sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
fe73ad57272f5308689296a33774010237e0ba73ce1e5f4bce8aef6744cbc6a9 | Python | 1,931 | 63 | import enum
import logging
import os
from typing import TYPE_CHECKING, Optional
from .ranker import DefaultRanker, Ranker
if TYPE_CHECKING:
from ... import DataContext
from .resource_manager import OpResourceAllocator, ResourceManager
logger = logging.getLogger(__name__)
DEFAULT_USE_OP_RESOURCE_ALLOCATOR_V... |
a0aa724dc6c3f9f9c8ded8ad81426b79c6421a39aaa2362d0f0db8548e218210 | Python | 1,932 | 67 | import os
# __enable_start__
import os
import uuid
import ray.train
import ray.train.torch
# The detector reads these on the driver when you construct the trainer.
os.environ["RAY_TRAIN_ENABLE_NCCL_HANG_DETECTOR"] = "1"
# Log a confirmed hang and capture diagnostics without failing the run.
# Set to "fail" to raise ... |
d9b535b69c0e521efa92cbd803951d292ec903db9fbb3a66f008777412b720e3 | Python | 1,932 | 75 | #%%
import numpy as np
import seaborn as sns
import pandas as pd
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure
import argparse
from tqdm import tqdm
import json
import os
import numpy as np
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
i... |
380db6b2b6ca88d02182ec871b3e05522b7272fe2b899817e7663daa1d8063ee | Python | 1,934 | 38 | from tests.objects import test_node
from neuron_morphology.morphology import Morphology
from neuron_morphology.constants import *
from neuron_morphology.validation.morphology_statistics import \
morphology_statistics
import unittest
from mock import patch
class TestMorphologyStatistics(unittest.TestCase):
"""... |
e5b72147af6917d1dd901f1742dea5d8f22b3b9d55c90ff54167e34fee73e690 | Python | 1,934 | 67 | from __future__ import print_function, unicode_literals, absolute_import, division
from six.moves import range, zip, map, reduce, filter
from ..utils import _raise, consume
import warnings
import numpy as np
from scipy.stats import laplace
class ProbabilisticPrediction(object):
"""Laplace distribution (independ... |
1ecb9dc5f2359c553e3c7c7c4c4b4b187041d86ef381ea3c1cce65085720c3c0 | Python | 1,935 | 31 | """Builds the in-browser CandyCrunch (web/) into a folder for GitHub Pages: the page, the wheels it installs (this checkout's candycrunch, glycowork) and
the example run. Run by .github/workflows/pages.yml; locally, e.g. python packaging/build_web.py _site --glycowork ../glycowork, then serve _site"""
import argparse
i... |
37262c23eb8f7c7f751815f597d2b334e41c2bf6e390230aed0ad25670eff70a | Python | 1,935 | 61 | # dataset settings
dataset_type = 'lqit.RTTSCocoDataset' # `lqit` means the scope
data_root = 'data/RESIDE/RTTS/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', scale=(1333, 800), keep_rat... |
a2d20048c28466a744133a02c2ebb8765298c3cab2ea64ec64b1c6b4b729e426 | Python | 1,936 | 52 | import inspect
from google.protobuf.json_format import MessageToDict, MessageToJson
"""
This module provides a compatibility layer for different versions of the protobuf
library.
"""
_protobuf_has_old_arg_name_cached = None
def _protobuf_has_old_arg_name():
"""Cache the inspect result to avoid doing it for eve... |
0d6d76689f4931badc8129572fdacef3486515e70496416b2ce28147427d6bea | Python | 1,938 | 79 | import sinabs
project = "Sinabs"
copyright = "2019-present, SynSense"
author = "employees of SynSense"
master_doc = "index"
extensions = [
"myst_nb",
"pbr.sphinxext",
"sphinx.ext.autodoc",
"sphinx.ext.mathjax",
"sphinx.ext.napoleon",
"sphinx.ext.autosummary",
"sphinx.ext.viewcode",
"s... |
cd7ad47abb8d71790b93a6b86d8d4f778c2552491967ef7efc9b830aba764899 | Python | 1,938 | 60 | import argparse
import functools as ft
import swap_errors.analysis as swan
def create_parser():
parser = argparse.ArgumentParser(
description="estimate distances between analysis points"
)
parser.add_argument(
"data_file",
type=str,
)
parser.add_argument(
"-o",
... |
25682999713e3a83fcdcc6457572b7e3004f576f87c685b209d19743a660f337 | Python | 1,939 | 42 | from IsoNet.models.unet.blocks import conv_blocks
from tensorflow.keras.layers import MaxPooling2D, UpSampling2D, MaxPooling3D, UpSampling3D, AveragePooling3D
from tensorflow.keras.layers import Concatenate
def build_unet(filter_base=32,depth=2,convs_per_depth=2,
kernel=(3,3),
batch_norm=... |
b0c47bd99bc9f496bff74d1ffcd3adf131ecfe112aa0856c4ba406f1db11030c | Python | 1,939 | 57 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
02292bf737e6b504a4277a4f26fb158461dee059e33f61d93424b7501971c34b | Python | 1,940 | 87 | import pdb
import torch
import torch.nn as nn
from latent_time_stepping.time_stepping_models.transformer import (
EncoderLayer,
PositionalEmbedding
)
class ParameterEncoder(nn.Module):
def __init__(
self,
embed_dim: int,
num_heads: int,
embed_hidden_dim: int,
num_la... |
2a29c8d4dfcddefb73ef7a1656dea174e78d5d00142d2874452f1d0f15e1cb34 | Python | 1,940 | 62 |
from banditopt import algorithms, objectives
P_STED = 150.0e-3
P_EX = 2.0e-6
PDT = 10.0e-6
# LASER_EX = {"lambda_" : 488e-9}
# LASER_STED = {"lambda_" : 575e-9, "zero_residual" : 0.01}
LASER_EX = {"lambda_" : 635e-9}
LASER_STED = {"lambda_" : 750e-9, "zero_residual" : 0.005, "anti_stoke": False}
DETECTOR = {"noise" ... |
78e68a3de8db1e22dd58abb543c8e93c08e0f681e38ac36e997db67875024769 | Python | 1,940 | 52 | import torch
import torch.nn.functional as F
from torch.nn import ReLU, Sequential, Linear, BatchNorm1d, Dropout, GRU
from torch_geometric.nn import NNConv, Set2Set
from torch_pgn.args import TrainArgs
class GGNet(torch.nn.Module):
"""Stock network from QM9 prediction paper gilmer et. al"""
def __init__(self... |
7de5cbc2b851098d32442388e7951128de035cdaa84c90576222f022ed865032 | Python | 1,940 | 63 | import collections.abc
from typing import Any
import numpy as np
import torch
__all__ = ["numpy_collate", "do_nothing_collate"]
default_collate_err_msg_format = (
"default_collate: batch must contain tensors, numpy arrays, numbers, " "dicts or lists; found {}"
)
def numpy_collate(batch: Any) -> Any:
"""
... |
8767dbdac6e231ac3c3f00c44267c9b4f10c659c89ccaebafb7a7f839faea286 | Python | 1,940 | 43 | # -*- coding: utf-8 -*-
from parameters import ParameterSet
from mozaik.models import Model
from mozaik.connectors.fast import UniformProbabilisticArborization
from mozaik import load_component
class VogelsAbbott(Model):
"""
This is implementation of model of self-sustained activity in balanced networks from:... |
d450f4d4a822f26d49ce74c30e27b43c04e4a86b81a7046074c6083393398589 | Python | 1,941 | 47 | import numpy as np
import torch
from torch.utils.data import Dataset, DataLoader
from KS_equation import dynamics
class KSDataset(Dataset):
def __init__(self, batch, n_steps, L, l, dt, prediction_steps):
super().__init__()
self.batch = batch
self.n_steps = n_steps
self.L... |
05cff308cdc9bdd51dc4c20b303cfdf1a43edc5d7b0b53cca0b919d1ce2b24ec | Python | 1,942 | 60 | # dataset settings
dataset_type = 'lqit.URPCCocoDataset' # `lqit` means the scope
data_root = 'data/URPC2020/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=... |
aec93d835eb9ac74682a478b822353d19839d84ff22422139415fa32858aecf8 | Python | 1,942 | 51 | import argparse
from pathlib import Path
import torch
import utils
from lightning_modules import LigandPocketDDPM
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('checkpoint', type=Path)
parser.add_argument('--pdbfile', type=str)
parser.add_argument('--resi_list', t... |
fe3ff8d30798b5d354f01f3999513ee28020d1eeed53a81cb15ab9c467247be5 | Python | 1,942 | 56 | """Base Configuration."""
# Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or... |
248d0042daf952e8116ddb8a1a35642f7d4b2ad1d2b7261e84de5df28bb2f2df | Python | 1,943 | 104 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
# OC20
# NOTE: this is the setting for slab and adslab
from __future__ import annotations
VASP_FLAGS = {
"ibrion": 2,
"nsw": 2000,... |
885749c02d083a1427bb74a142ad99e86b9ffb9dca3b26c0fd47fa1b4a56e6f1 | Python | 1,943 | 51 | from Bio import SeqIO
import random
import os
import sys
from pathlib import Path
import pandas as pd
project_root = '/ccb/cybertron/khchao/splam-analysis-results'
def main():
SEQ_LEN = 800
THRESHOLD = 100
ref_junc_f = f'{project_root}/train/results/ALL_RefSeq/REF_junctions/ref_d_a.sort.bed'
test_junc_... |
f9e9db5f2d7bf9c930d8665255383ebc78f769f391dc5c16703cbaf3631a6cf4 | Python | 1,943 | 61 | import numpy as np
import pandas as pd
import pytest
from siapy.core.exceptions import InvalidInputError
from siapy.features.spectral_indices import (
_convert_str_to_list,
compute_spectral_indices,
get_spectral_indices,
)
def test_convert_str_to_list():
input_data = "R"
expected_output = ["R"]
... |
2af2861652af98ebf8c671d9abe3d26cad27b02a96b1f349ec4176382c9f85b0 | Python | 1,944 | 57 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
9e8fd523301541b9cdf77b4342710827907ecfa1c4752bd783a9153f44306aec | Python | 1,944 | 57 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
b0fd6db793947e23e8c346513c26176ea705a2c7dcf6ffbb7d89bafeab3f8adf | Python | 1,945 | 58 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
d6f78ebfb839e7ba1346475fb663ef5ccc71d7444ced0ff975e60a9be83d2f1f | Python | 1,945 | 46 | """edgeofpy main module"""
from edgeofpy.avalanche import (detect_avalanches,
plot_pdf,
plot_cdf,
fit_powerlaw,
fit_third_exponent,
dcc,
... |
5e121c64ddfede869e3df76a5b05ac0e0ae1d322db4cc003aa6969f1687a1831 | Python | 1,946 | 47 | """The Ray autoscaler uses tags/labels to associate metadata with instances."""
# Tag for the name of the node
TAG_RAY_NODE_NAME = "ray-node-name"
# Tag for the kind of node (e.g. Head, Worker). For legacy reasons, the tag
# value says 'type' instead of 'kind'.
TAG_RAY_NODE_KIND = "ray-node-type"
NODE_KIND_HEAD = "he... |
81abe3a52300b22381e41164c460aa74ff69f234cecbaf8dbd6e271af30dc3f9 | Python | 1,948 | 22 | # Autogenerated by nbdev
d = { 'settings': { 'branch': 'main',
'doc_baseurl': '/scAnnot',
'doc_host': 'https://changebio.github.io',
'git_url': 'https://github.com/changebio/scAnnot',
'lib_path': 'scAnnot'},
'syms': { 'scAnnot.core': { 'scAnnot.core.ann... |
e0e8c86d92067a4083300c4e91d78328a2cb81d33b967d4f36eee04d6dc093ad | Python | 1,948 | 41 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
e96c4b46e2ef9372d2399a839f8a4d01538cf193229f94f0e5dfb1f8a494993a | Python | 1,949 | 62 | # -*- coding: utf-8 -*-
"""
EWH - I did not make this, but this is what is used for the LeicaWaterCam script
so that a user can draw the area they want to get the light reflection off the
water from.
"""
from pyqtgraph.Qt import QtCore, QtGui, QtWidgets
class paintableqlabel(QtWidgets.QLabel):
mod... |
1f0e20dc8d54b39e5b1439ba557ba2ce15c97bba142918a00d79e060753315c7 | Python | 1,950 | 69 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import os
import argparse
import gzip
def chr_extract(pin, chr):
out = ''
for i in pin[7].split(';'):
if i.split('=')[0] == chr:
out = i.split('=')[1]
return out
def vcf_stat_readin(filename):
fin = gzip.open(filename, 'rb... |
7e3318cece181dd6865c41b8cf317ebf0fd04eeca2c49139ec9a502bc30b7ffc | Python | 1,950 | 48 | import pandas as pd
from src.commons.process_dataframe import rename_df_col, insert_new_col_from_two_cols
from src.commons.process_number import cal_SEM
if __name__ == '__main__':
to_excel = False
# read data
PATH = "../data/ms2_triplets_4_data/"
DATA = "preprocessed_triplets_4.xlsx"
data = pd.re... |
067f68b6b5cb40cac12b91a1f2260c743622e31f8985c47809c6274d04377a09 | Python | 1,951 | 66 | """Compute statistical description of datasets."""
import importlib
from typing import Any
import pandas as pd
from tqdm import tqdm
from visions import VisionsTypeset
from data_profiling.config import Settings
from data_profiling.model.pandas.summary_pandas import (
pandas_describe_1d,
pandas_get_series_desc... |
1d77e1e37ba5e6777119aa6f2448f64caab1a6d84a56e5d2367996caceaaa10e | Python | 1,951 | 43 | from model import (ProteinInteractionNet, Trainer, Tester)
from uncertaintyAwareDeepLearn import VanillaRFFLayer
from utils import (
load_configuration,
initialize_logging,
set_random_seed,
get_computation_device,
initialize_scheduler,
train_and_validate_model
)
def main():
# --- Pre-Traini... |
9251ffdf9f2a75c926988a29375b9063b07690f96dcfdfbcd44610e0a4c45d25 | Python | 1,951 | 50 | ####################################################################################################
# Copyright (c) 2023, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is free softw... |
207459cf559e877e37e8f2cc0980e4a6005270242730f859b73a3bc642f76751 | Python | 1,953 | 60 | # dataset settings
dataset_type = 'lqit.URPCCocoDataset' # `lqit` means the scope
data_root = 'data/URPC2020/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=... |
403739f43353be1a209db7121d84d2f7d2b5f81d98d10dcbd77caab381ff92a3 | Python | 1,953 | 60 | # dataset settings
dataset_type = 'lqit.URPCCocoDataset' # `lqit` means the scope
data_root = 'data/URPC2020/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=... |
ea968ea0fbf1b6eb89d33fb1e04e1fef9ed6e73e25c02cc3c6bdd9f5e1b25cc9 | Python | 1,953 | 60 | # dataset settings
dataset_type = 'lqit.RUODDataset' # `lqit` means the scope
data_root = 'data/RUOD/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
... |
1ef0bcfe0bf47d1a13c0a2f9e390bb0c0df3f9ac22ad0c46434e7342e36cf72f | Python | 1,954 | 40 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
2a78c9c1c6cfc8e77c853815dffccba6fc2ce1cd00fedebf7b563cd4e8dc4fcc | Python | 1,954 | 77 | #!/usr/bin/env python3
"""
Example script demonstrating how to use CEBRA for time contrastive learning.
"""
import sklearn.decomposition
import torch
import cebra
import cebra.datasets
if __name__ == "__main__":
device = "mps"
input_data = cebra.datasets.init("rat-hippocampus-single-achilles")
latent_... |
9193520c3c2fcd8f55e534941fa27b1af1309fb2db02c2e0e923943ecdde0201 | Python | 1,954 | 72 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import argparse
import csv
import os
import pysam
import sys
def read_vid_list(vid_list):
ids = []
with open(vid_list) as fin:
reader = csv.reader(fin, delimiter='\t')
for row in reader:
vid = row[-1]
if vid not in ids:
... |
409f0f7da37addb8f655ffb5a7f85b89b58aa0fbd0b7572f26c8fd67b00d598d | Python | 1,956 | 87 | import numpy as np
from numba import jit
from tqdm import tqdm
def sim_latent(N_CELLS, N_DIM):
"""
Draws a latent space coordinate for each cell
randomly from a unit gaussian
"""
return np.random.normal(size=(N_CELLS, N_DIM))
def sim_umi_counts(N_CELLS, mid, scale):
"""
Simulates counts... |
479da80d0256c014c32fe7ba990096f015940d62f855d4ecf77239795fd765a0 | Python | 1,956 | 45 | import os
import numpy as np
from omegaconf import OmegaConf
import argparse
import time
from utils.tool import read_img, save_img
def merge(origin_path, decompressed_dir, chunks_dir):
origin_data = read_img(origin_path)
decompressed_data = np.zeros_like(origin_data)
chunk_names = os.listdir(chunks_dir)
... |
8dbd6ab5c1750b51ef28776b9688359b0018767453e19998fc6ac65c60af866c | Python | 1,957 | 54 | #
# Copyright (c) 2021, NVIDIA CORPORATION.
#
# 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 ... |
acd6704ff638d065df217978c16bea71bf92e52b2e4957c637252955ebe8615b | Python | 1,957 | 68 | # Randomly select impact cases for combinations and write to files.
import numpy as np
import random
import os
def combination(case_num, nn, K, path):
with open('injury_degree_both_MPS', 'r') as data:
data = data.readlines()
thres_len = round(len(data)/K - 1)
injury_degree = np... |
05401358e38ff764e4dae0077ef44a93ce0f91b106d78cdc183347421481c9a5 | Python | 1,959 | 64 | import sys
import numpy as np
# Add package path
packagepath = '../kcorePercolation' # Manually specify the path to your script
sys.path.append(packagepath)
from utils import kcorePercolation as kp # Import custom utility functions
def generate_networks(networkpath, L=1000, ks=[5, 10], zetas=[4, 5, 100]):
"""
... |
8d22e78e10dabe4a1f7ec021a7f7af3eb22b0c9d04cfc3dbe390d81174c4a85e | Python | 1,959 | 61 | # Copyright (c) DP Technology.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
from functools import lru_cache
from unicore.data import BaseWrapperDataset
class RemoveHydrogenDataset(BaseWrapperDataset):
def __init__(
... |
e916a11ccd0de047d5f149bb694c71301706c40f072b4650b1e8052b7c14226a | Python | 1,959 | 59 | # -*- coding: utf-8 -*-
# (C) Copyright 2026 IBM. All Rights Reserved.
#
# Licensed under the MIT license. See LICENSE file in the project root for details.
# pylint: disable=too-many-instance-attributes
# pylint: disable=too-many-lines
"""Runtime parameters for settings at simulation time."""
from dataclasses impo... |
689778f3c682a6366f961494d1656df6675682118e2e90c46ba1faaa1e65c4e3 | Python | 1,961 | 67 | import pandas as pd
import pytest
from pyspark.sql.types import IntegerType, StringType, StructField, StructType
from data_profiling.config import Settings
from data_profiling.model.spark.sample_spark import get_sample_spark
# FIXME: Move to data
@pytest.fixture()
def df(spark_session):
data_pandas = pd.DataFram... |
a76bbeb20901878e885aba4779b80f439deaaa9b7367de83d400fb8682604427 | Python | 1,962 | 54 | import argparse
import numpy as np
import pandas as pd
def main():
parser = argparse.ArgumentParser()
parser.add_argument('input', type=str, help='Input UKB covariate file')
parser.add_argument('--indiv', type=str, help='Path to subset of individuals')
parser.add_argument('--add_cov', nargs=2, action='... |
e5575b27626ed1eee9da576279ea4fb96ac7b8c37d83ec8f49f24092387bce7c | Python | 1,962 | 47 | import numpy as np
from scipy import sparse
from scipy.optimize import linear_sum_assignment
import time
def GetPerformance_Jaccard_2(GTMasks, Masks, ThreshJ=0.5):
'''Calculate the recall, precision, and F1 score of segmented neurons by comparing with ground truth.
Inputs:
GTMasks (sparse.csr_matrix... |
8906234c99f3ce2441a114e53a6692790352fe156955d2fa0d306c4ce94a69db | Python | 1,963 | 72 | import os
import subprocess
import json
from spinnaker2.helpers import global_word_address
"""
Simple example that takes an input value, sends it to a PE, where it is
multiplied by a constant depending on the PE-ID.
The result is read out after the experiment and compared to the expected value.
"""
def global_pe_id... |
8a8ebd12f7c24c8a6cbd57ef53bef3a8ea24bf63db11126b99e00d9f1e0239f2 | Python | 1,963 | 56 | from typing import Any, Dict, Optional, Sequence, Tuple
import pandas as pd
from data_profiling.config import Settings
from data_profiling.model.duplicates import get_duplicates
@get_duplicates.register(Settings, pd.DataFrame, Sequence)
def pandas_get_duplicates(
config: Settings, df: pd.DataFrame, supported_co... |
b3006d662c2251204493052e51bce40bf43de1c2463ab9b66be7bbc40a20ee96 | Python | 1,963 | 60 | import abc
from enum import Enum
from typing import Iterator, Optional, Set
from ray.data._internal.datasource_v2.interfaces.file_manifest import FileManifest
from ray.data.block import BlockMetadata
from ray.util.annotations import DeveloperAPI
@DeveloperAPI
class MetadataType(Enum):
NUM_ROWS = 0
NUM_BYTES ... |
d359b29b79685c5d59ebbc26b4b679e0b55934974d786d68ba07e6aff8451134 | Python | 1,963 | 46 | import torch
from ..distances import DotProductSimilarity
from ..utils import common_functions as c_f
from ..utils import loss_and_miner_utils as lmu
from ..losses.base_metric_loss_function import BaseMetricLossFunction
from ..losses.mixins import WeightRegularizerMixin
class NormalizedSoftmaxLoss(WeightRegularizerM... |
f4b3e5f3ff6dc5424b3874dd732ea4b0691599eaf99df546a450ac0ddc7666e3 | Python | 1,965 | 60 | # dataset settings
dataset_type = 'lqit.DUODataset' # `lqit` means the scope
data_root = 'data/DUO/'
backend_args = None
train_pipeline = [
dict(type='LoadImageFromFile', backend_args=backend_args),
dict(type='LoadAnnotations', with_bbox=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
... |
20132250d89fd752091af2c69ab086f6b210ef6346c0ad87682b96637e681d4b | Python | 1,969 | 68 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from ase.constraints import FixSymmetry
from ase.optimize import FIRE... |
51dda9cebfdcd03f0d80adf4f9b49f7d44707445b0ba104bf016ea6ed2d443d4 | Python | 1,969 | 65 | r"""
Batch correction module
"""
import os
from typing import List, Optional
import torch
from torch import Tensor
import numpy as np
from sklearn.utils.extmath import randomized_svd
from ..utils import get_free_gpu
def dual_pca(X:np.ndarray, Y:np.ndarray,
dim:Optional[int]=50,
singular:Opti... |
3e7a9a027a0ae666dc88befd893cc4f181c84f6c8c1868ec08d44d7ae77cf11f | Python | 1,970 | 44 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
b8f01ada2081e90a536bf7cd7944e5ad2b13dc7970169704edc9baf76c5b836b | Python | 1,970 | 75 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
2c6d81220f27cdb96d5fec93fec3851097e0296a4a29352914c3c1fb3ab1f0bc | Python | 1,971 | 60 | #!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.
# Calls the FXC compiler and generates a depfile from the compiler's standard output
# Lines in the standard output matching:
# Resolved to [D:\foo\bar.h]
# Produce rules in the depfile
import re, ... |
c0b3f773a776d6cc0cc2d061d266b68bcc031767c2fb20f77d1b8b40e2c0e16e | Python | 1,971 | 75 | import os
# CI environment is slow, set the timeout to 60 seconds
os.environ["RAY_CGRAPH_get_timeout"] = "60"
os.environ["RAY_CGRAPH_submit_timeout"] = "60"
# __cgraph_cpu_to_gpu_actor_start__
import torch
import ray
import ray.dag
@ray.remote(num_gpus=1)
class GPUActor:
def process(self, tensor: torch.Tensor):... |
15c9dbaee4e43a7743b0fe9a2e4d12457a961f725877632fa4efda6fc67c12bd | Python | 1,972 | 57 | import numpy as np
import pandas as pd
import sklearn.metrics
def decide_stertor_pred(row, threshs):
"""Pick class from logits using NNRank method"""
row_classif = row > threshs
for i in range(4):
if not row_classif[i]:
return int(max(i - 1, 0))
return 3
full_df = pd.read_csv("an... |
4ef9539fba37ebae72d3da251e820021fda91dd1247a6ab03b3e74e6da989fb3 | Python | 1,972 | 46 | import tensorflow as tf
from projectmetis.python.models.model_def import ModelDef
from projectmetis.python.models.keras.optimizers.fed_prox import FedProx
class CifarCNN(ModelDef):
def __init__(self, metrics=["accuracy"]):
super(CifarCNN, self).__init__()
self.metrics = metrics
def get_mode... |
60d9b720a2f31048cb781d9aa44c5e09057660d5160812ed7dd32adabe827d69 | Python | 1,972 | 59 | # built-in dependencies
from typing import Any, List, Tuple, Union
# 3rd party dependencies
import cv2
import numpy as np
from numpy.typing import NDArray
# These functions are copied from Minivision's Silent-Face-Anti-Spoofing Repo
# licensed under Apache License 2.0
# Ref: github.com/minivision-ai/Silent-Face-Anti-... |
921a2655949c22ca1319345710ac8ee8be9c5ae3a62fd9b5e3843d0756632e69 | Python | 1,972 | 68 | import json
import sys
import time
import boto3
import click
from ci.ray_ci.utils import ci_init, logger
from ray_release.test_automation.state_machine import TestStateMachine
from ray_release.util import get_write_state_machine_aws_bucket
AWS_WEEKLY_GREEN_METRIC = "ray_weekly_green_metric"
@click.command()
@clic... |
9a2bda8abcedecc37c461a1cbe540ad93af1462a339f5ddffdd3501a15ead7e9 | Python | 1,972 | 61 | import pytest
from flask import Flask
from deepface.api.src.app import create_app
from deepface.api.src.modules.core import routes
@pytest.mark.parametrize(
"content_type", ["application/x-www-form-urlencoded", "multipart/form-data"]
)
@pytest.mark.parametrize(
"image",
["image.jpg", "https://example.com... |
919ad53808b35dc502f78cb109b3b9142cef2e00af62977d154bea1eff485004 | Python | 1,973 | 71 | import gym
import gym.spaces
import numpy as np
import pytest
import pfrl
class ActionRecordingEnv(gym.Env):
observation_space = gym.spaces.Box(low=-1, high=1, shape=(1,))
action_space = gym.spaces.Discrete(3)
def __init__(self):
self.past_actions = []
def reset(self):
return self.... |
f6d565da4b20b0355e29e95fe53c18f89ee867020dccbf5db463559531d534f2 | Python | 1,973 | 55 | import logging
from typing import Any, Dict
import ray
from ray._common.logging_constants import LogKey
class CoreContextFilter(logging.Filter):
TASK_LEVEL_LOG_KEYS = [
LogKey.TASK_ID.value,
LogKey.TASK_NAME.value,
LogKey.TASK_FUNCTION_NAME.value,
]
@classmethod
def get_ray_c... |
92cb20a525595ab56955c28394ff27ed07699a9251dc83896ef1f1bdda4262c7 | Python | 1,974 | 59 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
9bd3cb733a61b003e70da51b769e9423ae676c6c44d1a2140e86095aefba6f91 | Python | 1,975 | 40 | from data_processing.data_utils import *
from data_processing.embed import *
import os
# This script will process the raw data and embed using ESM-2.
"""First, process the raw Bernett data"""
def make_bernett_interactions(dataset, target_dir, fasta):
negative_file = f"{DIR}{intra}_neg_rr.txt"
positive_fil... |
a98cfed950ef414197ec63f0039f21a6575f146b0d63522e22d593b30b01b0fa | Python | 1,975 | 72 | """
Copyright (c) Meta Platforms, Inc. and affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
Uncompresses downloaded S2EF datasets to be used by the LMDB preprocessing
script - preprocess_ef.py
"""
from __future__ import annotations
i... |
1fc79a875ed6efda3910f5d9467e83073e4abdb708dc16b834dc25909b44b7b9 | Python | 1,977 | 63 | import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from stats import compute_stats, moving_average
sns.set(style='white', palette='colorblind', context='talk')
cpal = sns.color_palette()
def plot_learning_curve(
data, ylabel='MSE', window_size=1, alpha=.3, final_error_winsize=100, color=cpal... |
01a93729087f55b513da4ddf0e570b5be3ca72ddbc379b09ca65d0c3aeb93fe5 | Python | 1,979 | 58 | import logging
from contextlib import nullcontext
from typing import List, Union
import torch
import torch.distributed # noqa: F401
from ray.air._internal.device_manager.torch_device_manager import TorchDeviceManager
logger = logging.getLogger(__name__)
class TPUTorchDeviceManager(TorchDeviceManager):
"""TPU ... |
270e1e501ac5044b48a1b456755cc34484857d800ea00596c7dc5063f0af527a | Python | 1,979 | 61 | import tensorflow as tf
import numpy as np
from IsoNet.preprocessing.simulate import TwoDPsf
import mrcfile
# def loss_wedge_mae(y_true,y_pred):
def wedge_power_gain(y_true,y_pred):
alpha = 0.15
y_pred_np = y_pred.numpy() # in the shape of [chanels,side,side,side,n]
N = y_pred_np.shape[-1]
cube_l... |
af792b3903065d058cddb26e76ebbb0bb4a8bda333a1c970d597fa163455a8a5 | Python | 1,979 | 44 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
77d239dbdded91213bfbf89a18b7966ab017564a5687d146a51f3387d04cc68e | Python | 1,980 | 75 | # Determine the appropriate fitting interval based on the goodness of fit,
# the error of the solution and the fitting range.
# Requirements: 1. The goodness of fit is greater than 0.99;
# 2. On the premise that the fitting range is as large as possible,
# the solution error should be as small as possible.
import n... |
20328084eb158ba71fc130ba7871d80db664d9284b3350bbc6ad80a3b2b10d87 | Python | 1,981 | 57 | # coding=utf-8
# Copyright 2023 HuggingFace 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 or ag... |
9104e2d1b51d6fb99d25c5045866008a3fc72ccb1525b29088af5bb844747c97 | Python | 1,981 | 67 | """
Compatibility shim for the optional ``anndataoom`` dependency.
omicverse's Rust-backed out-of-memory AnnData support is provided by the
external ``anndataoom`` package (install via ``pip install omicverse[rust]``).
If that package is not installed, this module provides no-op fallbacks so
omicverse's core functions... |
b7e58df649a4a268b73e5f21713df1cd8b9c37bc142b401d6d84f78989640d7a | Python | 1,981 | 64 | import logconfig
import logging
import logging.config
def setup_logger( name, config ):
'''
Returns a logging.getLogger instance with name and configured with dictConfig using config
@param name - Name to give the logger(passed to logging.getLogger
@param config - Valid logging.config.dict... |
5e4fd313d2b4d3060a22c5eaa6356f04954376cc1b1085b9fca374a5297ad98d | Python | 1,982 | 53 | import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
if __name__ == "__main__":
tags = ['Total Weight', 'Activation', 'Decay', 'STP']
dev_id = 0
reps_per_op = 10000
float16 = pd.DataFrame()
float32 = pd.DataFrame()
M = 64
while M <= 4096:
... |
ca774e964ccf51f5a16892e13c28a3e0551887fd19fc6dceb03b5999a94713ed | Python | 1,982 | 68 | """Testing center of mass calculation for layer-activity"""
import numpy as np
import nibabel as nb
import glob
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
subs = ['sub-05', 'sub-06', 'sub-07', 'sub-08', 'sub-09']
subList = []
comList = []
durList = []
modalityList = []
for sub in subs... |
83d86b69e2163c066e677566939c077c9be8e8f28bac91715e37467670d168bb | Python | 1,983 | 58 | import numpy as np
import matplotlib.pyplot as plt
from lib5c.util.plotting import plotter
@plotter
def plot_dd_curves(row, col, before, after, repnames=None, log=True, **kwargs):
"""
Plots a comparison of distance dependence curves before and after scaling.
Parameters
----------
row, col : np.n... |
885f9662cde81d0e5f2d6cb18fdda91f40647ef6b16111a7f71b4e2f0b9a6a38 | Python | 1,983 | 67 | import os
from setuptools import find_packages, setup
import versioneer
try:
import builtins
except ImportError:
import __builtin__ as builtins
builtins.__RISING_SETUP__ = True
def resolve_requirements(file):
requirements = []
with open(file) as f:
req = f.read().splitlines()
for r... |
a5b9d6940ab1a7704659bd516711b02fea3628b5286e761de08546d876aa3fd5 | Python | 1,985 | 55 | import pathlib
path = pathlib.Path.cwd()
if path.stem == 'tmb_survival':
cwd = path
else:
cwd = list(path.parents)[::-1][path.parts.index('tmb_survival')]
import sys
sys.path.append(str(cwd))
import pickle
import numpy as np
import pysam
from sklearn.neighbors import KernelDensity
from tqdm import tqdm
import ... |
bb73e391a3893adf3425e94d71ea9ffb52fc48bd9a8bebda7355f665e7e6bde5 | Python | 1,985 | 53 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
2617d2933738f5ec0144dff1f91b5f71addedb8a77598770e23d933c19d17d63 | Python | 1,986 | 61 | # -*- coding: utf-8 -*-
# (C) Copyright 2020, 2021, 2022, 2023, 2024 IBM. All Rights Reserved.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.
#... |
2f3b59682475bf19a4a101fe7b2ce568ed4deeff1d8deb563499d3739f28c4a3 | Python | 1,987 | 43 | ####################################################################################################
# Copyright (c) 2016 - 2024, EPFL / Blue Brain Project
# Author(s): Marwan Abdellah <marwan.abdellah@epfl.ch>
#
# This file is part of NeuroMorphoVis <https://github.com/BlueBrain/NeuroMorphoVis>
#
# This program is fre... |
ea67330082b4c20390486ce10fddba964c535ae499c3daab0a0b7716df59558c | Python | 1,987 | 67 | import os
import pandas as pd
from data_profiling.model.summarizer import ProfilingSummarizer, format_summary
from data_profiling.model.typeset import ProfilingTypeSet
base_path = os.path.abspath(os.path.dirname(__file__))
def test_summarizer(config):
pps = ProfilingSummarizer(typeset=ProfilingTypeS... |
cf81cc7899f6e8a4e4c4ab232e1aa7610a50e936003f7bf0d4059e8924b161dd | Python | 1,988 | 59 | # Copyright 2026 Google LLC
#
# 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
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
fcc0f332ad0915949a0c1e40295a773be584454dbd8b69d2c612e4b077b6989a | Python | 1,988 | 58 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
28cc6e187d982fa46d22ce7ff3de21adf708c7edaf24d26aeaca830ed59e0521 | Python | 1,989 | 64 | # stdlib dependencies
from typing import Any, List, Union
# 3rd party dependencies
from numpy.typing import NDArray
# project dependencies
from deepface.models.demography.DemographyUtils import RACE_LABELS
from deepface.models.demography.onnx.OnnxDemography import OnnxDemography
from deepface.commons.onnx_utils impor... |
bc4b60c1e57a2531b7712374bc5727a3f814d4ee5c486a75eb6d996fda3af445 | Python | 1,990 | 53 | # encoding: utf-8
r"""
This module contains visualization code not conforming the Plotting framework
defined in the mozaik.visualization.plotting module.
Most of this code is likely being used as a debugging visualization tools or is
generic visualization tools that can in turn be used by plotting algorithms.
"""
imp... |
1d412c72bd07c6433908d7f1843f07c1a977ffdbd2061b41408b38ac25a4af2d | Python | 1,991 | 48 | import torch.nn as nn
from src.networks.discriminator.utils import DiscriminatorNetworks
from src.networks.discriminator.taming import TamingDiscriminator
from src.networks.discriminator.baseline import BaselineDiscriminator
from src.networks.discriminator.baseline_2d import BaselineDiscriminator2D
def get_discrimin... |
566f9f4ea43edb2a431daf2497b035956ba3b9a4710dbc4aab63b5bf38b3f9c5 | Python | 1,991 | 55 | from textwrap import wrap
all_aaa_file = "../data/all_aaa.fa"
with open(all_aaa_file, 'w') as of:
of.write(">AllAs"+"\n")
all_aaa_str = "A" * 80
all_aaa_str = all_aaa_str + "\n"
for x in range(40):
of.write(all_aaa_str)
of.write("A" * 24)
of.write("\n")
all_aaa_file = "../data/repat_4a... |
87366a68f66327f74a3ecd0878b9d79d4f74ffc996ab2f408999d0ee8b077545 | Python | 1,992 | 58 | # Copyright 2021 Google LLC
# 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
# https://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, sof... |
f422ee98d164d320ab216615707e4532cba846b50ce2cad863b8aaec838f9d9e | Python | 1,992 | 68 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import pandas as pd
import numpy as np
import scipy.stats as ss
def choose_parent_counts(stats):
# If the children don't agree, pick the strongest
is_child = (stats['sample'].str.endswith('p1') |
stats['sample'].str.end... |
3a46627297f5cc93ef8076b8e8ba001bcf6638679db0973d02297612f9f4860a | Python | 1,993 | 66 | """Sub-agent that performs document search and summarisation."""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any, Iterable, List, Protocol, Sequence
class VectorStore(Protocol):
"""Minimal protocol for vector stores used by :class:`ResearchAgent`."""
def search(s... |
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