sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
20ad68a3cc23324c9fa02f8516254d447a4a3f172fe9650e6f751183c61ef27c | Python | 1,256 | 33 | from typing import TYPE_CHECKING
from ray.data._internal.execution.execution_callback import (
ExecutionCallback,
)
if TYPE_CHECKING:
from ray.data._internal.execution.streaming_executor import StreamingExecutor
from ray.data._internal.issue_detection.issue_detector_manager import (
IssueDetectorManager,
... |
ecff52db5bb9287ad4c23e45d5a46a62e9c93f0230139dccfc1fbac6a704d91a | Python | 1,256 | 28 | ####################################################################################################
# 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... |
87f53980fedcd23213f347d7cdf75b11bb024c9baa378be7ec43125c15ec3032 | Python | 1,257 | 47 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import pysam
def main():
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('batch_vcf')
parser.add_argument('cohort_vcf')
parser.add... |
f040dd6bc75f220e6b09c140ffde6c03c2ea90b0d355732d3401b9b18c8b51e0 | Python | 1,257 | 35 | import jieba
import torch
import DataSet
import re
from Config import fix_length, label_list
def x_tokenize(x):
str = re.sub('[^\u4e00-\u9fa5]', "", x)
return jieba.lcut(str)
def getModel(name):
model = torch.load('done_model/'+name+'_model.pkl')
return model
model = getModel('Transformer')
device = ... |
8ee0c2c06db820d882bce2c7ec1a05124def1d87581ddc95294ed1eba5f75a70 | Python | 1,258 | 40 | # -*- coding: utf-8 -*-
"""
This is the implementation of the model corresponding to the pre-print `Iso-orientation bias of layer 2/3 connections: the unifying mechanism of spontaneous, visually and optogenetically driven V1 dynamics`
Rózsa, T., Cagnol, R., Antolík, J. (2024).
https://www.biorxiv.org/ TODO: Update
"""
... |
bffc9d58e5197abea8fedf621798c055029e65e67708d8adad51ad9c0f3fb320 | Python | 1,258 | 40 | # -*- coding: utf-8 -*-
"""
This is the implementation of the model corresponding to the pre-print `Iso-orientation bias of layer 2/3 connections: the unifying mechanism of spontaneous, visually and optogenetically driven V1 dynamics`
Rózsa, T., Cagnol, R., Antolík, J. (2024).
https://www.biorxiv.org/ TODO: Update
"""
... |
27298f18d4dd2640bbd6da053eec325e9582157bc051a8f642276f61b26b7693 | Python | 1,259 | 39 | # --8<-- [start:long]
import pandas as pd
from rich import print
from siapy.entities import Pixels, Signatures
from siapy.entities.signatures import Signals
# Option 1: Step-by-step initialization
# Initialize Pixels object from a DataFrame
pixels_df = pd.DataFrame({"x": [10, 30], "y": [20, 40]})
pixels = Pixels(pixe... |
3927308a9d00350aa957e8a6e5348e24ce2241e0f118bf39883d724a778cb07a | Python | 1,259 | 40 | # -*- coding: utf-8 -*-
"""
This is the implementation of the model corresponding to the pre-print `Iso-orientation bias of layer 2/3 connections: the unifying mechanism of spontaneous, visually and optogenetically driven V1 dynamics`
Rózsa, T., Cagnol, R., Antolík, J. (2024).
https://www.biorxiv.org/ TODO: Update
"""
... |
39ddfefbf07015d851c9674f9a789502094e128f5c0185021ad207475936965d | Python | 1,259 | 31 | """
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.
Constants for Triton kernel operations.
"""
from __future__ import annotations
# Block size for channel vectorization in Triton kernels.
# Mu... |
3ace735ab1399d3f7f4e6e8ae1f9ec3f749891862917e37d1cdded873be2e401 | Python | 1,259 | 40 | class MovingAverage:
window_size = None
current_value = None
observations = None
observation_count = None
use_window = None
def __init__(self, window_size=None, use_window=True):
self.window_size = window_size
self.current_value = 0
self.observation_count = 0
s... |
eac411b3f7dcc0ece38fb23f410d40563ba1115eaba56f05f5af7641220062e2 | Python | 1,259 | 50 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
Wrap bgzip output
"""
import sys
import subprocess
class BgzipFile:
def __init__(self, filename, bgzip=True):
self.filename = filename
self.bgzip = bgzip
def __enter__(self):
# Open output file
if self.is_stdout:
... |
ae62c73accc348653a6493ea4a8b159765c013784abbddf101979fc3d6d25b70 | Python | 1,260 | 54 | import numpy as np
def plot_morphology_xy(morphology, ax):
nodes = morphology.nodes()
x = [node['x'] for node in nodes]
y = [node['y'] for node in nodes]
ax.scatter(x, y, s=0.1, color="k")
ax.set_aspect('equal')
def plot_morphology_zy(morphology, ax):
nodes = morphology.nodes()
y = [n... |
e2f580de6cc3376940460a3ecd59ef6beb347b69392be39b4524daa9b4431b85 | Python | 1,260 | 41 | import sys
import pytest
from ray._common.tls_utils import generate_self_signed_tls_certs
def test_generate_self_signed_tls_certs_returns_tuple():
cert_contents, key_contents = generate_self_signed_tls_certs()
assert isinstance(cert_contents, str)
assert isinstance(key_contents, str)
def test_generate... |
501d765545560c6f84cbaab5dc356758b406695cb2729fbb910c5d0b6eef6a9e | Python | 1,261 | 40 | #!/usr/bin/env python
# This is an executable script that runs an example of every single CliLogger
# function for demonstration purposes. Primarily useful for tuning color and
# other formatting.
from ray.autoscaler._private.cli_logger import cf, cli_logger
cli_logger.configure(log_style="auto", verbosity=999)
cli... |
898a8340d083f56e8c456a73255cc3b80ebd4b99ea804ea968f81947ed518ab3 | Python | 1,261 | 42 | from typing import Any, Callable, Optional
from ray.air.execution._internal.tracked_actor import TrackedActor
class TrackedActorTask:
"""Actor task tracked by a Ray event manager.
This container class is used to define callbacks to be invoked when
the task resolves, errors, or times out.
Note:
... |
f7613eec72749d5b79587b222ed6338c0f80b8a7c8639fb0c12346a842c42d1d | Python | 1,261 | 53 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
Drop records with zero non-reference alleles in AF-annotated VCF
"""
import argparse
import sys
import pysam
from svtk.utils import is_biallelic
NULL_GTs = [(0, 0), (None, None), (0, ), (None, ), (None, 2)]
def prune_allrefs(vcf, fout):
for record in vcf.fet... |
086a7bb6d3fd80a9c698aae448699fb8aab5ef6797562b8ca9e5a051e9e85e12 | Python | 1,262 | 40 | import matplotlib.pyplot as plt
import quantax as qtx
from quantax.symmetry import TotalSz, SpinInverse, C4v
lattice = qtx.sites.Square(10)
N = lattice.nsites
H = qtx.operator.Heisenberg(J=[1, 0.5], n_neighbor=[1, 2], msr=True)
net = qtx.nn.ResSum(16, 16, 3, use_sinh=True)
state = qtx.state.Variational(
net,
... |
3d5b831bc12c81ed9b21893ecc0bd4508764026660de0a3d41da8326297af5d9 | Python | 1,262 | 21 | #!/usr/local/bin/ipython -i
from mozaik.experiments import *
from mozaik.sheets.population_selector import RCRandomPercentage
from parameters import ParameterSet
def create_experiments(model):
return [
#Lets kick the network up into activation
Poiss... |
5b44716a619411b360a511b347608e26ce64ada032e86986a7bfa411b36876f1 | Python | 1,262 | 36 | import os
import pandas as pd
import numpy as np
import tensorflow as tf
from utils import oneHot
from tensorflow.keras.layers import *
if __name__ == '__main__':
num_shuffles = 10
predictions_ala = []
predictions_no_ala = []
WTaa = 'SINSVHT'
aaList = 'ACDEFGHIKLMNPQRSTVWY'
seq = input(f"Plea... |
f1b8fa7ec75046c23b92350b7442dab65b6f30c8ec057a35d977a97f4eb4b7c0 | Python | 1,262 | 39 | """
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, Any
if TYPE_CHECKING:
from fairchem.core.components.reducer impo... |
f4df5121eae3d237bb44672efe107c4fdca5893eca2aa504e61a539dcd44cf03 | Python | 1,262 | 43 | import struct
import numpy
import warnings
from tqdm.autonotebook import tqdm
def packIntAsLong(value):
"""Packs a python 4 byte integer to an arduino long
Parameters
----------
value : int
A 4 byte integer
Returns
-------
packed : bytes
A 4 byte long
"""
return str... |
4df7027b889d79af2830b957bbe316534a5324a54679bf031b82eaefa8bc4feb | Python | 1,263 | 52 | import os
import pytest
from ._docs_examples import (
PROJECT_ROOT,
InstallSandboxCache,
build_python_namespace,
execute_bash_sample,
execute_python_sample,
iter_doc_sources,
runnable_samples,
seed_docs_sandbox,
)
DOC_SOURCES = tuple(
path for path in iter_doc_sources() if runnabl... |
814b3d3c3bfead6f48288022208c763a3e2df7d15272896dddac7943c1f29d46 | Python | 1,263 | 32 | import argparse
import os
# Implementation note:
# This code implements the same python code in the GetSampleBatchPEMap task without alterations.
def main(batch_sample_lists, batch_name_list, batch_pe_files, prefix):
_batch_pe_files = []
with open(batch_pe_files, 'r') as pe:
for line in pe:
... |
27ce0c376b5ba293d383fe8d8651264658445100ae23e97f8a7d5afba2a5c525 | Python | 1,264 | 49 | # %%
import numpy as np
import pickle
import pandas as pd
# from numba import njit
# sessions = ["G", "H", "F"]
sessions = ["H"] # round 2
path = "fit_result5/result_0001.pkl"
with open(path, "rb") as f:
solutions = pickle.load(f)
params = solutions["H"][0][0].keys()
# %% load all solution and make dataframe
... |
813128186b41188289432f48eedb9c328cf99728fe7a046e6dc6126815692b7b | Python | 1,265 | 35 | import torch.nn as nn
from argparse import Namespace, ArgumentParser
from .base import BaseModelConfig
from optuna import Trial
from monai.networks.nets import DynUNet
class DynUNetConfig(BaseModelConfig):
model_name = "dynunet"
def setup_search_space(self, trial: Trial, args: Namespace) -> Namespace:
... |
929333ae7f2a66a344726fe7e9dd58c37e7b9aa68d1a09742de0647b03ebecbf | Python | 1,265 | 25 | ####################################################################################################
# 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... |
65f923d282d9bbc4c0a728211e60a088b6c99b28abeb9b43e3bf899837d23b94 | Python | 1,266 | 41 | from typing import Tuple
import pandas as pd
from data_profiling.config import Settings
from data_profiling.model.summary_algorithms import describe_supported, series_hashable
@describe_supported.register
@series_hashable
def pandas_describe_supported(
config: Settings, series: pd.Series, series_description: di... |
878c8c99bff81a0b4ef32f1fa9277429410aec9017580ee0b9c3ccec9f39717a | Python | 1,268 | 40 |
from enum import Enum, auto
from dataclasses import dataclass, field
import torch
from e3nn.o3 import ReducedTensorProducts
@dataclass
class ModelParameters:
atom_types: list
irreps_in: str = field(init=False) # irreps_in is generated later...
irreps_out: str = field(default="1x0e+1x1e+1x2e", init=Fals... |
d64facbd796462aac9c349b0d72708731a86982e1c26a2858700849ad3b6ac07 | Python | 1,269 | 33 | """rapppid_org URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/4.1/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-b... |
4040bb81bf53efb6e3e5a32aaab2ae786bc3c5d3eb49aa61fcf6451abbb89f7a | Python | 1,270 | 52 | """
test voltage reset to v_reset for LIF neuron
"""
import os
import matplotlib.pyplot as plt
import numpy as np
from spinnaker2 import hardware, snn
def test_lif_neuron_reset_to_zero(do_plot=False):
params = {
"threshold": 1.0,
"alpha_decay": 1.0,
"i_offset": 0.12,
"v_reset": 0.... |
cbc366676758cda78c52ce59cb8cf94d2212f70dc1eefa9d1c2828daf7664628 | Python | 1,270 | 29 | import platform
import socket
import logging
from typing import Dict
# Defaults
home_base_dir = "/home/smadan"
project_dir = "/git/mirna-disease-association-detector-submission"
LOCAL_MLFLOW_TRACKING_URI = "http://localhost:5000"
MLFLOW_TRACKING_URI = LOCAL_MLFLOW_TRACKING_URI
LOGGING_LEVEL = logging.INFO
EXTERNAL_LOG... |
bde3a26a047468eb067e2e15ec48cb7f554536f2289ecdf0c5c2ca38d73224bc | Python | 1,271 | 44 | """
Utility functions for tedana decomposition
"""
import logging
import numpy as np
from scipy import stats
LGR = logging.getLogger("GENERAL")
RepLGR = logging.getLogger("REPORT")
def eimask(dd, ees=None):
"""
Returns mask for data between [0.001, 5] * 98th percentile of dd
Parameters
----------
... |
5297b9d8fb8f271bae2e8bfb812e66231e08e76dd5363629377e6d3334656e50 | Python | 1,272 | 45 | # -*- 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.
#... |
6562ce6c34617a9c435a4868faadd108700c3eb9e55d288eaa4963f5db83e37d | Python | 1,272 | 31 | from .surface_report import write_surface_report
from .threemica_report import (available_threemica_surface_maps,
write_brainspace_threemica_report,
write_threemica_report)
__all__ = ['build_plotter',
'plot_surf',
'make_contour_actor'... |
f5a49f02dcb07c11988def81d0ae3748ff13597cfdc842cef8570bdc64ba5628 | Python | 1,272 | 30 | from mozaik.tools.distribution_parametrization import ParameterWithUnitsAndPeriod, MozaikExtendedParameterSet
from mozaik.sheets.direct_stimulator import Depolarization
from collections import OrderedDict
def add_per_stimulus_current_injection(exp,stimulation_configuration,stimulation_sheet,stimulation_current):
... |
f2ba869b99a6c141e05bfb1a9fbbceae0bf191a9e2219b4b6ace6b5e1661bd94 | Python | 1,273 | 32 | import pandas as pd
from matplotlib import pyplot as plt
import json
import numpy as np
from mpl_toolkits.mplot3d import Axes3D, proj3d
def rewardtoDocking(r: float)->float:
return 10*r/(r-1)
dataDir = "6lu7/log336h_6lu7/data10/"
df = pd.read_csv(dataDir+'/present/scores.csv')
arr = df.values # points ... |
90b77839b4906d16cc4da0dc233fd50ebc4ccdae4fd06c48f333bf9e183b0919 | Python | 1,274 | 39 | import h5py
import numpy as np
import argparse
import sys, os
sys.path.insert(0, os.getcwd())
from warnings import warn
import json
import pandas as pd
def main():
parser = argparse.ArgumentParser(description='Create HDF5 files.')
parser.add_argument('-f', type=str, help='path to dataset config file')
arg... |
c97e105db61909a20261dc22984b2206dad0c8f3e0f01360e95c5e29edb42908 | Python | 1,275 | 27 | import os
import nibabel as nib
import matplotlib.pyplot as plt
root = '/path/to/results/phantom'
pars = ['D','f','vd']
plot_range = {'D':[0.5,1.2],'f':[0,5],'vd':[1.5,2.0]}
scale = {'D':1e3,'f':100,'vd':1}
plot_methods = {'gt':'Ground truth','nlls':'NLLS','seg':'Segmented fitting','bayesu':'Bayesian: Uniform','bayess... |
a684ededdb3918b8354142351d7e17a602bdd0532b4e3a0479340642f0b1b99d | Python | 1,276 | 53 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import pandas as pd
def explode(df, idx_cols, list_col):
"""
Explode a column of lists into one row per list element
"""
df = df.set_index(idx_cols)
df[list_col] = df[list_col].str.split(',')
df = df[list_col].apply(pd... |
af1aa3718e6d5d4af8d809490453dc78aeaaa328be68a21a1624567043b710e6 | Python | 1,276 | 40 | from data_profiling.config import Settings
from data_profiling.report.formatters import fmt, fmt_bytesize, fmt_percent
from data_profiling.report.presentation.core import HTML, Container, Table, VariableInfo
def render_generic(config: Settings, summary: dict) -> dict:
info = VariableInfo(
anchor_id=summar... |
e225fb3d764b7d9b4d2280b261d512f7e7c629a4033a5b33cc57dfed9979607d | Python | 1,276 | 52 | # -*- 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=invalid-name
"""Krylov with analog preconditioner"""
import numpy as np
import matplotlib.pyplot as plt
from torch import device as torch_dev... |
023582ad3ffc657cc64f36b45620c0a7775f640fccd57c511a86fda5e02b8a5a | Python | 1,277 | 47 | from __future__ import annotations
import logging
from pokeformer.preproc.fpocket import run_fpocket
from pokeformer.utils.pdb_utils import get_pdb_path
logger = logging.getLogger(__name__)
def _detect_pocket_impl(
pdb_path,
params,
save_result_path=None,
remove_alt_h=False,
):
if params.backen... |
102759543f56486bf6560b8c4fdc7f9281daeb2dafd6b68a0f5b1240d25aa19b | Python | 1,278 | 37 | from setuptools import setup, find_packages
with open("README.md", 'r') as fh:
long_description = fh.read()
''' https://packaging.python.org/guides/distributing-packages-using-setuptools/ '''
''' https://setuptools.readthedocs.io/en/latest/ '''
setup(
name='nas-bench-graph',
version='1.0',
author='THU... |
b0322b089f6365dbe6d79f20fffb541d51795ac623d7000af9a3614c8f315973 | Python | 1,278 | 55 | # %%
import numpy as np
import pickle
import pandas as pd
# from numba import njit
sessions = ["G"]
path = "fit_result6/result_0001.pkl"
with open(path, "rb") as f:
solutions = pickle.load(f)
params = solutions["G"][0][0].keys()
len(solutions["G"][0][0])
# %% load all solution and make dataframe
# fractions... |
db9a08dc9657e747ca8b08fa7aa66381dc044fb7a3bbbb852108382e2b0a5bd1 | Python | 1,278 | 38 | """Pytest configuration for the doctests in the ``stl`` package.
The examples in the docstrings read files such as
``tests/stl_binary/HalfDonut.stl`` and write files such as ``example.stl``
with relative paths, the way a user would from their own project directory.
Run from the checkout they would leave the written fi... |
173c61d7fee01287c160f7da1fbe428a748ae56c9d5d4f2b9f85b8e58f2f69d2 | Python | 1,279 | 48 | import importlib
# Dynamically import all modules inside the Spark folder
SPARK_MODULES = [
"correlations_spark",
"dataframe_spark",
"describe_boolean_spark",
"describe_categorical_spark",
"describe_counts_spark",
"describe_date_spark",
"describe_generic_spark",
"describe_numeric_spark"... |
554e02aec6cd00986350d06479a49f5df496fc815cab77b680a94ad88944d359 | Python | 1,279 | 29 | import os
import matplotlib.pyplot as plt
import nibabel as nib
import numpy as np
root = '/tmp'
sub = 'phantom'
fig,axess = plt.subplots(2,3,figsize=(3*5,2*5))
for a, axes in enumerate(axess):
for ax,parname, unit, scale, plotmax in zip(axes,['D','f','vd'],['µm2/ms','%','mm/s'],[1e3,1e2,1],[3e-3,0.6,5]):
... |
060197e3efc0528bd1a6437f5a25ea164bb6a2073b57e9c71009c9987b7227ae | Python | 1,280 | 38 | # Copyright 2023 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... |
16154df62b38526fa18ea9c044628ebb2e6ba8e05857186abde1ec65accb7ab3 | Python | 1,280 | 36 | from typing import Any, Callable, Dict, Optional
import pyarrow
from ray.data.block import BlockAccessor
from ray.data.datasource.file_based_datasource import _resolve_kwargs
from ray.data.datasource.file_datasink import BlockBasedFileDatasink
class JSONDatasink(BlockBasedFileDatasink):
def __init__(
se... |
58677c4727e333e680f362b86fb4783100595f11070073764eccea9998a2bb7a | Python | 1,280 | 58 |
"""
This script creates the negative of the input image.
Usage:
python inverse_images_hc-leipzig-7t-mp2rage.py -i <input_image> -o <output_image>
Author: Katerina Krejci
"""
import os
import argparse
import numpy as np
from argparse import RawTextHelpFormatter
from spinalcordtoolbox.image import Image, zeros_l... |
dad2d12274d24dea32c65f4fa9955ed742157e28655a89a27ad63579c40ffd62 | Python | 1,280 | 31 | import sys
import os
sys.path.insert(0, "/srv/home/zgaleday/torch_pgn")
import os.path as osp
from scripts.generate_final_correlations import generate_final_correlations
base_dir = '/srv/home/zgaleday/models/torch_pgn/figure_2'
model_dirs = ['pdbbind_general_rand_fp_hyper/',
'refined_final_pgn/',
... |
e868dc196975f39474edeb96049d7a9d6913226b47ef7833f235a3c08b6cf96f | Python | 1,280 | 37 | from pathlib import Path
import pandas as pd
from data_profiling import ProfileReport
from data_profiling.utils.cache import cache_zipped_file
"""
The "Auto" correlation is an interpretable pairwise column metric of the following mapping:
- Variable_type-Variable_type : Method, **Range**
- Categorical-Categorical ... |
46dcea6d2e921a1950f3eda9061c176495505b6bd2bb3bace6a5ea692e83cc42 | Python | 1,281 | 37 | # Copyright 2022 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... |
9320d2dae5dc798eecd58df600b8efe2816f184ab5d268a8eba7d817f97939e5 | Python | 1,281 | 38 | import torch
import soft_rank_pytorch
from metrics import _rank_data
def spearman_loss(pred, true, regularization_strength, regularization):
assert pred.device == true.device
assert pred.shape == true.shape
assert pred.shape[0] == 1
assert pred.ndim == 2
device = pred.device
soft... |
9c86e32e94ba72adff2601fd54b930b1470a801b66b22f9bf293e35fe7ad9480 | Python | 1,281 | 52 | import sys
import numpy as np
import matplotlib.pyplot as plt
from utils import load_pickle, save_image, read_lines, load_image
# from visual import cmap_turbo_truncated
def plot_super(
x, outfile, underground=None, truncate=None):
x = x.copy()
mask = np.isfinite(x)
if truncate is not None:
... |
fb1d26dd8c9c440b67736c45d6951f0d238b5be0e03c73be9ba73ec4be91564a | Python | 1,281 | 46 | '''verify that my boundaries match tan's computation'''
import os
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from utils import ID2CHAPTER, split_video_id, padded_corr
from utils import EventLabel, TrainValidSplit, DataLoader, HumanBondaries
sns.set(style... |
0af2a7739e3debbc1a6c4de14439dbd4b282c4831c3d8559c4d565d20b75c136 | Python | 1,284 | 32 | from src import main
from src.models import multi_stage
from src.models.Hang2020 import spectral_network
from src.data import read_config
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
config = read_config("config.yml")
config["crop_dir"] = "/Users/benwei... |
a82209161fc7381fcce78fd35e7ed6586f24ef9804cb39b64f373e32bb538ffa | Python | 1,284 | 28 | ####################################################################################################
# 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... |
948c2a6f6d74409113c4ca997a78e7714f8d21524380d969bc109eb2ab004033 | Python | 1,285 | 56 | import os
def results_file(directory, site, batch, modelname, filename):
"""
Define the output results file
"""
batch = str(batch)
if os.path.isdir(directory):
pass
else:
os.mkdir(directory)
batchdir = os.path.join(directory, batch)
if os.path.isdir(batchdir):
... |
e0f7008b08a810041a65432c32f6ec1de881fac29c599559a332175dbc87ab0c | Python | 1,285 | 39 | # THIS FILE HAS BEEN AUTOGENERATED. To update:
# 1. modify the `_deps` dict in setup.py
# 2. run `make deps_table_update``
deps = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax... |
95d0a9272b4f8a450e01a40c1adaa78436fc6e22134805422d2fe86ed7df3f06 | Python | 1,287 | 39 | # Configuration file for the Sphinx documentation builder.
#
# For the full list of built-in configuration values, see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Project information -----------------------------------------------------
# https://www.sphinx-doc.org/en/master... |
ed471f2da25fceeab2ac8055228a772aec8c555d71b8604d492e6489dd5f962d | Python | 1,287 | 43 | import os
import gzip
import requests
import numpy as np
def load_data(kind='train'):
base_url = 'http://yann.lecun.com/exdb/mnist/'
labels_filename = '%s-labels-idx1-ubyte.gz' % kind
images_filename = '%s-images-idx3-ubyte.gz' % kind
# Download labels file
labels_url = base_url + labels_filename... |
9bf61c2569417a05e43310a90d078a95ffca9ff041246cfee043c442670b0f3f | Python | 1,289 | 40 | # built-in dependencies
from typing import Any, List, Union, cast
# 3rd party dependencies
from numpy.typing import NDArray
# project dependencies
from deepface.commons.onnx_utils import run_session
from deepface.models.FacialRecognition import FacialRecognition
from deepface.commons.logger import Logger
logger = Lo... |
b3fef66f453a70d099b430fa2959f0fc9d3415325e67784f96c3c4c5c70123cd | Python | 1,289 | 69 |
#from utility import * # check utility.py for functions documentation
#from component import *
#A = np.arange(10)
#print('input list = ',A)
import ex
import sys
import numpy as np
class Component(object):
def initialize(self):
ex.log("From python: initialize ")
ex.log(sys.path[0])
... |
cabaffb79deb7446a2ba0da3f405c18ab9dddacf43949070c9e3df6f865e698e | Python | 1,289 | 43 | from __future__ import annotations
import torch.nn as nn
from fairchem.core.models.escaip.utils.nn_utils import Activation, get_linear
def get_feedforward(
hidden_dim: int,
activation: Activation | None,
hidden_layer_multiplier: int,
bias: bool = False,
dropout: float = 0.0,
input_dim: int |... |
22fa713117e3d61e1a8846cd8569010ad54e60fd3aba2e55fd27970634a159a3 | Python | 1,291 | 47 | #! /usr/bin/env python
import argparse
import os
import subprocess
import sys
from glob import glob
import shutil
import re
parser = argparse.ArgumentParser()
parser.add_argument("filename")
parser.add_argument("--results_folder", "-r", default="./")
parser.add_argument("--nreads", "-n", default=20000000)
args = pars... |
b79617cc8b39c9d29afceef592be9877f9cdabd54c1552d838fdd678bdef7cd9 | Python | 1,291 | 46 | import cv2 # noqa: F401 — preload libtiff before HIPT/torchvision shadows it (omicverse vendored patch)
import argparse
from utils import load_tsv, write_lines, read_lines
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('inpfile', type=str, help='e.g. demo/cnts.tsv')
parser.add_arg... |
3a4f58879ba0cd687061572482340d8cd6995a8414aeee96cbb6d89f6d4f03a5 | Python | 1,292 | 32 | # Copyright 2023 The HuggingFace Inc. team. 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... |
822144f29080897ee63eeaf7efa085123e47c8676fa7ee1e0cb3c21184df5f98 | Python | 1,292 | 34 | import sys
import os
sys.path.insert(0, "/srv/home/zgaleday/torch_pgn")
from torch_pgn.train.run_training import run_training
from torch_pgn.train.hyperopt import hyperopt
from torch_pgn.args import TrainArgs, HyperoptArgs
args = HyperoptArgs()
args.from_dict({'raw_data_path': '/srv/home/zgaleday/IG_data/pdbbind_refi... |
d648ae5f1b48be335c342b85ceb8279d402ab2c66f194f41addba5273b092bf8 | Python | 1,292 | 48 | """
This file serves as a documentation example for disaggregated tokenization.
"""
import ray
from ray.data.llm import vLLMEngineProcessorConfig, build_processor
# __disaggregated_tokenization_start__
config = vLLMEngineProcessorConfig(
model_source="unsloth/Llama-3.1-8B-Instruct",
engine_kwargs={"max_model... |
f76e6d60cad689e7e3695b529634f8c8c45771d5255daf4b5eb4d5a6278a88f1 | Python | 1,292 | 48 | {
'dataset_loader_train': {
'__factory__': 'model.DatasetLoader',
'path': 'aclImdb/train/',
},
'dataset_loader_test': {
'__factory__': 'model.DatasetLoader',
'path': 'aclImdb/test/',
},
'model': {
'__factory__': 'model.create_pipeline',
'use_cuda': T... |
3bcdde605beb4dbced776d703e17cffcf821369841d985b96c318f30705256f4 | Python | 1,293 | 38 | """NumPy batches use the same analysis path at every batch size."""
import numpy as np
import pytest
from deepface.modules import demography, modeling
class FixedAgeModel:
def predict(self, img):
assert img.shape == (1, 224, 224, 3)
return 32
@pytest.mark.parametrize("batch_size", [0, 1, 2])
d... |
3c3869f297672582737c207df8207487fabf9bbbb57b1bd70e4afc44ea471571 | Python | 1,293 | 38 | from typing import Optional
import torch
from rising.ops import torch_one_hot
__all__ = ["one_hot_batch"]
def one_hot_batch(
target: torch.Tensor, num_classes: Optional[int] = None, dtype: Optional[torch.dtype] = None
) -> torch.Tensor:
"""
Compute one hot for input tensor (assumed to a be batch and th... |
972d05e3efc39d83e87d6d331ab02f63894d15a4214992fed4862e871348e3c4 | Python | 1,295 | 32 | """
Tests for :func:`mozaik.meta_workflow.experanto_export.resolve_datastore`, which finds the
datastore a given ``(trial, chunk)`` was simulated into by globbing a stable name prefix
inside the results directory.
What is easy to get wrong there -- and did go wrong -- is that the results directory is a
literal path be... |
012a199626a82420af80369f99ed4dc28f03545667e3f0851d4aa0c2d82dce56 | Python | 1,296 | 38 | from typing import Any, Optional, Tuple
from ray.util.annotations import DeveloperAPI
@DeveloperAPI
class NodeLaunchException(Exception):
"""A structured exception that can be thrown by a node provider during a
`create_node` call to pass additional information for observability.
"""
def __init__(
... |
7858ba03f1a49b3ba5a7ba14354dd737fcafbbd04f02ae8a3aa94e8b4d07dd88 | Python | 1,296 | 47 | import unittest
from unittest.mock import Mock
import optuna
import pfrl
class TestOptunaPrunerHook(unittest.TestCase):
def test_dont_prune(self):
trial = Mock()
trial.should_prune.return_value = False
optuna_pruner_hook = pfrl.experiments.OptunaPrunerHook(trial=trial)
env = Moc... |
8a772b760b8c714a2279e824c4c05b12090ede9545e0463870c05d683e0db4c3 | Python | 1,296 | 43 | from abc import ABCMeta, abstractmethod
from typing import List
from mmengine.model import BaseModule
from lqit.edit.structures import BatchPixelData
from lqit.registry import MODELS
from lqit.utils import ConfigType, OptConfigType, OptMultiConfig
class BaseGenerator(BaseModule, metaclass=ABCMeta):
"""Base clas... |
d0b5294ebbf4d4544ba52f4b76d5387ef6f31f82d72cd3fb69b8f9aa88df7615 | Python | 1,296 | 37 | import numpy as np
from pfrl import explorer
class AdditiveGaussian(explorer.Explorer):
"""Additive Gaussian noise to actions.
Each action must be numpy.ndarray.
Args:
scale (float or array_like of floats): Scale parameter.
low (float, array_like of floats, or None): Lower bound of acti... |
feeb5329f7c1ee82c3f09d152a1244136941b13b5dff064d892a17c9929f7456 | Python | 1,296 | 38 | # 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
235da83dc22e535a32e8f97745f09803848e3b9b619186436a217c3698b87897 | Python | 1,298 | 43 | from ipywidgets import Box, widgets
from data_profiling.report.presentation.core import Collapse
class WidgetCollapse(Collapse):
def render(self) -> widgets.VBox:
if self.content["button"].anchor_id == "toggle-correlation-description":
collapse = "correlation"
else:
collap... |
109e7f5e4870c7e2ff1d3e260b26c116dccc3404f1eecd0c04fcd21be7ae5085 | Python | 1,299 | 48 | import os
import subprocess
import json
from spinnaker2.helpers import global_word_address
APPNAME = "../../../s2-sim2lab-app/host/experiment/app/experiment"
PE = (1,1,0)
memfile = "../../../s2-sim2lab-app/chip/app-pe/s2app/arm_sanity/binaries/s2app_arm.mem"
exp_spec = {
'active_pes' : [PE],
'mem_fi... |
6b951153f2dea47c28759a5f83c3cb00955b23ecf01b2e0a43eb617c8ca4117d | Python | 1,299 | 39 | # built-in dependencies
from typing import Optional, Dict, Any
# project dependencies
from deepface.commons.logger import Logger
logger = Logger()
# pylint: disable=too-few-public-methods
class AuthService:
def __init__(self, auth_token: Optional[str] = None) -> None:
self.auth_token = auth_token
... |
d028fda8267becfe96abff6b25a90d4e59c81721fb2a769df368bd10875e6a70 | Python | 1,299 | 43 | from typing import Optional
import numpy as np
import torch
def torch_one_hot(target: torch.Tensor, num_classes: Optional[int] = None) -> torch.Tensor:
"""
Compute one hot encoding of input tensor
Args:
target: tensor to be converted
num_classes: number of classes. If :attr:`num_classes`... |
201b25f4c35d9f0ba445348e63158b021967e908879e6aef55ea2266f758a299 | Python | 1,300 | 40 | # 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.
from unicore.data import BaseWrapperDataset
def collate_tokens_coords(
values,
pad_idx,
left_pad=False,
pad_to_length=None,
pad_to_multiple=1,... |
ee2c93d759d009a8766e81d2f0c7d541fc217bd39f20c4a102c023041a5ec4ab | Python | 1,300 | 31 | # This class works
import numpy as np
import pandas as pd
import numpyro.distributions as dist
import numpyro
import jax.numpy as jnp
class tobit_dist(numpyro.distributions.Distribution):
arg_constraints = {}
def __init__(self, mean, sigma):
#import pdb; pdb.set_trace()
self.loc = mean
... |
20b1edf3480ec4ce2a673cbe918150ef0933e834af9e99fa013b5710b97bd54d | Python | 1,301 | 49 | import numpy as np
def generate_bigclam(F, B=None, D=None, p_no_comm=0, seed=None):
"""Produce the graph according to the BigCLAM model.
Parameters
----------
F : np.ndarray, shape [N, K]
Nonnegative community affiliation matrix.
B : np.ndarray, shape [K, K]
Compatiblity matrix.
... |
3389d537b72c773711940814f36be63060fa885d747d4a0e3d7c7720b35316c9 | Python | 1,301 | 37 | from pathlib import Path
from openmm import unit
from openmm.app import CharmmCrdFile, CharmmParameterSet, CharmmPsfFile, PDBFile
from .base import EndstateCorrectionBase
from ..system import read_box
class EndstateCorrectionCHARMM(EndstateCorrectionBase):
def _get_mm_topology(self) -> CharmmPsfFile:
ps... |
a4614dc35502f2a8e5d1a8cd8f2bc527e22bc0e12812199e04f63929f7c827a1 | Python | 1,301 | 41 | """aihwkit example 19: Analog summary on LeNet.
Extracts analog information in the form of a printed table.
The information can also be accessed via the returned AnalogInfo object.
"""
# pylint: disable=invalid-name
# Imports from PyTorch.
from torch import nn
# Imports from aihwkit.
from aihwkit.nn.conversion impo... |
ebef4e1a6455569e5f98646b365702633ac0fcf31cdda7e1b1e45b5c026c69f4 | Python | 1,301 | 21 | """OFFLINE converter: run only in the trusted historical sklearn environment."""
import hashlib,sys
from pathlib import Path
import joblib,numpy as np
p=Path(sys.argv[1])
expected='792cce50db528a20c9769842a0efac26aa9a77e5e04ba76819ee500a78d29566'
if hashlib.sha256(p.read_bytes()).hexdigest() != expected:
raise Valu... |
9cfa737538e41c1636d233f26c8f21916fd2ca8f7bac7f1bb7ff4a50ab67754c | Python | 1,302 | 50 | import os
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from utils import padded_corr
from utils import EventLabel, TrainValidSplit, HumanBondaries
sns.set(style='white', palette='colorblind', context='talk')
tvs = TrainValidSplit()
evlab = EventLabel()
hb ... |
45988d1efab348c6442ffd8e477218deaa4d2e681c37d2e21bf1482d6ebba1e8 | Python | 1,303 | 49 | import pytest
import torch.nn as nn
from sinabs.backend.dynapcnn import DynapcnnNetwork
from sinabs.backend.dynapcnn.mapping import edmonds, make_flow_graph, recover_mapping
from sinabs.from_torch import from_model
ann = nn.Sequential(
nn.Conv2d(1, 20, 5, 1, bias=False),
nn.ReLU(),
nn.AvgPool2d(2, 2),
... |
aab8ccb04a5f76ec71297ec77fcff93f4affb038e4ec01fe059de6523af0dc18 | Python | 1,303 | 44 | #!/usr/bin/env python
# coding: utf-8
import torch
import torch.nn as nn
def init_weights(m, mean=0, std=0.1, bias=0):
if isinstance(m, nn.Linear):
nn.init.normal_(m.weight, mean, std)
nn.init.constant_(m.bias, bias)
if isinstance(m, nn.LSTM):
for name, param in m.named_parameters():
... |
cd3f2801e60701f612a8e111cc5fa8dde11512137018ed688df78487153c5a84 | Python | 1,303 | 59 | from math import pow
from math import floor
from os import makedirs
from os import get_terminal_size
from os.path import join
from os.path import exists
from os.path import normpath
from os import sep
def conditional_makedir(path):
try:
import pathlib
p = pathlib.Path(path)
p.parent.mkdir... |
1f780d12196f182efec622cac48b0ad3f9fde0a3fb5ed68bb492b64b846918b2 | Python | 1,306 | 53 | """
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
import os
import numpy as np
import pytest
from ase.io import read
from fairchem.core.datasets import... |
2ff0e2ddaa060d8535c38707e2f0c914ed8d59bf230a96f19ddecb56217cd82a | Python | 1,306 | 69 |
#from utility import * # check utility.py for functions documentation
#from component import *
#A = np.arange(10)
#print('input list = ',A)
import ex
import sys
import numpy as np
class Component(object):
def initialize(self):
ex.log("From python: initialize ")
pass
def sta... |
68d97df82d16f7b147b269c390250d751498e59e31a410b1af7327901ba8d5d2 | Python | 1,306 | 40 | # Modified from https://github.com/dbolya/tide
# This work is licensed under MIT license.
# Defines qualifiers like "Extra small box"
def _area(x):
return x['bbox'][2] * x['bbox'][3]
def _ar(x):
return x['bbox'][2] / x['bbox'][3]
class Qualifier:
"""Creates a qualifier with the given name.
test_fun... |
c475d699e6068016809da52c7c94cd4301a690743cdc41eea677d95eb6d8238f | Python | 1,306 | 57 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
"""
"""
import argparse
import pysam
import pandas as pd
def main():
parser = argparse.ArgumentParser(
description=__doc__,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('vcf')
parser.add_argument('scores')
... |
c76b2e9ff807e5cc2a5b55e0e83bde4dd6df3b7fac9553555d3f2fe4b7bfad94 | Python | 1,307 | 39 | # Copyright 2022 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... |
9b5e2cf4c767ffcb8b7adbf9a9f47cf3f05b97b6696efb369342cf0f27dbbb66 | Python | 1,308 | 49 | #!/usr/bin/env python3
import os
from pathlib import Path
from snakebids import bidsapp, plugins
try: # Works when run as a package
from hippunfold.plugins import (
atlas as atlas_plugin,
download as download_plugin,
)
from hippunfold.workflow.lib import utils
except ImportError: # Works... |
b17bf984e9586fe437d39ae36e4a1ad0b1a8f08bdea7517557c46b8f2583b330 | Python | 1,308 | 40 | import nltk
import re
# def tokenize_sentences(document):
# document = document.replace(r"\n", r" ")
# document = document.replace(r"\t", r" ")
# document = re.sub(r"\s\s+", r" ", document)
# document = re.sub(r"\.” ([A-Z])", r".”. \1", document)
# sentences = nltk.sent_tokenize(document)
# cl... |
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