sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
3d9a52a56cc41afdbe34112ab93b730a0fdf8f16180816b8c6385934de033df7 | Python | 4,037 | 115 | import os
import numpy as np
import torch
from sklearn.utils import shuffle
def normalization(data, test_data=None):
for feature_index in range(data.shape[2]):
mean_values = np.mean(data[:, :, feature_index])
var_values = np.var(data[:, :, feature_index])
data[:, :, feature... |
5a1e64b75a352f63bdd220eed8567d52ff009418c11c40b3dd19c6c8d70c8853 | Python | 4,039 | 108 | import pytest
import pathlib
import hashlib
import numpy as np
from pciSeq.src.core.main import VarBayes
from pciSeq.app import parse_args, stage_data
from pciSeq.src.validation.config_manager import ConfigManager
from pciSeq.src.validation.input_validation import InputValidator
from constants import EXPECTED_AREA_METR... |
b2ac524c72408f0ffecdd814b32568c7d568d38511ba2106ba17e73055fa55cd | Python | 4,041 | 121 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
def gather_nd_impl(
data: np.ndarray, indices: np.ndarray, batch_dims: i... |
de2cae3a8075711333dc030e5909cd23ef731a24e78e0cef4fa693b085603ba7 | Python | 4,042 | 104 | """Longest Common Subsequence similarity distance, from tslearn."""
__author__ = ["fkiraly"]
from sktime.dists_kernels.base import BasePairwiseTransformerPanel
from sktime.dists_kernels.base.adapters import _TslearnPwTrafoAdapter
class LcssTslearn(_TslearnPwTrafoAdapter, BasePairwiseTransformerPanel):
"""Longes... |
f10d794ae085d4bd264b34b788d84e881908dfa7f07d56d13ab724b57c161059 | Python | 4,042 | 98 | import numpy as np
import os
import torch
from tqdm import tqdm
from atom3d.util.transforms import prot_graph_transform, PairedGraphTransform
from atom3d.datasets import LMDBDataset
from torch_geometric.data import Data, Dataset, Batch
from torch.utils.data import DataLoader
import atom3d.util.graph as gr
class G... |
e00f4acfefe36d264d20e76a6a26ab836cac50e5026c41d4aa7e4fb8f7f64c12 | Python | 4,046 | 109 | import shutil
import os
import pyvips
import logging
stage_image_logger = logging.getLogger(__name__)
def split_image(im):
# DEPRECATED to be removed
'''
you can just do:
im.dzsave('./out', suffix='.tif', skip_blanks=-1, background=0, depth='one', overlap=0, tile_size=2000, layout='google')
to... |
517420c046d7dd4efefdc6b4d6616702c58ef578ec981a4722aaaf9c3eff2c57 | Python | 4,048 | 105 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
8c822bd57a60ffc70e168fdf7454c38e3d4c9f0ed5e24a7c0fd4b6e316fa8166 | Python | 4,048 | 109 | import os
import dotenv as de
import numpy as np
import pandas as pd
import torch
from atom3d.datasets import LMDBDataset
from atom3d.util.voxelize import dotdict, get_center, gen_rot_matrix, get_grid
from torch.utils.data import DataLoader
de.load_dotenv(de.find_dotenv(usecwd=True))
class CNN3D_TransformLEP(obje... |
6cd3668bc9fd00c932b128e0c0a97fe8ffef7f864ef44ff918f432b95311d6ba | Python | 4,050 | 91 |
"""
This module parses the arguments given through the torchserve command-line. This is used by model-server
at runtime.
"""
import argparse
# noinspection PyTypeChecker
class ArgParser(object):
"""
Argument parser for torchserve and torchserve-export commands
TODO : Add readme url
"""
@staticm... |
39927a254758cd2aad02b5272218c7da0fd17aae6be6abeb2487f506d4ab756e | Python | 4,051 | 119 | """Tests for bycycle.features.shape."""
import pytest
import numpy as np
from bycycle.features.shape import *
###################################################################################################
###################################################################################################
@pyte... |
d7b692070f7916c250e06b6c741cb3d24fa9bbdc13b5edf267f82631ead81d3b | Python | 4,051 | 123 | import os
import shutil
from pathlib import Path
import numpy as np
from asreview.state import JSONState, HDF5State, DictState
from asreview.state import open_state, state_from_asreview_file
from asreview.settings import ASReviewSettings
def test_read_json_state(tmpdir):
state_fp = Path("tests", "state_files",... |
02982235d1bd633d9064eb9d1ba53adbad8b38c91af32840837b77d93e757b0f | Python | 4,052 | 108 | import data_adapter
import numpy as np
from scipy import io as sio
from tensorpac import Pac, EventRelatedPac, PreferredPhase
from tensorpac.utils import PeakLockedTF, PSD, ITC, BinAmplitude
import matplotlib.pyplot as plt
import time
from multiprocessing import Pool
import signal_tools
import argparse
def erpac(x,ch,... |
6afdfa748bd7a941d2f63d3ce1eaa6d1129ab368f4dde5afa22fa5904663312d | Python | 4,055 | 119 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
78d0617047b527b8d89429faa028dce9bfaa14ebe38666823395a3a823f9c55f | Python | 4,056 | 134 |
import numpy as np
import pandas as pd
import pytest
from numpy.testing import assert_array_equal
from seaborn._core.groupby import GroupBy
@pytest.fixture
def df():
return pd.DataFrame(
columns=["a", "b", "x", "y"],
data=[
["a", "g", 1, .2],
["b", "h", 3, .5],
... |
99f07303e9f2e400d79c8413856d5d282b9f6b0a68157d9e6e713c102ea75529 | Python | 4,056 | 110 | # coding=utf-8
# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... |
bca6a4af05bfe1c26ac67a97fc4fed934bd050edeb0f8a860a27788f23cd25c4 | Python | 4,056 | 104 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri May 29 15:46:05 2020
@author: sam
"""
import os
import argparse
from pipeline_utils import submit_job
from pipeline_utils import check_filedeps
import configparser as ConfigParser
import glob
import h5py
import numpy as np
if __name__ == '__main__':
... |
4f2d7827b5424112b83f83f8d2578fde36e46bfdb356e1382e98eb9b078274d1 | Python | 4,058 | 120 | import torch
import torch.nn as nn
import torch.nn.functional as F
from utils.func import one_hot
from utils.const import regression_loss
class WarpedLoss():
def __init__(self, loss_function, criterion):
self.loss_function = loss_function
self.criterion = criterion
self.squeeze = True if... |
1d280a097deddcfb14203d51a30800ace620545aa7c709bd1fa126a5bdc1f552 | Python | 4,061 | 123 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
a8a6c223c2a296eb3a9be883303da6b93c76c936a16e83b52f69f6e4a04d6c73 | Python | 4,061 | 129 | import argparse
import re
import os
import pickle
import numpy as np
from tqdm import tqdm
from rdkit import Chem
from collections import Counter
import torch
import random
from typing import Optional
def seed_everything(seed: Optional[int] = 0) -> None:
torch.manual_seed(seed)
random.seed(seed... |
daabbc97ba3f9d75e610d31ab29b70bf6557167aed5e6385150eccbd3a472121 | Python | 4,061 | 112 | import sys
import socket
import struct
import numpy as np
from datetime import datetime, timedelta
from functools import reduce
import random
from math import pi, sin
from time import sleep
from parameterSetup import ParameterSetup
# sends mock signal to online.py by connectin to networkServer
args = sys... |
e2d034f7bb26ed448909a3687649a5c05914793048d215a77e74f9d67d7eeb0e | Python | 4,061 | 131 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
e1edf2dce41c797d039d72beb73cef2d8f229a897c26f4cfd36965899f1a068a | Python | 4,063 | 119 | import numpy as np
import pandas as pd
import statsmodels.api as sm
from features import *
def get_model(promoter='u6', classifier=False, path='../Saved models/CRISPRedict'):
'''
Loads the appropriate model for the chosen task.
:parameter promoter: gRNA transcription method to load the suitable model ('u6', 't... |
0ff59e00b7bfe5f8f2b22b523845a6743bd4d23ebbf0fb6dfda95c9aad19e924 | Python | 4,064 | 104 | import face_recognition
import cv2
import numpy as np
# This is a demo of running face recognition on live video from your webcam. It's a little more complicated than the
# other example, but it includes some basic performance tweaks to make things run a lot faster:
# 1. Process each video frame at 1/4 resolution (t... |
a8662eaa20a2479e3e96b1bd24ef9f9853d4067f42da936f30448c84b1087901 | Python | 4,064 | 95 | import os
from os import path
from lfads_tf2.defaults import get_cfg_defaults
from lfads_tf2.tuples import BatchInput
from lfads_tf2.utils import unflatten
from ray import tune
from yacs.config import CfgNode as CN
def create_trainable_class(epochs_per_generation=50):
"""Creates a tuneLFADS class with specified ... |
b1d502dd92d9e6a9d7547c8bde0ba029dbe3f7f534e598836323006779edabf0 | Python | 4,064 | 129 | # Copyright 2019-2026 The AmpliGraph Authors. All Rights Reserved.
#
# This file is Licensed under the Apache License, Version 2.0.
# A copy of the Licence is available in LICENCE, or at:
#
# http://www.apache.org/licenses/LICENSE-2.0
#
import tensorflow as tf
class CalibrationLayer(tf.keras.layers.Layer):
""... |
5fbdbd882cab2dc54bcc1658a62c506d6d70ca224aafcccbb12c92adb62b5f1d | Python | 4,065 | 113 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
dee57dd9ba9c38de4a44f8f6869355570f8de55eded4a8821a764fca34dfa550 | Python | 4,066 | 98 | # Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
687d4b77895ee3f7fb8dba50d7e0bb955e2263a165f2ec7d2fd1f364673ca05e | Python | 4,067 | 119 | # ----------------------------------------------------------------------------
# Copyright (c) 2017-2026, QIIME 2 development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ------------------------------------------------... |
44eb6cca239f2ffa828c70d9fe2e929251a646d14381a017ee188fbd3f8f811f | Python | 4,068 | 95 | import itertools
import random
import numpy as np
import pandas as pd
from lee_et_al_2023.src import base
def center_model(model):
"""Center a model."""
new_model = model.copy()
all_ratings = new_model[base.MONELL_CLASS_LIST].values
bias = np.mean(all_ratings, axis=0)
new_model[base.MONELL_CLASS_... |
28a0c3da80da130bf9ecb6b6ce15ec5ac32ede6f318138cbd59180c683c57867 | Python | 4,069 | 131 | # SPDX-License-Identifier: LGPL-3.0-or-later
"""Testing of models predicting charge density on grid points."""
from deepmd.infer.model_test.base import (
ChunkContext,
ModelTester,
_write_per_frame_details,
)
from deepmd.utils.data import (
DeepmdData,
)
from deepmd.utils.eval_metrics import (
mae,... |
c1a5ba5ed3b6290e73ed81f2ae83f71b77b2eb172eb771995c4de3794f6826cc | Python | 4,069 | 139 | # Copyright (c) OpenMMLab. All rights reserved.
import pytest
import torch
from mmcv.utils.parrots_wrapper import _BatchNorm
from mmcls.models.backbones import VGG
def check_norm_state(modules, train_state):
"""Check if norm layer is in correct train state."""
for mod in modules:
if isinstance(mod, _... |
62770a004dbe0d7ee117d6f0b818bb71167735cae7cff002f0bd06b593d55d65 | Python | 4,071 | 116 |
def _add_axis_arrows(ax, dims=None, origin=None, azim=0, elev=0, **kwargs):
"""
Plots arrows to show the 3d Axis.
Parameters
---------------------
ax : matplotlib ax
dims : list, string
LR, AP, SI, 'all', None
origin : list (len of 3)
Origin of center of arrow axes.
... |
ee74aa1d30c8e2146fbd1f988aae5ef5d919c3ce4f6ac635978cc52615a208a7 | Python | 4,074 | 137 | from __future__ import annotations
import functools
import textwrap
from typing import Any
from typing import TYPE_CHECKING
from typing import TypeVar
import warnings
from optuna._warnings import optuna_warn
from optuna.exceptions import ExperimentalWarning
if TYPE_CHECKING:
from collections.abc import Callable... |
46a849cca62a3368a7d9706fd096c88bcd62967d990145918593d48a955667bc | Python | 4,075 | 114 | import torch
from torch.utils.data.sampler import Sampler
class WarmupLRScheduler():
def __init__(self, optimizer, warmup_epochs, initial_lr):
self.epoch = 0
self.optimizer = optimizer
self.warmup_epochs = warmup_epochs
self.initial_lr = initial_lr
def step(self):
if s... |
f8cf6f8ba7c7d27c2f02cbf922301c724e0a4e0c69672b1e2f1663ec2579f440 | Python | 4,075 | 137 | import numpy as np
import pandas as pd
import statsmodels.api as sm
from features import *
def get_training_data(promoter='u6', classifier=False, add_constant=True, path='../Data/2. Training datasets'):
'''
Loads training dataset for the corresponding model.
:parameter promoter: gRNA transcription method to co... |
b5cd8dd3474711ff44173a94e1fb8cc2b9aaae91645ed135f6f0e321e7b2a6f4 | Python | 4,076 | 99 | import pytest
import flair.datasets
from flair.data import Sentence
from flair.embeddings import DocumentRNNEmbeddings, FlairEmbeddings, WordEmbeddings
from flair.models import TextClassifier
from flair.samplers import ImbalancedClassificationDatasetSampler
from flair.trainers import ModelTrainer
from tests.model_test... |
ecd59f5e577d07baac589b76016944c516a7fbedf16471847ddc2ece9d2a3126 | Python | 4,078 | 105 | # Copyright 2018-2023
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
cb5dc005b5cff1d62d56112eddd659be9ce382a384ebf0eca068ea6048bde6bf | Python | 4,081 | 126 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
826989da89c8e2191085d60ceb0203a0093cc6b7e0f37aca2bdbbf61c08ea0f5 | Python | 4,084 | 181 | """Tests for time series k-means."""
import numpy as np
import pytest
from sklearn import metrics
from sktime.clustering.k_means import TimeSeriesKMeans
from sktime.datasets import load_basic_motions
from sktime.tests.test_switch import run_test_for_class
expected_results = {
"mean": [
2,
2,
... |
96c3aff48723e4d3f87f0d8ec480195f534178c9c99980d4c3e2501bcadf90e8 | Python | 4,084 | 117 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
from collections import OrderedDict
import torch
def get_layer_maps(layer_num, with_bn):
layer_maps = {'conv': {}, 'bn': {}}
if with_bn:
if layer_num == 11:
layer_idxs = [0, 4, 8, 11, 15, 18, 22, 25]
elif la... |
a48ea2bdfb02464aeed9eb7407021833fd2442f9cd8b239577c8c10e7f8847e7 | Python | 4,086 | 112 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
d157cc336a279bd8f3ad4c840c047e54a371e9658d5251ecd4b5fd79cfb78984 | Python | 4,086 | 114 | """
Define some data structures that are used in multiple analysis locations
"""
from dataclasses import dataclass, field
import numpy as np
def def_empty_np():
return np.array(0)
def def_empty_list():
return []
def def_empty_dict():
return {}
@dataclass()
class PData:
"""
data class for some ... |
06228f5507a672d23776693883eeaeb93aa580636090a8385f5f2dd5e6faac57 | Python | 4,087 | 116 | # Copyright 2018-2026
# Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH
# 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/LICE... |
f590f6887ad731f622abfec8f78e422e602ad32d902071f10f2330878886bf34 | Python | 4,087 | 114 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
907cc4ac435c90b3f67b3421be5ad252ee3a27a8b29c7855f276c1abf391afcc | Python | 4,089 | 123 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
46060106b78bb110638e3d61ae80dfb39127b28fb41f89470ddd7c81dd78270a | Python | 4,093 | 139 | """Tests for E-Agglo (agglomerative clustering algorithm)."""
__author__ = ["KatieBuc"]
import numpy as np
import pandas as pd
import pytest
from sktime.detection.eagglo import EAgglo
from sktime.tests.test_switch import run_test_for_class
@pytest.mark.skipif(
not run_test_for_class(EAgglo),
reason="run te... |
6c84d4f7c4c62196b1d7ded5b315621fd2aceff43119809f982fe13391c0a5f3 | Python | 4,094 | 127 | import math
import torch.nn as nn
def default_conv(in_channels, out_channels, kernel_size, bias=True):
return nn.Conv2d(
in_channels, out_channels, kernel_size,
padding=(kernel_size//2), bias=bias)
class Upsampler(nn.Sequential):
def __init__(self, conv, scale, n_feat, bn=False, act=False, b... |
92aa195cd59c45bcc59d0751ecb1134560a11d492073992520ca91cf0a922f51 | Python | 4,096 | 120 | #!/usr/bin/env python3
#!/usr/bin/env pypy3
"""Set qnames based on the curies defined for a given ontology.
Usage:
qnamefix [options]
qnamefix [options] (-x <prefix>)...
qnamefix [options] <file>...
qnamefix [options] (-x <prefix>)... <file>...
Options:
-h --help print this
-k --keep ... |
a043b8cea9e7015fc07aadfb281be3a23ddac5a1f8bf15750ddea84dc62dfc2b | Python | 4,101 | 139 | """
A simple module to allow tracking and timing of calls using decorators.
This module is part of *vcnmodel*.
Support::
NIH grants:
DC R01 DC015901 (Spirou, Manis, Ellisman),
DC R01 DC004551 (Manis, 2013-2019, Early development)
DC R01 DC019053 (Manis, 2020-2025, Later development)
Copyright 2017-2... |
f649e29d122b470865fc7d350deedf15c522a474d00eda4bbf57276a0a2cf12d | Python | 4,102 | 166 | #%% [markdown]
# # Matching when including the contralateral connections
#%% [markdown]
# ## Preliminaries
#%%
import datetime
import os
import time
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from giskard.plot import adjplot, matched_stripplot,... |
01ee6cae9715d9aef6a1e25a63004f1cf5120f83f7b314af8035ee7e5090ba29 | Python | 4,104 | 109 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.ops.aionnxml._op_run_aionnxml import OpRunAiOnnxMl
from onnx.reference.ops.aionnxml.op_tree_ensemble_helper import TreeEnsemble
class TreeEnsembleRegressor(OpRun... |
4afb7afd41ac9f3f6f48a1b9501875e57b02cc77747c8c077c6c0b1819d2872f | Python | 4,107 | 113 | """
Test sounds and plot waveforms.
This script tests the sound waveform generator for a variety of sounds
"""
import numpy as np
import pyqtgraph as pg
from cnmodel.util import sound
from collections import OrderedDict
import scipy.signal
import sys
try:
import PySounds
HAVE_PYSOUNDS = True
except ImportErro... |
b5bff261c6fc0ba73a473e68312b1dd139c83cb85dc02daa24dae9fb7a3ccf46 | Python | 4,108 | 136 | import matplotlib.pyplot as plt
import numpy as np
from brian2 import *
# import matplotlib.pyplot as plt
import time
import pickle
import brian2cuda
set_device("cuda_standalone", build_on_run=False)
"""
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
78863288b3f41e63f795245cac5b29eea4530e2899272b798fae83b654d740c2 | Python | 4,112 | 149 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
8b7cb650a55f1d5d3658365137c6c3dd740527a40acfef98307ebe6142fa50d4 | Python | 4,112 | 120 | from networkunit.capabilities.ProducesSpikeTrains import ProducesSpikeTrains
from sciunit.models import RunnableModel
from networkunit.plots.rasterplot import rasterplot
from neo.core import SpikeTrain
from copy import copy
import numpy as np
import neo
class loaded_spiketrains(RunnableModel, ProducesSpikeTrains):
... |
92aad5060a2ea8a66864ec74106bdc35db88702b358e4ab3cd253871a4f753fb | Python | 4,113 | 124 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import pytest
from onnx.reference.ops._op_list import load_op
from onnx.reference.ops.op_attention import _compute_attention
def test_attention_reference_uses_versioned_implementati... |
4e154b7ec8fc5621a3f3ecb638ec33fb5a90d8b6a08dd2f7d06289d057e79145 | Python | 4,116 | 121 | from __future__ import print_function
import numpy as np
from .augment import Augment, Compose
from .perturb import Perturb
class Section(Augment):
"""Perturb random sections in a training sample.
Args:
perturb (``Perturb``): ``Perturb`` class.
maxsec (int):
prob (float, optional):
... |
251abc8b1aff61a5f18d317a947a04e9c6165732064960cb385ef7af2e26c694 | Python | 4,117 | 110 | __all__ = ['import_features', 'get_data']
from collections.abc import Iterable
from pathlib import Path
from traceback import print_exc
import nibabel
import numpy as np
from graynet import config_graynet as cfg
_base_feature_list = ['thickness', 'curv', 'sulc', 'area',
'area.pial', 'jacobian_... |
1fc010fd78b591ad10d33899e6c67dcc1915e54892ada0fda4addb2945ef82f2 | Python | 4,119 | 172 | {
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### This is using Keras for Keras"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from keras import layers, models"
]
},
{
"cell_type": "markdown",
"... |
d2d18f2c3811e8e9033c0d9ad9b42f5f89f65979da1db7d602c80fd5ad5f4035 | Python | 4,120 | 115 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
7fa70da7555e1d7f0d2114bdcf66dce608b2f733e903fb12a759eec61732a0c9 | Python | 4,124 | 135 |
"""
Context object of incoming request
"""
class Context(object):
"""
Context stores model relevant worker information
Some fixed during load times and some
"""
def __init__(self, model_name, model_dir, manifest, batch_size, gpu, mms_version):
self.model_name = model_name
self.m... |
aece97737431759b703eaca5adffe2c96d73a3ca0c8d726c26a997cb62d19462 | Python | 4,125 | 111 | # copyright: skpro developers, BSD-3-Clause License (see LICENSE file)
"""Base class for data types."""
__author__ = ["fkiraly"]
from sktime.datatypes._base import BaseDatatype
class ScitypePanel(BaseDatatype):
r"""Panel data type. Represents a panel (flat collection) of time series.
The ``Panel`` data typ... |
c69c8c3077f4cecdcdf11bd08e36e0bc269dcb1999bff72091a1adfdfdd84f0c | Python | 4,125 | 119 | """Test the distance calculations are correct.
Compare the distance calculations on the 1D and 2D (d,m) format input against the
results generated with tsml, in distances.tests.TestDistances.
"""
__author__ = ["chrisholder", "TonyBagnall", "fkiraly"]
import pytest
from numpy.testing import assert_almost_equal
from s... |
f14810d2370b56c7f9b477ffa7a75de7485787d8591d1bde4fe263e3b2a20776 | Python | 4,128 | 151 | # Copyright (c) ONNX Project Contributors
#
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
import onnx
from onnx.backend.test.case.base import Base
from onnx.backend.test.case.node import expect
class StringSplit(Base):
@staticmethod
def export_basic() -> None:
... |
3fe7206d457b841e209776af488ac2ec90ad222a487149a85dd3eb7fe8ee75c9 | Python | 4,130 | 112 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import numpy as np
from onnx.reference.op_run import OpRun
def topk_sorted_implementation(X, k, axis, largest):
"""See function `_kneighbors_reduce_func
<https://github.com/scikit-learn/scikit... |
1fb16c711582609879b67c7980056e7877cd27c8538eeb01bb919dafb893201d | Python | 4,136 | 86 | import logging
logger = logging.getLogger('DockOnSurf')
def select_stable_confs(conf_list, energy_cutoff):
"""From a list of atomic configurations selects the most stable ones.
Given a list of ase.Atoms configurations and an energy cutoff, selects all
the structures that have an energy lower than, the e... |
bba98c4af534053ba36d128bb4d087faeaacbd720bddaaae91e5cf644b1646e0 | Python | 4,137 | 113 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
from collections import OrderedDict
import torch
def convert_conv1(model_key, model_weight, state_dict, converted_names):
if model_key.find('conv1.0') >= 0:
new_key = model_key.replace('conv1.0', 'backbone.conv1.conv')
else:
new_... |
88ef1de10921a5f77337547eec6adc1902e2b052454bdd56462c11f6e3c3f8d1 | Python | 4,138 | 115 | import numpy as np
import tensorflow as tf
from utils import dipole_kernel
from utils import dxp, dyp, dzp
#
#Description:
#Loss function for training QSMnet and DIAM-CNN
#
# Copyright @ Yanqiu Feng
# Laboratory for Medical Imaging and Diagnostic Technology
# Southern Medical University
# email: foree@163.com
#
def l... |
08cf05647dae721a955d4ce2257c24dd2fe63ff3a9b091980d798532dd0d31ca | Python | 4,141 | 97 | from open_spiel.python.rl_environment import Environment, TimeStep, StepType
class ValidActionsMaskEnvironment(Environment):
def step(self, actions):
"""Updates the environment according to `actions` and returns a `TimeStep`.
If the environment returned a `TimeStep` with `StepType.LAST` at the
... |
9b4f3bd4cde4df76ebfd60f3cd1e77364e5fb2bd582f08ecd3eb045714cc694f | Python | 4,141 | 118 | import numpy as np
from tensorflow import keras
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
from tensorflow.keras.layers import Convolution2D, MaxPooling2D
import matplotlib.pyplot as plt
from tensorflow.keras import laye... |
e210cf3552af1ef91aed51203bb0c48fd3e758308f4ffb04d6bbc4db3f59949e | Python | 4,142 | 105 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
d85bc046ace6174bde21abeefb49f0fdd525570cf009b51c56d9ec54761566cf | Python | 4,147 | 89 |
import argparse
import os
from os import path
from typing import Any
class CheckArgs(argparse.Action):
"""
Check our command line arguments for validity
"""
def __init__(self, option_strings, dest, nargs=None, **kwargs):
if nargs is not None:
raise ValueError("nargs not allowed")
... |
4d2bf6fc3a9085124fbe031e750ed9b61543b6d3a9967d4e204c93516dedff55 | Python | 4,151 | 130 | import re
import os
import sys
from setuptools import setup
def abspath(relpath, _dir=os.path.dirname(__file__)):
return os.path.join(_dir, relpath)
def find_version(filename):
abs_filename = abspath(filename)
_version_re = re.compile(r"__version__ = ['\"](.*)['\"]")
last = None # match python sema... |
71e42db250c15c2907be560ec83a111d19953f808a0f2457b2e7bb7b19a7e950 | Python | 4,151 | 135 | """Tests for spatio-temporal DBSCAN."""
import numpy as np
import pytest
from sktime.clustering.spatio_temporal import STDBSCAN
from sktime.clustering.utils.toy_data_generation._make_moving_blobs import (
make_moving_blobs,
)
def _rename_labels(X, centers_origin, y_pred, n_labels):
"""Rename cluster labels ... |
420342ca580b9e3f279425c423c6d0fccddd2e8fe1f953c8f50ef97759791afb | Python | 4,152 | 120 | #!/usr/bin/env python
#
# Copyright 2008, Google Inc.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list... |
bd0b55b559184e652b534f7d72970be1093c8e106dc854ba5a7dbd6f6f13c1c8 | Python | 4,152 | 115 | # -*- coding: utf-8 -*-
#
# Copyright © 2023 Charles E. Vejnar
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://www.mozilla.org/MPL/2.0/.
#
import glob
import logging
import os
from ..in... |
54fa3f33785cac827cc37bd641239bc41024bb7a5a1484339c89cde6c61630c0 | Python | 4,153 | 83 | """Functions for RATA analysis"""
from pathlib import Path
import IPython.display
import pandas as pd
import seaborn as sns
DATA_PATH = Path(__file__).parent.parent / 'data'
FIGURE_PATH = Path(__file__).parent.parent / 'figures'
ODOR_LABEL_LIST = [
u'alcoholic', u'aldehydic', u'alliaceous', u'almond', u'amber', u'... |
836795236f90180fb014a52bb2381ace8522118195cc59d0b7e8c90a1a3e204b | Python | 4,153 | 116 | # Copyright (c) OpenMMLab. All rights reserved.
import argparse
import warnings
import mmcv
import numpy as np
from mmcv import DictAction
from mmcv.parallel import MMDataParallel
from mmcls.apis import single_gpu_test
from mmcls.core.export import ONNXRuntimeClassifier, TensorRTClassifier
from mmcls.datasets import ... |
222aa7b103c6aa0a1bef7281478ae326616e2a5f1f353b45acae4a27eed45dcf | Python | 4,158 | 107 | # Copyright 2019 DeepMind Technologies Limited
#
# 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 agr... |
bc60f05f171c0adf7a00f43777b2dd245c461b5071137c787b13c8a947bbb5c0 | Python | 4,158 | 108 | """
Create a network with excitatory, inhibitory, and modulatory connections. Add input sources and output monitors, and
simulate using numpy.
William Nourse
December 1st, 2021
"""
"""Imports"""
# Import packages and modules for designing the network
from sns_toolbox.neurons import NonSpikingNeuron
from sns_toolbox.co... |
9f7913f8329444e778d9b44ff394f2130d60d64ce350fd400967c192f6a15c52 | Python | 4,160 | 71 | """
@file: run_cutechess_experiments
Created on 03.10.2023
@project: CrazyAra
@author: Felix
Executes cutechess commands in the shell
"""
import subprocess
from datetime import datetime
device = 0
player_a = "correct_phases"
player_b = "no_phases"
batch_size_options = [64]
use960 = False
movetime_options = [100, 20... |
e64d9424f93e9f7ed789b86d26f20e72b6453a4f89af4447e532e54a7398d570 | Python | 4,161 | 120 | # Copyright 2026 DeepMind Technologies Limited
#
# 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 agr... |
5cff9f2e528db5ec5bdc2e3c925887230b1c4ca5249836ed370b4d345d457d4e | Python | 4,162 | 105 | """
multi_run does multiple runs with the models
OBSELETE 3/2020
"""
from __future__ import print_function
import os.path
import model_run as MR
import pprint
import json
pp = pprint.PrettyPrinter(indent=4, width=60)
# create an instance of the modelrunner for each cell configuration
# population the configuration ... |
57bad0a81f93369d00addda76e93ca4b566faf9c906b53898fb059e69f41ab7e | Python | 4,163 | 122 | # Copyright 2022 DeepMind Technologies Limited
#
# 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 agr... |
e29be5ea96015cefe898292a9d94b65d54a97d7ab8e9efe64d2e51069eb8c6ee | Python | 4,166 | 99 | import numpy as np
import pytest
import torch
from short2long.competitive_model import CompetitiveAllocationNet, multinomial_nll_terms, unsmoothed_cluster_targets
GROUPS = np.array([0, 0, 1, 1, 1])
STRUCTURES = ["g0|chr1|+|10-20", "g0|chr1|+|10-30", "g1|chr2|-|40-60",
"g1|chr2|-|40-80", "g1|chr2|-|50-9... |
09cc0dac126bd31a0d106926f76926aa412355c037fee33248fd6bf8c5803b28 | Python | 4,167 | 110 | """This is the template script for running PBT with lfads_tf2.
Please copy and modify this script to suit your needs.
"""
import shutil
from os import path
import ray
import yaml
from lfads_tf2.defaults import DEFAULT_CONFIG_DIR
from lfads_tf2.utils import flatten
from ray import tune
from tune_tf2.models import crea... |
c2e4cfcbbf95413dbdc8d783054776f976750177a0e94d279f988f17e19f0efc | Python | 4,168 | 133 | import numpy as np
import pandas as pd
import logomaker
import matplotlib.pyplot as plt
# MOANA (MOtif ANAlysis)
def activation_pwm(fmap, X, threshold=0.5, window=20):
# Set the left and right window sizes
window_left = int(window/2)
window_right = window - window_left
N, L, A = X.shape # assume thi... |
380e6f970febe4406fdd1b4026fd9d7ccc7d7aed37cf67de21194a1956a625cc | Python | 4,170 | 111 | # 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, software
# distributed under t... |
dd1e829e5a453503cf8aa8db91e5307bfc5afa6df777f13cac2f89a5dde4eac1 | Python | 4,172 | 90 | import functools
import torch
import torch.nn as nn
import torch.nn.functional as F
import models.modules.module_util as mutil
class ResidualDenseBlock_5C(nn.Module):
def __init__(self, nf=64, gc=32, bias=True):
'''def __init__(self, nc, kernel_size=3, gc=32, stride=1, bias=True, pad_type='zero', \
... |
15947c58bf3f312ab4cdf6410edbf2e73be5664059d04f27a7052eef8a8fa446 | Python | 4,175 | 119 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
72b91e7ff448a68ffe58e6436c2cc0a798628da8230047d1c072019a79fdc396 | Python | 4,176 | 103 | # Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
from __future__ import annotations
import math
import numpy as np
from onnx.reference.op_run import OpRun
class MaxUnpool(OpRun):
def _run(
self, X, indices, output_shape=None, kernel_shape=None, pads=None, strides=None
... |
6ba35048061256611fb849d45836d2da58fdb70252e7cf995dcf1ee3ea2eb690 | Python | 4,177 | 115 | #!/usr/bin/env python
import pandas as pd
import numpy as np
import os
import shutil
import sys
# Analyze the Orthofinder results
OGTSVPATH="./fasta/OrthoFinder/Results_Jul02/Orthogroups/Orthogroups.tsv"
sp_to_chrom = {
"CFR": "../../genomes/for_odp/creolimax/CFR.chrom",
"CLA": "../../genomes/for_odp/cladorhi... |
17789aaff8022a3a6221199d48e367f0c5b5fad7f4c2388f10076bec9a5aeb54 | Python | 4,180 | 95 | import logging
import os
import re
from base.processor_base import Processor
from onmt.bin.preprocess import preprocess as onmt_preprocess
from rdkit import Chem
from typing import Dict, List
def smi_tokenizer(smi: str):
"""Tokenize a SMILES molecule or reaction, adapted from https://github.com/pschwllr/Molecular... |
069fea93c90dbdefd89f024ec48fcf5717adc4610e281510cc058e0ba431b66e | Python | 4,181 | 126 | # Copyright 2019 DeepMind Technologies Ltd. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... |
10cb774c53d2029e9e9be4d5acb2a49ffbd8c9a344badb38778b3063516a6696 | Python | 4,181 | 123 | #!/usr/bin/env python
"""
Script: run_dataset_splitting.py
Description: CLI for balanced dataset splitting via Monte Carlo permutation
search. Reads a CSV file with one row per subject, runs
permutation_balanced_splits, and writes the same CSV with an
added 'fold' column (0-indexe... |
144928866eb88a69d942b57ccb10a79067a0f98ca7b499f9c2caa05c77e23b86 | Python | 4,181 | 118 | # -*- coding: utf-8 -*-
#
# Copyright © 2013 Charles E. Vejnar
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at https://www.mozilla.org/MPL/2.0/.
#
import logging
import os
from ..interfaces imp... |
1b1353555c1ef33da17c1f59eb0ee68a1a62f923c9541127a1169b1c035cdd91 | Python | 4,183 | 152 | import matplotlib.pyplot as plt
import mcubes
import nibabel as nib
import numpy as np
from scipy.ndimage import label
from skimage import measure
import os
def marching_cubes(res, name='vessel', level=1, spacing=(0.3, 0.3, 0.3), gradient_direction='descent', offset=0):
verts, faces, normals, values = measure.mar... |
b67813a8936744321c5aaa1e3173c33458b8b65d7399e885f9491e84349d6a26 | Python | 4,184 | 136 | # -*- coding: utf-8 -*-
"""
Created on Fri Jan 24 15:14:41 2020
@author: daniel
"""
from mpi4py import MPI
import d1msn as msn
import plasticity_experiment as pe
import parameters as pp
import numpy as np
import pickle
import json
import scipy.signal as ss
import sys
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
npr... |
6715b4eeb4faa1c78eebff1dec349beb61cf3bec451b6bb14618d0a2444ce078 | Python | 4,185 | 103 | import os.path as osp
import logging
import time
import argparse
from collections import OrderedDict
import options.options as option
import utils.util as util
from data.util import bgr2ycbcr
from data import create_dataset, create_dataloader
from models import create_model
#### options
parser = argparse.ArgumentPars... |
7f96f56c0e29e02fc2227209155b4645f0245bcb3192d8adf5a10a182ed13feb | Python | 4,187 | 141 | #!/usr/bin/env python
import click
from functools import partial
from multiprocessing import Pool
import numpy as np
import os
import pandas as pd
import pickle
from pybedtools import BedTool
from pybedtools.helpers import cleanup
import re
import subprocess as sp
from tqdm import tqdm
import warnings
warnings.filterw... |
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