sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5889da5e17220655884d5a2fcfc3a1c9caa57e263d01161328e5d77e5baf5db7 | Python | 23,132 | 601 | import keras
from keras.src import backend
from keras.src import tree
from keras.src.api_export import keras_export
from keras.src.distillation.distillation_loss import _convert_loss_to_function
from keras.src.models.model import Model
from keras.src.saving import serialization_lib
@keras_export("keras.distillation.D... |
59a98f6f21d573fef2e51b486876f66b554a9991dfc7821f8f62d2dd6c2875d0 | Python | 23,133 | 538 |
from cfg import *
from flatmapper import FlatMapper
sys.path.append('atlasoverlay')
import atlasoverlay as ao
hex2rgb = lambda x : tuple(int(x.lstrip('#')[i:i+2], 16) for i in (0, 2, 4))
class BrainPlotter:
def __init__(self, a = 1, atlas_overlay_dir = './', flatmapper_dir = './', data_dir = './',
... |
e920e249faf0256fe24118093d2bacd3ff2bdd18d6b2487b68fda7cd21b38b31 | Python | 23,133 | 608 | """
GTN Search Library - Interface to the GTN SQLite database.
Provides search over Galaxy Training Network tutorials and FAQs
using SQLite FTS5 full-text search with BM25 ranking.
"""
import logging
import os
import re
import shutil
import sqlite3
from dataclasses import dataclass
from datetime import (
datetime... |
b6fd4a5187a56b6e6af5e929735333b7d28bba0cb9002d2c0f30359910ade180 | Python | 23,140 | 573 | import numpy as np
import pytest
from absl.testing import parameterized
from keras.src import backend
from keras.src import layers
from keras.src import ops
from keras.src import testing
from keras.src.testing import test_utils
class AttentionTest(testing.TestCase):
def test_attention_basics(self):
# No ... |
057d2a60f1c8d89937203654c1f2696e909f46bf16bf2f51e95b83be1c63246c | Python | 23,160 | 639 | import logging
from typing import Dict, Optional, Union
import torch
from e3nn import o3
from e3nn.math import soft_one_hot_linspace
from e3nn.nn.models.gate_points_2102 import Network as GateNetwork
from e3nn.nn.models.gate_points_2102 import smooth_cutoff
from e3nn.nn.models.v2106.gate_points_networks import Message... |
609d624e80b1db11863155a2565cdc3dcf9b965efc6ea6fd2e3174d2f2b26157 | Python | 23,166 | 673 | """The typed batch envelope and the collate door (extract memo D9 + item 5).
Every batch that reaches the model travels as ONE :class:`BatchEnvelope`:
positional args, kwargs, the INPUT-DERIVED row count, the auxiliary
attention mask, and a JSON-portable disclosure that rides the manifest and
the resume signature. Coe... |
dbb52986ff934f927f920e3493b038cf78c9e1e9049abe37e78f15f42d826b52 | Python | 23,170 | 580 | """r29 capture/validation hardening pins (round-32 re-attack closures).
F1 (HIGH/SECURITY): the r28 storage-rebind ancestry barrier (91fff81c) failed
open for the LAYOUT-fact family. A storage-SWAPPING ``t.data = rhs`` receiver's
own label is correctly refused by the barrier (rung 1 of
``_resolve_layout_rooting_labels... |
d1d9356ea131cb8afca3ceb92e5a920d760c0063e42638979176753366ee7c99 | Python | 23,171 | 399 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
6be2087f64ab63e1904c8d57f52adcced33fe7f68149317f58517abd6cd2805a | Python | 23,175 | 613 | """SO(3) diffusion methods."""
import numpy as np
import torch
from scipy.spatial.transform import Rotation as scipy_R
import logging
import os
from scipy.spatial.transform import Rotation
import pickle
import scipy.linalg
### First define geometric operations on the SO3 manifold
# hat map from vector space R^3 to L... |
e5600fdd430289b7bff29c57145c3eeeffeb803b718f380ee4959fb5a816c873 | Python | 23,179 | 583 | # Copyright (c) 2022 PaddlePaddle 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 app... |
a95a238ab51e19aa1647418a79cb4d503a0c5b9c8241cc182eba86ee3dee17ef | Python | 23,191 | 426 | """
The proposed methoed: GloDyNE
---------------------------------
limit=0.1 # limited computational resources i.e. the upper limit # of selected nodes
# NOTE: limit i.e. $\alpha$ in our paper
num_walks=10, walk_length=80, # random walk hyper-parameters
... |
92924933da5b1262ea4c38382dd8ca0f0ed6f5c92972e8176154c3a5762e14e1 | Python | 23,194 | 588 | from collections import namedtuple
from jax import random, grad, jit, lax, vmap
import jax
import jax.numpy as jnp
import numpy as np
from jax.scipy.stats import multivariate_normal
from jax.scipy.stats import t as studentst
import optax
import functools
import seaborn as sns
import scipy
import sys
import os
import ma... |
ebd8f6204ce5fd5efc5c3702d7556b43706dd7fb0edcf1e48aff8e1f27b1d413 | Python | 23,213 | 583 | # Copyright (c) 2022 PaddlePaddle 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 app... |
579abcb7bfdc6572de61f416320caaa050153c8d348a2432fddd3569ee9efa09 | Python | 23,218 | 558 | """Environment-fingerprinted golden resolution for the god-lane oracles (M13).
The byte-identity oracles (surface-v1, viz identity, legacy artifact, state
keysets) freeze REGRESSION baselines, not cross-environment identities: a
different torch/python build can legitimately change qualnames, float
formatting inside re... |
03d2b373205d078b5f95b1edf0508e17ac15c942560d76025a2859131b77fd1c | Python | 23,251 | 497 |
import sys
import numpy as np
import pandas as pd
import random
import pkg_resources
#from importlib import resources
from collections import defaultdict
from sklearn.preprocessing import OneHotEncoder
from tensorflow.keras.activations import relu
from tensorflow.keras.models import Model
from tensorflow.keras.l... |
c0d2b87f118e3033f6fc95fb08da144608e92a9493f4d28019fdf2ea8d019080 | Python | 23,257 | 768 | """
Histograms
"""
from __future__ import annotations
from typing import Any, Optional, Sequence
import itertools
import numpy as np
import pandas as pd
import seaborn as sns
from .. import plot, reg, funcs
from ..model import moduleDB as MD
__all__: list[str] = [
"module_endpoint_hists",
"plot_ang_pars",
... |
148405f3007e6fdf9d6d35fe8b75023e09f161e59c7e23d9905ea45cc4d573ca | Python | 23,261 | 551 | ''' Fast rasterization of cell coordinates into images.
Implementation of STalign.normalize, STalign.rasterize and
STalign.rasterize_with_signal (see their docstrings for the parameters). The
results equal those of the original per-cell loop up to floating point
rounding (relative differences ~1e-15).
How it works
-... |
a3c75150b58afa7982031fdb06be0e78f63eed5bbd88fb814a4343baccbeaf83 | Python | 23,274 | 567 | import logging
from typing import Any, Dict, List, Union
import numpy as np
import numpy.typing as npt
import torch
from ase import data as ase_data
from e3nn import o3
from pymatgen.analysis.graphs import MoleculeGraph
from pymatgen.core.structure import Molecule
from torch_geometric.data import Data
from torch_geome... |
d7fee2c5044cd863fff8a5451d28e9f5070db0ff1f37d5bcb56182cb776c10fe | Python | 23,285 | 813 | """
Classes and methods for managing nested dictionaries and lists
"""
from __future__ import annotations
from typing import Any
import copy
import json
import pickle
import typing
import agentpy.sequences
import pandas as pd
__all__: list[str] = [
"AttrDict",
"load_dict",
"save_dict",
"bidict",
... |
e1704bbe864798896d96bba03c350a807dd60b122076e41f160881665ff19683 | Python | 23,285 | 746 | #!/usr/bin/env python
#
# Copyright 2005 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 of... |
72bfedbd8f68de95c944c5f2b35faa0f517cd1f7938c9e1db661d9e966e1d38d | Python | 23,301 | 506 | import argparse
import gzip
import pathlib
import logging
import numpy as np
from Bio.PDB import PDBParser, Polypeptide
from constants import AMINO_ACID_INDICES
from scipy.spatial.transform import Rotation
def get_arguments():
"""Fetch command-line arguments"""
argument_parser = argparse.ArgumentP... |
ef71cb1006a39d9b8c24d141ae48f7c2560c75cbff3fb98ffda2c570247d8d6a | Python | 23,301 | 582 | # Copyright (c) 2022 PaddlePaddle 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 app... |
f54f59ae0da1b35b5dc9f2a6b7e77726b0321fb355e9e34c5e52f3240b8ac673 | Python | 23,301 | 536 | import json
import pandas as pd
import os
import glob
import torch
from torch.utils.data import Dataset, DataLoader, ConcatDataset, random_split
from torchvision import transforms
import hashlib
from PIL import Image, ImageDraw
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
na... |
e645cdd6b523d36ae63289caeed65c4bc82453820c5e5a67a1dacce63350fe8f | Python | 23,302 | 558 | """Unit tests for sensor-level analysis."""
import mne
import numpy as np
import pytest
from mne_rsa import rdm_epochs, rdm_evokeds, rsa_epochs, rsa_evokeds, squareform
from numpy.testing import assert_equal
def load_epochs():
"""Load some of the MNE-Sample data epochs."""
path = mne.datasets.sample.data_pat... |
d4d55e5829ac94125fcb8546c05517a8e58b0700ec9a6f611b10e8e125f1bc8a | Python | 23,308 | 552 |
import ipdb
import torch
import torch.nn as nn
from ourmodel.loss_transfer import TransferLoss
import torch.nn.functional as F
class AdaRNN(nn.Module):
"""
model_type: 'Boosting', 'AdaRNN'
"""
def __init__(self, use_bottleneck=False, bottleneck_width=256, n_input=128, n_hiddens=[64, 64], n_output=6... |
39fc66409105327a0823042e9b62b83df6d3c029fcaefbc0df1c25bdf3584d83 | Python | 23,327 | 664 | # -*- coding: utf-8 -*-
import os
import glob
import pysam
import pytest
import shutil
import gzip
from pathlib import Path
from TestUtils import load_and_convert, make_data_files, slurp_file, CBCF_DATADIR
def setUpModule():
make_data_files(CBCF_DATADIR)
def read_header(filename):
data = []
if filenam... |
8ee52cf595ae3bc24c001d68221cb905cb475e012ab7f4cdd5e199cc965651ec | Python | 23,333 | 602 | # Copyright (c) 2021 PaddlePaddle 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 app... |
1bc7540e5a73f748a11d0d09b5e51f24269dcce88713d431decdf1e6b2091511 | Python | 23,351 | 302 | from __future__ import print_function
import sys
import logging
from statistics import mean
from svim.SVSignature import SignatureDeletion, SignatureInsertion, SignatureInversion, SignatureTranslocation, SignatureDuplicationTandem, SignatureInsertionFrom
from svim.SVIM_clustering import consolidate_clusters_bilocal, ... |
27b407f7e9cb90eed270f5c875aae03336bb1f95202dc4753a6b8d58e9fde111 | Python | 23,352 | 686 | import random
import numpy as np
import pandas as pd
import scipy.sparse as sp
from numba import jit
import scanpy as sc
from sklearn.svm import SVC
from sklearn.neighbors import kneighbors_graph
from torch.utils.data import Dataset
import torch
def setup_seed(seed):
"""
Set random seed
Parameters
--... |
28401859a66cd54f66144c510aacc5bdafa4732c0687e63e57926c20cd41c5c1 | Python | 23,363 | 726 | import pickle
from decimal import Decimal
from itertools import count
from random import shuffle
from time import time
from unittest.mock import Mock, patch
import pytest
from celery import states, uuid
from celery.events import Event
from celery.events.state import HEARTBEAT_DRIFT_MAX, HEARTBEAT_EXPIRE_WINDOW, State... |
bb99de12b34e3a202f863846203d2c73d691cfb83a2f8f5cc5c05464368ce688 | Python | 23,367 | 676 | # -*- coding: utf-8 -*-
# %% [markdown]
# # Find Fixed Points
# %% [markdown]
# The goal of this tutorial is to learn about fixed point finding by running the algorithm on a simple data generator, a Gated Recurrent Unit (GRU) that is trained to make a binary decision, namely whether the integral of the white noise inp... |
bad12efd8d18c3bb726e408e1dd0d2acfded5a8f1b50e9de78debfccf9b84b3d | Python | 23,396 | 547 | """
Copyright (C) 2022 Giansalvo Gusinu <profgusinu@gmail.com>
Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the "Software"),
to deal in the Software without restriction, including without limitation
the rights to use, copy, modify, m... |
034941931d095dc6c722b61c23545a1b66aec56275f9a59dcb5f591b0b853028 | Python | 23,403 | 564 | # encoding: utf8
"""
PyTorch implementation of the HMAX model of human vision. For more information
about HMAX, check:
http://maxlab.neuro.georgetown.edu/hmax.html
The S and C units of the HMAX model can almost be mapped directly onto
TorchVision's Conv2d and MaxPool2d layers, where channels are used to store the... |
558891f373ca79a87fc70308f646d26ec63a39c633bea51ef76c47afec33e62e | Python | 23,453 | 644 | """Regression tests for the dual predicate-consolidation review (opus + sol).
Every test here encodes one reproducer from the 2026-08-11 predicate reviews
(``results/review-predicate-opus.md`` / ``results/review-predicate-sol.md``).
Tests marked FIX failed at 4f568d5f (pre-fix arming proof); tests marked PIN
character... |
654a4d9ac7d07ca0bfe20246d4dd843e454a9c0993b112a72916d61658edf9c6 | Python | 23,460 | 692 | # SOURCE: vendored from https://github.com/igashov/DiffLinker @ fafbe47afe6cf068e9e1b23e7145377fb0f89f89
# (src/egnn.py -- the real E(3)-equivariant EGNN `Dynamics` network used as the noise-
# prediction backbone of DiffLinker's fragment-conditioned diffusion model. The nn.Module
# architecture (GCL, EquivariantUpdate... |
711f93b13ceccd205da03fd3dc8288cad6d0ddf92ae1b993692e3a6a6c1066dd | Python | 23,463 | 413 | import argparse, time, logging, os, sys, math
import gc
import numpy as np
import mxnet as mx
import mxnet.ndarray as F
import gluoncv as gcv
gcv.utils.check_version('0.6.0')
from mxnet import gluon, nd, gpu, init, context
from mxnet import autograd as ag
from mxnet.gluon import nn
from mxnet.gluon.data.vision import ... |
862a87f41c000c09adf1493f45103f8df5ba57877718dd4bada03a770bf42c05 | Python | 23,476 | 664 | # Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
"""Plot multidimensional uniform time series."""
from typing import Union, Sequence
import matplotlib.axes
import numpy as np
from .._data_obj import Datalist, Dataset
from .._names import INTERPOLATE_CHANNELS
from . import _base
from ._base import (
PlotTy... |
49ed3153ff0cc5802f8bd7e4c7bed5909d68492ba85ebae5e07500e68698f69e | Python | 23,483 | 492 | import numpy as np
#try:
# import statsmodels.api as sm
#except ImportError:
# import statsmodels as sm
import statsmodels as sm
from statsmodels.genmod.generalized_linear_model import GLM
from tqdm import tqdm
from ..utils import gislib, constants, utils
from ..core.flowdataframe import FlowDataFrame
distfunc =... |
80dd28cdf28694e1afefdcc13535177ea7b9c92931b3487eb16998696259b543 | Python | 23,488 | 669 | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import copy
import pickle
import warnings
import matplotlib.pyplot as plt
from sklearn.model_selection import KFold
import shap
from typing import Tuple
import xgboost as xgb
from lifelines.utils import concordance_index
plt.style.use("bmh")
np.r... |
60afa1dbcd646667f08d182e6ca4b92ec2299ba2a122847c3af700507ded4d98 | Python | 23,497 | 615 | """L5 M2 pins: size encoding channel (``size_by`` + ``scale=``), D4 default-applied.
Covers the design-memo 3.1 test list plus the 2.2 "dims" typed-shape-path
pins, the 2.4(ii) funnel image-drop rule, the C2(b) width/height/fixedsize
writer discipline, and the 2.3b rolled-aggregate size verdicts (size REFUSES
where co... |
f360ccc099a965bf7fca5f1f8129355a75088365542b78d5e52f6d8e599e5357 | Python | 23,499 | 622 | """Hardening tests for loop/recurrence grouping (round-21).
Locks the fixes for the round-20 adversarial findings:
* Multi-output calls (LSTMCell h/c, fused RNN/GRU/LSTM output/state slots) must
produce one recurrent layer PER OUTPUT SLOT, never interleaved passes of one
layer (review F3, review's fused-module ge... |
7c8fd9c7a6b2f5bbba92c66e5de666fe5824f02b1abfc31c34733e06ca759c27 | Python | 23,502 | 620 | from datetime import datetime, timedelta, timezone
from unittest.mock import MagicMock, Mock, call, patch
import pytest
from google.cloud.exceptions import NotFound
from celery.backends.gcs import GCSBackend
from celery.exceptions import ImproperlyConfigured
class test_GCSBackend:
def setup_method(self):
... |
31f5c77e9914ec5b9aae32220a5c9ca865cd5e70c0f752e680d126d5c61e267a | Python | 23,511 | 609 | #!/usr/bin/env python3
"""
Build GTN Search Database from GTN Repository.
This script processes the Galaxy Training Network repository and creates
a SQLite database with FTS5 full-text search capabilities for fast tutorial search.
Usage:
python build_database.py <gtn_repo_path> [--output <db_path>]
"""
import js... |
f790b99eedded9e8388021c080e10572aa7bcecb465d884ee816dec1ab93a41d | Python | 23,516 | 389 | import os
import logging
import numpy as np
import tensorflow as tf
from tensorflow import keras
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import KFold
import matplotlib.pyplot as plt
from matplotlib import cm
import seaborn as sns
# %% Set training parameters
n_sessi... |
a21b73d577bb12d622206e011b4642072321214e35207639bb9719824065e0a4 | Python | 23,519 | 749 | import datetime
import os.path
import fnmatch
import math
from typing import Any, Iterable
from os.path import split
import numpy as np
import pydicom
from pydicom import FileDataset, Dataset, datadict, DataElement
from pydicom.multival import MultiValue
from pydicom.tag import Tag
def lookup_modality(modality: None... |
5571f2c456ac2800a792449e978b72040097561509826110eba32d32f3cd702c | Python | 23,532 | 658 | import os
import pytest
from tensorflow import data as tf_data
from keras.src import backend
from keras.src import layers
from keras.src import models
from keras.src import ops
from keras.src import testing
from keras.src.backend.common import standardize_dtype
from keras.src.layers.preprocessing import feature_space... |
2c2e806c6b1e7dea6b6097e4466fd010e460146acf7723c348cefed5d8b8be7e | Python | 23,556 | 652 | import datetime as dt
import os
import brainpy_datasets as bd
import numpy as np
import pandas as pd
__all__= [
'HarData',
'CheetahData',
'GestureData',
'OccupancyData',
'OzoneData',
'PersonData',
'PowerData',
'SMnistData',
'TrafficData',
]
def _cut_in_sequences(x, seq_len, inc=1, y=None, stack_ax... |
b20e6bd820803b87a9e67d8de52d11934ccb661a4c9977747bc7b0622bba8109 | Python | 23,582 | 674 | """
behav_plots.py
This script contains functions for plotting pupil and running analyses.
Authors: Colleen Gillon
Date: January, 2021
Note: this code uses python 3.7.
"""
import numpy as np
from matplotlib import pyplot as plt
from matplotlib import ticker, patches
import seaborn
from util import logger_util, pl... |
f0cd362ce7d8e1a9c510a5236bd22b62dbcfbfff597c26ad3cc966ea79bbd271 | Python | 23,586 | 468 | #import scipy
import numpy as np
import logging
from ridge_utils.utils import mult_diag, counter
import random
import itertools as itools
zs = lambda v: (v-v.mean(0))/v.std(0) ## z-score function
ridge_logger = logging.getLogger("ridge_corr")
def ridge(stim, resp, alpha, singcutoff=1e-10, normalpha=False, logger=rid... |
7c2f358035191b1ef8ee7b79e31463476c9f130e9cac8fca50f68815ef81b971 | Python | 23,588 | 619 | import copy
import numpy as np
import scipy.ndimage as ndi
import scipy.fft as fft
import pandas as pd
from copy import deepcopy
from scipy.special import factorial
def pool_voxel_grids(x1, x2, pooling_method):
if x1 is None:
return copy.deepcopy(x2)
elif pooling_method == "max":
# Perform... |
88afaaae7324d89b83a02daa0d7502ea190bbcc247fd4a88056b8731f1049c1d | Python | 23,597 | 540 | # -*- coding: utf-8 -*-
"""
@File : cci_two_cluster.py
@Time : 2022/07/03 11:50:40
@Author : LuluZuo
@Version : 1.0
@Desc : spatial cell cell communication
"""
import itertools
import random
from typing import Tuple
import numpy as np
import pandas as pd
from anndata import AnnData
from scipy.spar... |
0c6a5cd1d131900b877aae8337a1f0a52dc0de56b96593de55aeed5b1a65da6b | Python | 23,618 | 605 | #==============================================================================#
# Author: Dominik Müller #
# Copyright: 2024 IT-Infrastructure for Translational Medical Research, #
# University of Augsburg ... |
169ec82f55c563e12ecd64560c9f59d25c8fdef5e997248db084c0568aa6d2ea | Python | 23,619 | 650 | import torch as th
import torch.nn as nn
import numpy as np
import random
import torch.nn.functional as F
from torch.distributions import Normal
from torch_scatter import scatter_add
from sklearn import metrics
from sklearn.metrics import roc_auc_score, mean_squared_error, precision_recall_curve, auc
from scipy.stats i... |
b530425554f927671f02baae081298e5935babc0cf094d70ba7df9a3330e7897 | Python | 23,640 | 513 | #!/usr/bin/env python
"""
Importer for dataset published from Centre de Conférence Pierre Mendès-France
Ministère de l'Économie, des Finances et de la Relance
"""
import csv
import sys
import os
import progressbar
import subprocess
import zipfile
from glob import glob
from multiprocessing import Pool
import hashlib
i... |
ff4f5bb745b59524426516d05cb385b461c15a2fc2c0310d361a5d13d0fdb57d | Python | 23,653 | 686 | # This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains th... |
637c739a7c6a44b50bf4e5de0cef3a4ca6cbcf07f3a2bdb14c3074218f6b31e7 | Python | 23,656 | 686 | # This file helps to compute a version number in source trees obtained from
# git-archive tarball (such as those provided by githubs download-from-tag
# feature). Distribution tarballs (built by setup.py sdist) and build
# directories (produced by setup.py build) will contain a much shorter file
# that just contains th... |
b4cc1d282cc037ba811cabce472154a5fb02733fe138af977881fd96856f23bc | Python | 23,662 | 784 | """
Shared logic behind the environment builder.
Normalizes the builder's object rows against the stored environment payload,
so the canvas, the form and the saved configuration stay consistent.
"""
from __future__ import annotations
from dataclasses import dataclass
import copy
import re
from typing import Any
fro... |
ae793b145c67d571c0b2aa8149673d988d77f6a7173abd04c5a9c951cb8f116f | Python | 23,666 | 518 | # SPDX-License-Identifier: LGPL-2.1-or-later
#!/usr/bin/env python
#-*- coding: utf-8 -*-
import os
from collections import OrderedDict
import numpy as np
from .utils import general as utils
from .plotting_functions import single_in_cohort_soc_plot
from .plotting_functions import make_RasterPlot
from .write_to_file imp... |
e7ac321eef98c100a2cbbe84c6cc23bfeebcbf25a0987cb4fdef150b9a885357 | Python | 23,673 | 732 | import logging
from collections.abc import Callable
from typing import Any, Self, TypedDict
import numpy as np
import ome_zarr_models.v06.coordinate_transforms as ozmt
import pytest
import transformnd as tnd
import zarr
from ome_zarr_models.v06.coordinate_transforms import (
AnyTransform,
CoordinateSystem,
... |
b04ba6dd971d09721eb9efa00d151db1e2160efc1742c4c61609406d1fe7e577 | Python | 23,676 | 528 | import abc
import logging
import os
import shutil
import tempfile
from typing import (
NamedTuple,
)
from sqlalchemy.orm import Session
from sqlalchemy.orm.exc import DetachedInstanceError
from galaxy.datatypes.data import (
Data,
Directory,
)
from galaxy.datatypes.registry import Registry
from galaxy.dat... |
040e3c37dd9d160e94238d8f16a2c2520df1afdaeef9de79d40382893379d6be | Python | 23,681 | 527 | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import itertools
import json
from sklearn.metrics import classification_report
from role_prediction.graphormer.data import get_dataset
import torch
import math
import torch.nn as nn
import pytorch_lightning as pl
from role_prediction.graphormer... |
a683ed9737151f1649af70a7ccdde90c527ef60e2ab9238a846adee1f27ee326 | Python | 23,684 | 656 | """Adversarial regression tests for CLC tile scheduling.
These cases intentionally target scheduler-sensitive shapes: mismatched
sequence lengths, non-aligned tiles, GQA ratios, minimal problems, and
larger persistent workloads. This is deterministic adversarial coverage,
not randomized fuzzing.
"""
from contextlib i... |
e203579cf6c0fa472f21d353b62e386dcdd14bddfc499b010ac9e59e0173d67b | Python | 23,684 | 572 | from __future__ import annotations
from typing import NamedTuple, Optional, Sequence, Union
import bream4.legacy.device_interfaces.devices.promethion as legacy_promethion
from bream4.device_interfaces.devices.base_device import BaseDeviceInterface
Temperature = NamedTuple("Temperature", [("current_temp", float), ("d... |
8a81754204aa7823a14b4ef08a2e9f220938278f4bc230034f5cd3bedad99184 | Python | 23,691 | 504 | from typing import Callable, Dict, List, Optional, Tuple
import torch
from pytorch_lightning.utilities.exceptions import MisconfigurationException
from torch import Tensor, nn
from pl_bolts.utils import _TORCHVISION_AVAILABLE
from pl_bolts.utils.warnings import warn_missing_pkg
if _TORCHVISION_AVAILABLE:
from to... |
1561a6a8ca5f8ec63fd42dd7bebe2156b0be99487e0287f056f0d0708ac83611 | Python | 23,701 | 461 | """Single-shot Multi-box Detector."""
from __future__ import absolute_import
import os
import warnings
import mxnet as mx
from mxnet import autograd
from mxnet.gluon import nn
from mxnet.gluon import HybridBlock
from ...nn.feature import FeatureExpander
from .anchor import SSDAnchorGenerator
from ...nn.predictor impor... |
8510aa5de9eb62db602d41ae4ada2e965299697bfb6c292202115d9f3afe396e | Python | 23,702 | 579 | """Worker command-line program.
This module is the 'program-version' of :mod:`celery.worker`.
It does everything necessary to run that module
as an actual application, like installing signal handlers,
platform tweaks, and so on.
"""
import logging
import os
import platform as _platform
import sys
from datetime import... |
71c82ad620035f86daa97809b26de8fdcc44c8f8e0d02fc40cb034055c323f57 | Python | 23,706 | 548 | # adapted from https://github.com/facebookresearch/detectron2/blob/master/detectron2/data/datasets/coco.py
import contextlib
import copy
import datetime
import time
import io
import json
import logging
import os
from PIL import Image
import numpy as np
import portalocker
from ..detection.detection_utils import try_im... |
0867028f397389fc3fe4b9892b6bf77526aeb696c1e1c1889ec3d204afb34ae6 | Python | 23,711 | 535 | """Sparse-call argument decoding and binding."""
from __future__ import annotations
import math
from collections.abc import Callable, Mapping, Sequence, Set as AbstractSet
from typing import TYPE_CHECKING, Any, cast
import torch
from ._runnable_state import (
_OUTPUT_COUNT_FLOOR,
RunResourceCeiling,
_al... |
7a9e73c31cb8d96a3a54fc671f0fe1be9b696cdf079147c032eedefc71424fff | Python | 23,712 | 805 | #!/usr/bin/python3
# import modules
import argparse
import sys
import tempfile
version = "0.1.5"
###############
# sb43 modified to suit casm need and output additional columns : boiotype, gnene name and chromosome
# Hong-Dong Li, GTFtools: a Python package for analyzing various modes of gene models, bioRxiv, 263517... |
b32fd51187a61e428dc9ae149ca05d79900e3bd3fbbcf6df1c84a85fa6612b1b | Python | 23,712 | 543 | """
MXNet implementation of tracktor in SMOT: Single-Shot Multi Object Tracking
https://arxiv.org/abs/2010.16031
"""
# pylint: disable=line-too-long,logging-format-interpolation,unused-argument,missing-function-docstring
from __future__ import absolute_import
import logging
import time
import numpy as np
import mxnet ... |
6a18a511d7ffb2468ad4d703c3bf4cd1d91b770a7f827d93e0d9a6c25a8339d8 | Python | 23,725 | 591 | # Copyright (c) 2022 PaddlePaddle 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 app... |
0502b55ace73a14f2bb8f8536f5b71cad8224152d0b282c0930667e3d1d646cb | Python | 23,731 | 627 | import collections
import ctypes
import io
import math
import numpy as np
import os
import pyogg
import tempfile
import wave
from .helpers import LimitingPool
from collections import namedtuple
from .io import open_remote, remove_remote, copy_remote, is_remote_path
AudioFormat = namedtuple('AudioFormat', 'rate channe... |
8c35b7ecf9f9794293e09ce4aac27988a9f85054ead32ad4d6c76ed1983f95f0 | Python | 23,753 | 637 | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models.layers import trunc_normal_, DropPath
from timm.models.registry import register_model
from model import common
def make_model(args, parent=False):
return MogaNet(args)
def build_act_layer(act_type):
"""Build activ... |
7b335a3d1cf2dfc966da51d65d94d440711d2f2c82de8db7e57ab248d9cafad1 | Python | 23,767 | 826 | import numpy as np
from numba import jit # , njit, prange
################################
# Time only functions
################################
@jit(nopython=True, cache=True)
def jitrestrict(time_array, starts, ends):
n = len(time_array)
m = len(starts)
ix = np.zeros(n, dtype=np.int64)
if n == 0 ... |
186a963573429006223b800c6da9ec5154f123d4099cce5d2b15a48653e6f295 | Python | 23,778 | 597 | import copy
from keras.src import backend
from keras.src import ops
from keras.src import utils
from keras.src.api_export import keras_export
from keras.src.layers.layer import Layer
from keras.src.layers.rnn.gru import GRU
from keras.src.layers.rnn.lstm import LSTM
from keras.src.saving import serialization_lib
@ke... |
46fe5408b58ea2672662c4265c398ddda00056fa9883ca2bc2b3b29f7c7a22ee | Python | 23,781 | 679 | """Some basic example datasets for testing."""
from distutils.version import LooseVersion
from itertools import product
import os
from pathlib import Path
import shutil
import string
import mne
from mne import minimum_norm as mn
import numpy as np
from .. import _info, load
from .._data_obj import Dataset, Factor, Va... |
64f77ecc9715d68403804f2e23ff1fc8eb27549b31c9a96d0fff63cddce62c87 | Python | 23,782 | 458 | #!/usr/bin/env python
# coding: utf-8
# In[3]:
import tensorflow as tf
import tensorflow.keras as keras
from tensorflow.keras.layers import Reshape, Input, Flatten, concatenate, Dense, BatchNormalization ,Conv1D,Conv2D,Conv3D,MaxPool1D, MaxPool2D,MaxPool3D, GlobalMaxPool2D, Dropout
from tensorflow.keras.optimizers i... |
f902d3d32d6a2b863b5898ef4b92ef3946b5539c1912908a895dae53e2cbc28f | Python | 23,785 | 755 | import logging
import os
import sys
import numpy as np
import mne
sys.path.insert(0, '/mnt/homes/home024/abraun/pymeg')
sys.path.insert(0, "/mnt/homes/home024/abraun/conf_meg")
from optparse import OptionParser
from os import makedirs
from os.path import join
import pandas as pd
from joblib import Memory
from pyme... |
e3e6d67672672673b4c53c6a874f77d07bb84f438a916ecb582c177bb515bc81 | Python | 23,790 | 755 | """Tests for ``tl.debug.infer_input_shape``."""
from __future__ import annotations
import torch
import torch.nn.functional as F
from torch import nn
import torchlens as tl
class TinyMlp(nn.Module):
"""Simple MLP with a statically readable input width."""
def __init__(self) -> None:
"""Initialize l... |
e4e21394eb608858d246885b8001a42b249d49f9e5de992fa79e046dffff6534 | Python | 23,794 | 710 | """Callable identity for extraction resume (extract memo D8 + item 15).
The classifier digests everything a Python callable can OBSERVE — bytecode,
signature facts, default values BY VALUE, closure cells BY VALUE, and every
global name the bytecode actually loads — and refuses exactly where it is
blind. The classifica... |
eae7c17a4172b5c0f0731acedcbbaf91d7f14edc46d218719ed4d86f5646883a | Python | 23,808 | 559 | import logging
import os
import time
import traceback
from datetime import timedelta
from typing import TYPE_CHECKING
try:
import pbs
PBS_IMPORT_MESSAGE = None
except ImportError as exc:
pbs = None
PBS_IMPORT_MESSAGE = (
"The Python pbs-python package is required to use "
"this feature... |
1b7da400b07169fdada99b69e7da61a731c411e539b2140c27e517a33e79c5e2 | Python | 23,811 | 688 | import warnings
from keras.src import backend
from keras.src import layers
from keras.src.api_export import keras_export
from keras.src.applications import imagenet_utils
from keras.src.models import Functional
from keras.src.ops import operation_utils
from keras.src.utils import file_utils
BASE_WEIGHT_PATH = (
"... |
20540c1f3a098f69047b4218bf3c8fbd814d8a6f7ac6080d00042ba80b2300ff | Python | 23,845 | 634 | """Output-tree reconstruction honesty for the unified ``Trace.run`` surface.
Round-6 hardening. A run reporting ``VERIFIED`` MUST return the exact output
object -- correct container TYPE, all non-tensor literal leaves byte-exact, all
fields. A lossy or wrong output must be ``UNVERIFIABLE`` (or diverged), never a
silen... |
5b0caf4e1b5c985327263835bc85130bf4cb26b3379d18de45d6f7b3b6cb84b4 | Python | 23,854 | 608 | """Capture-OUTCOME corpus for detached torch references — the stage-2 deletion gate.
This module converts the detached-reference corpus from patch-MECHANICS
assertions ("the crawler rewrote slot X to wrapper Y") to capture-OUTCOME
assertions ("the op appears in the trace" / "the miss has exactly this
signature"). The ... |
4664451da073dd7502d997d56219cfcb5d63db39ca3607f797630c6f293ab9d5 | Python | 23,874 | 606 | import unittest
from unittest.mock import patch
from codecarbon.core.emissions import Emissions
from codecarbon.core.units import Energy
from codecarbon.external.geography import CloudMetadata, GeoMetadata
from codecarbon.input import DataSource
from tests.testutils import get_test_data_source
class TestEmissions(un... |
9716d26935187ec2227c5eb20c80dc8f5a030aff62ca1c0333fadcafe0f1363d | Python | 23,876 | 589 | """Consumer-ledger generation and closure gates (P0).
Regenerates the ledger from the tree and the scenario battery every run,
asserts the closure properties, and DIFFS the regenerated inventory against the
git-tracked artifacts next to this test, so P2 keeps a reviewable migration
checklist and producer/consumer drif... |
1a760bba2ff4ec0ef39182c8b4b4fda510131e67d65b93316387ff7b345c66c4 | Python | 23,888 | 616 | # Copyright (c) 2021 PaddlePaddle 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 app... |
f625f35a689cbd0397170466f1cdf057e758e224a66f68f28b819f183facfbd3 | Python | 23,914 | 553 | import pkg_resources
import nanite.model as nmodel
import numpy as np
from PyQt5 import uic, QtCore, QtWidgets
from .. import units
class TabFit(QtWidgets.QWidget):
def __init__(self, *args, **kwargs):
super(TabFit, self).__init__(*args, **kwargs)
path_ui = pkg_resources.resource_filename("pyjib... |
264d0d9abba7aaadd8da9765eae0dbe7535a988e752841c354c66aa6a477e685 | Python | 23,920 | 686 | """
Intermittency modules alternating between activity and pause.
Larval behaviour is organized into bouts: stretches of crawling or feeding
separated by pauses. These modules generate that alternation, either by
sampling the bout durations from fitted distributions or by running a
branching process, and gate the craw... |
7ef1151636093cd2074dccdc2e5160816373630d786ff79455d65841f5c82294 | Python | 23,921 | 591 | from keras.src import backend
from keras.src import constraints
from keras.src import initializers
from keras.src import ops
from keras.src import regularizers
from keras.src.api_export import keras_export
from keras.src.layers.input_spec import InputSpec
from keras.src.layers.layer import Layer
# TODO(abheesht17): M... |
7711993dff82b1dd60478cac81145d9d3c61e773e20a5d88417c255ef895a7c7 | Python | 23,922 | 719 | """
The dataset analysis app.
Lets the user pick stored datasets and render the plots that apply to them.
"""
from __future__ import annotations
from html import escape
from typing import Any
import pandas as pd
import panel as pn
from larvaworld.lib.reg.graph import GraphRegistry
from larvaworld.lib.process.datas... |
2898e7265e33ff418a1c73b1166c6b4619f421b4717c4442cd12730af77d393b | Python | 23,926 | 570 | """
Functions specific for LIFE data set.
"""
import os
import numpy as np
import mne
import pandas as pd
from tools_general import load_json
def read_erp(subj, dir_data, decim=1, notch=False, h_freq=45, baseline=(-.2, -.05)):
"""
Read the data from stimulus based recordings
Adapted from Denis Engemann <... |
36e858ca5249065e7dba11be128cb31588195b30e117b5d9007f0a51d29bb9ee | Python | 23,941 | 482 | #!/usr/bin/env python3
"""Журнал протокола B («Когда выгодно учиться»): статистика и HTML-секция.
Читает runs/daily/protocol_b.jsonl (суточный прогон runs/daily_b.py),
считает по всему накопленному то, что объявлено в PREREGISTRATION_B.md,
и отдаёт машинное состояние (docs/journal_b.json) плюс HTML-фрагмент,
который r... |
23c72f3d7e57dc063bbf6b7b24c25af78f24fde77df61e6cadfad25c397eeb0c | Python | 23,964 | 616 | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import logging
import math
import random
import numpy as np
import torch
import torchvision.io as io
from . import transform as transform
logger = logging.getLogger(__name__)
def temporal_sampling(frames, start_idx, end... |
29cd8e3d15eeaaef3ee5c9714aa0dd910c7b4ce81765e2922ed2b557ec0f4329 | Python | 23,965 | 592 | """
Validation functions for input preprocessing.
This module contains functions to validate different aspects of the input data
before it's processed by the preprocessing pipeline.
"""
from typing import List, Dict, Any, Tuple, Optional, Set
import logging
import os
import copy
import json
import re
import tempfile
... |
310d00679ef920dd6e0c82fe8f9dcf202a2c495979f2040b24297d2b41084d98 | Python | 23,966 | 808 | import builtins
import inspect
import io
import logging
import os
import platform
import sys
import threading
import types
import warnings
from contextlib import contextmanager
from functools import wraps
from importlib import import_module, reload
from unittest.mock import MagicMock, Mock, patch
import pytest
from ko... |
35a8d8af169aeed47bf8e5b8d7d9ec59ae1d54ba6d69e9c024af43599cfeec35 | Python | 23,972 | 605 | """Three-layer capture snapshots for the parity harness.
A snapshot canonicalizes one capture into JSON-able structures across the
three comparison layers the design-of-record names:
* ``journal`` — the op-event stream exactly as postprocess step 0 consumes it
(intercepted at ``materialize_from_events`` entry, the ... |
7272feffbe27321dd423a0184037c1bf48a1e6a4db7bd73563fc7ff565e90f1a | Python | 23,976 | 461 | ##########################################################################
## ##
## Copyright (c) 2019 Philipp Lösel. All rights reserved. ##
## ##
## This file is par... |
e7e6c96fe22534b0ba3aa570e34fc2f59b8c54ddbb19ffffb6d0afc41782b531 | Python | 23,977 | 385 | from __future__ import print_function
import sys
import logging
from random import seed, sample
from statistics import mean, stdev
import numpy as np
from scipy.cluster.hierarchy import linkage, fcluster
from edlib import align
from pysam import FastaFile
from svim.SVSignature import SignatureClusterUniLocal, Signat... |
031e7b188938ffdf045fd038986c1b3185f8782de28f1ba9a2725f2e13bbe01c | Python | 23,987 | 742 | """
Screen renderable items for pygame-based simulation visualization
"""
from __future__ import annotations
from typing import Any
import os
import param
from ..param import (
Area2DPixel,
IntegerTuple,
NestedConf,
NumericTuple2DRobust,
Pos2D,
PositiveInteger,
PositiveNumber,
PosPix... |
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