a10803b7ea8681bb9d | Python | 17,631 | 505 | """Reader for Neurosuite/Neuroscope formatted electrophysiology data.
Handles:
- XML metadata parsing (channel count, sampling rates, channel groups)
- Binary signal files (.dat, .eeg, .lfp) via memory mapping
- Spike sorting results (.clu.N / .res.N pairs)
- Event files (.evt) with automatic pairing of start/stop eve... |
3769cad1f9e6c0f1c00e6bc18c01c1ec316e24272d87306e516e15ba414b40de | Python | 17,639 | 353 | import torch
import torch.nn.functional as F
from torch.utils.data import DataLoader
from torch.distributions.categorical import Categorical
import os
import sys
import argparse
import numpy as np
import math
from copy import deepcopy
from model import BIML_S, describe_model
import datasets as dat
from train_lib import... |
d3dfc85fdfba861e150b9f97481461ade511d82c20381ca4412b03ab9bfb3c6d | Python | 17,639 | 432 | """Library for exporting SavedModel for Keras models/layers."""
from keras.src import backend
from keras.src.api_export import keras_export
from keras.src.export.export_utils import get_input_signature
# Re-export for backward compatibility (used by tfsm_layer.py)
from keras.src.export.saved_model_export_archive impo... |
5292eb9d6ed17ad9a9f8f549e4aec572ce0249a5be65190704f63bfd5ebe0707 | Python | 17,646 | 446 | # --- THIS FILE IS AUTO-GENERATED ---
# Modifications will be overwitten the next time code generation run.
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Label(_BaseLayoutHierarchyType):
_parent_path_str = "layout.newshape"
_... |
b3627f2104b84ce71e27ec64fc2097252759423016b284fb6d4225f663593c67 | Python | 17,659 | 423 | """Real-model transform rows (memo 10.2; lane F19). Offline, cache-gated.
The realism rule discharged on the transforms library itself: real
checkpoints, real tokenizers, real ragged shapes — NEVER downloads. Vision rows skip typed where
their cached checkpoint is absent; tokenizer rows run only in the R1 offline venu... |
fd2de011d56136af54234c36a3505be414a15b6735f84d74162ff08ecd61a02a | Python | 17,664 | 349 | # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license
from __future__ import annotations
from collections import deque
from typing import Any
import numpy as np
from ultralytics.utils.metrics import bbox_ioa
from .basetrack import TrackState
from .byte_tracker import BYTETracker, STrack
from .utils i... |
2a10e2f10cd72caa755b64509cf0accceb13b447a14563048861f0fb04e9cf56 | Python | 17,671 | 347 | from keras.src import backend
from keras.src.api_export import keras_export
from keras.src.backend.common import is_float_dtype
from keras.src.backend.common import is_int_dtype
@keras_export("keras.random.normal")
def normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None):
"""Draw random samples from a norma... |
cc4ea65d57ade4f76c6f7016f66e0e4885d28179f0523411e6b54d57394f0cf4 | Python | 17,672 | 493 | import numpy as np
from sklearn.utils.validation import check_random_state
from ..utils.mean import mean_riemann
from ..utils.distance import distance_riemann
from ..utils.base import invsqrtm, powm, sqrtm, expm
from .sampling import generate_random_spd_matrix, sample_gaussian_spd
from ..transfer import encode_domains... |
a58df147f5e314a2de30277b4e8ff7c88b0245138f84cddcc282e6d252cb0521 | Python | 17,677 | 405 | '''
Tools for online output to display/download.
'''
import re
import os
import argparse
import glob
import logging
import json
import time
import zipfile
import tempfile
import os.path as osp
from typing import Union
import numpy as np
import pandas as pd
from tools.draw_results import draw_pae, draw_interface_h... |
680ff207ff37305dff2743ceb6c858a73ab389bc2ed89cc41d16faac73ca8af3 | Python | 17,680 | 458 | import numpy as np
import torch
import pandas as pd
from lifelines.utils import concordance_index
from lifelines.statistics import logrank_test
from lifelines import CoxPHFitter
from sklearn.preprocessing import MinMaxScaler
from survival_plus_x.losses.coxph import neg_cox_log_likelihood,\
neg_cox_log... |
dc2c608546c7b011f46e0b2a1bb248c2fc14e182983224bc4f016a8aedfb3a7f | Python | 17,681 | 373 | import random
import os
import numpy as np
import paddle
import paddle.nn as nn
import paddle.nn.functional as F
import joblib
import pgl.graph as G
from paddle.io import DataLoader
from .maml import MAML
from ..datasets import sample_meta_datasets, sample_test_datasets, MoleculeDataset
from ..utils import Logger
cla... |
24ed366b15c76184914308826564e79689b01c2420143f48dfbb7135051e200e | Python | 17,683 | 355 | from mirp.data_import.import_image import import_image
from mirp.data_import.import_mask import import_mask
from mirp._data_import.generic_file import ImageFile, MaskFile, MaskFullImage
from mirp._data_import.dicom_file import ImageDicomFile, MaskDicomFile
from mirp._data_import.dicom_file_stack import ImageDicomFileSt... |
c2a35008cb736e278cc7a22aa2c2ed2a71e0309ca777a345cfff6eb5b9c48e4e | Python | 17,688 | 548 | '''
Copyright 2021 Twente Medical Systems international B.V., Oldenzaal The Netherlands
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 requir... |
71a70d5eb37379c90f40d8f612ebaddba211ed7ad7f58ed825c413c2e2419886 | Python | 17,690 | 513 | """
To test it, you need to set:
export CODECARBON_API_URL=http://localhost:8008
export DATABASE_URL=postgresql://codecarbon-user:supersecret@localhost:5480/codecarbon_db
Then execute the tests:
uv run task test-api-integ
"""
import os
import unittest
import uuid
from datetime import datetime
import jwt
import pytest... |
0d4ef274108ee768ec7cf8f572b823e21c6602bbb11bf5136c86aba6c5d2b846 | Python | 17,697 | 514 | """Wave-0 gates for the private DROP-gated ATen execution profile."""
from __future__ import annotations
import re
from collections.abc import Iterator
from pathlib import Path
import pytest
import torch
from torch import nn
import torchlens as tl
from torchlens import _state
from torchlens._io import TorchLensIOEr... |
ba2765327a5c82c0bf0ba9b932c68ea77941a1ea63d3de6b722054d66592ec22 | Python | 17,697 | 437 | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: bream/mux_scan_results.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from... |
f96c26a5433461249e0f8a6a61d1ffe295468dbe23caa161e63ff99b5e1c74bd | Python | 17,701 | 530 | """
Taken and adapted from https://github.com/lucidrains/vit-pytorch.
Also some inspiration for the embeddings taken from https://github.com/rwightman/pytorch-image-models
"""
import torch
from torch import nn
from einops import rearrange, repeat
from einops.layers.torch import Rearrange
import numpy as... |
a32a0706125c57bb536e941b84f10e5a48d8f17c967d83ddd5b8e2171b244e83 | Python | 17,708 | 460 | # Copyright (c) 2023, Tri Dao.
import os
import time
from pathlib import Path
import torch
import pytest
from einops import rearrange
from transformers import AutoConfig, AutoTokenizer, AutoModelForCausalLM
from flash_attn.models.gpt import (
GPTLMHeadModel,
combine_state_dicts_tp,
shard_state_dict_tp,
... |
9759cc668175a43493aa3013d819013dbe25c75b30f229ba2a1b9352bd0afe0d | Python | 17,721 | 563 | # coding=utf-8
# Copyright 2025 The Google Research 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 applicab... |
4686d3eb0bf1e91457b79ab30bc8bb6a15f3f1f0cbbef52f36c7fa89e4c11a7f | Python | 17,725 | 518 | # Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
''' Pointnet2 layers.
Modified based on: https://github.com/erikwijmans/Pointnet2_PyTorch
Extended with the following:
1. Uniform sampling in... |
dd4a18d7463519f595d1dd7bd169dd9025d8378cb8e6e4d7d47d0708a328d0e3 | Python | 17,726 | 430 | '''
Copyright 2021 Twente Medical Systems international B.V., Oldenzaal The Netherlands
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 requir... |
06cfd744eca84491b3275ad2d9a5c623e552b8d18a049bc25df6947a3fe986af | Python | 17,729 | 459 | # Copyright 2025 Google.
#
# 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 agreed to in writing, soft... |
12fa68f97124d840ca5e1378a5c479c84a6edcf039926deac4f5fa2cb2c9fe89 | Python | 17,733 | 394 | #!/usr/bin/env python3
"""
Dx AY — Phase B2 high-impact auxiliary re-runs
================================================
Re-runs three load-bearing auxiliary diagnostics under the proper
per-fold per-cohort-deployment pipeline:
1. §3.2 4×4 bootstrap CIs (classifier-only): rank-norm vs z-score
× deployment vs... |
2a8ab65143ad14242e046b715cb4294c4d41d5abb56fa15069d50c86d7908297 | Python | 17,742 | 408 | import torch
import numpy as np
import os
from utils import parse_config,load_CDS,rename
from scipy.stats import pearsonr,kendalltau,spearmanr
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd
from itertools import combinations
from os.path import exists
from utils import parse_config, setup_fo... |
b8bff59d369fbaaaa4e2006b42c0889f51b2dd9c7508c1a44fe83c4c81cb7c06 | Python | 17,757 | 466 | from typing import Optional
try:
from typing import Literal
except ImportError:
from typing_extensions import Literal
import os
import anndata
import cv2
import numpy as np
import pandas as pd
from scipy.sparse import isspmatrix
from scipy.spatial import distance
from tqdm import tqdm
from ...configuration ... |
103b51d6250032ecf7cc181ea3a88f4a4b4001b8d08618880dbbd941e7a81b75 | Python | 17,764 | 441 | '''
Figuras para la tesis
1) Plot per boxes
2)
'''
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import sys
import matplotlib.patches as mpatches
import numpy as np
import sys, os
import pickle
import matplotlib
matplotlib.use('Agg')
# plt.style.use('seaborn-colorblind')
acceleration_... |
7264ea0c8c9a645f3e00fed0721a754a25b2b459949fb3c716e90cbdb36c20dc | Python | 17,764 | 447 | """Utils for auto tasks"""
import copy
import warnings
import numpy as np
import autogluon.core as ag
from ..estimators.base_estimator import BaseEstimator
from ..estimators import SSDEstimator, FasterRCNNEstimator, YOLOv3Estimator, CenterNetEstimator
from ..estimators import ImageClassificationEstimator
from ..data.... |
32f9c9b0c5b62124d741de51dbe974c28c043af0b5dff79a38919bce4f98fcf2 | Python | 17,770 | 509 | import re
from pathlib import Path
from typing import Any, Iterable, List, Optional, Union
import numpy as np
import pandas as pd
# auto-object related utility functions
#######################################
# ---------------------------------------------------------------------------
# Regexes for parsing auto-... |
20f2b2067c0412d1f8b2de1bc23a378402e5d4a5b17324b877bbba7193c00dd7 | Python | 17,774 | 465 | """
A single simulated experiment.
Runs one experiment configuration to completion, then optionally enriches and
analyses the dataset it produced.
"""
from __future__ import annotations
from typing import Any, Optional
import os
import time
import contextlib
import io
import agentpy
import numpy as np
import pandas ... |
b92546f5e4c3f86b0e699fa83aa4981e24b191f311b7e1634f5f497954701697 | Python | 17,792 | 439 | """SRP construction oracles: exact, corpus-free identities (memo B6/B10; lane F19).
O1a (construction algebra), O1f (distribution identity — what makes T-C13's
labels checkable rather than editorial), O3 (generation determinism, kept
executable because "passes by construction" is exactly the claim that should
be teste... |
e08cd168a1629b7dfb1223f9e0968d4e1d5be2f2bf79a37f4df01ac707c34476 | Python | 17,804 | 553 | import textwrap
from copy import copy
import os
from packaging.version import Version
import warnings
from plotly import optional_imports
from plotly.io._base_renderers import (
MimetypeRenderer,
ExternalRenderer,
PlotlyRenderer,
NotebookRenderer,
KaggleRenderer,
AzureRenderer,
ColabRender... |
b9d8fa0a7bcb83fd85a24a1dbc9078af4b4a2914c2c45b33a79eed8ae46f78a1 | Python | 17,809 | 442 | """IO functions for BGI stereo technology.
"""
import gzip
import math
import warnings
from typing import Callable, Dict, List, NamedTuple, Optional, Tuple, Union
import cv2
import numpy as np
import pandas as pd
with warnings.catch_warnings():
warnings.simplefilter("ignore")
import skimage.io
from anndata i... |
75bb7a0be67d86315c23cfa7fc24f72467738f787e574317bfe484473e797069 | Python | 17,814 | 484 | '''
I'd like to make a container class. The container should just be based on
a numpy array.
The Container is EEG data - so there should be some header info as well as
data info
It should have some methods to allow for communication (Possibly using
multithreading cues)
It should have some automated methods, called ... |
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