repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
MFTreeSearchCV | MFTreeSearchCV-master/utils/unittest_optimisers.py | """
Unit tests for optimers.
-- [email protected]
"""
# pylint: disable=import-error
# pylint: disable=no-member
# pylint: disable=invalid-name
# pylint: disable=relative-import
# pylint: disable=abstract-class-not-used
import os
from argparse import Namespace
import numpy as np
import time
# Local
from base_t... | 5,155 | 36.911765 | 87 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/ancillary_utils.py | """
A collection of utilities for ancillary purposes.
-- [email protected]
"""
# pylint: disable=import-error
# pylint: disable=no-member
# pylint: disable=invalid-name
# pylint: disable=relative-import
import numpy as np
# Print lists as strings
def get_rounded_list(float_list, round_to_decimals=3):
""" R... | 1,795 | 27.507937 | 73 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/experimenters.py | """
Harness to run experiments and save results.
-- [email protected]
"""
# pylint: disable=import-error
# pylint: disable=no-member
# pylint: disable=relative-import
# pylint: disable=abstract-class-not-used
from argparse import Namespace
import random
from time import time
import numpy as np
from scipy.io im... | 3,830 | 34.472222 | 89 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/reporters.py | """
Monitors are used to monitor the progress of any algorithm. Here we implement
the most basic monitor which will be inherited by monitors for specific processes.
-- [email protected]
"""
import sys
def get_reporter(reporter):
""" Returns a reporter based on what was passed as argument. If reporter is al... | 1,537 | 29.156863 | 87 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/base_test_class.py | """
Implements a base class for unit tests with some common utilities.
"""
import numpy as np
import random
import sys
from time import time
import unittest
class BaseTestClass(unittest.TestCase):
""" An abstract base class for unit tests. """
def __init__(self, *args, **kwargs):
""" Constructor. """
... | 1,298 | 24.98 | 74 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/general_utils.py | """
A collection of very generic python utilities.
-- [email protected]
"""
# pylint: disable=import-error
# pylint: disable=no-member
# pylint: disable=invalid-name
# pylint: disable=relative-import
import numpy as np
def compare_dict(dict_1, dict_2):
""" Compares two dictionaries. """
# N.B: Taken from... | 3,506 | 33.048544 | 90 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/__init__.py | """
Some general utility functions we will need.
-- [email protected]
"""
| 81 | 15.4 | 46 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/optimisers.py | """
A collection of wrappers for optimisng a function.
-- [email protected]
"""
# pylint: disable=import-error
# pylint: disable=no-member
# pylint: disable=invalid-name
# pylint: disable=relative-import
# pylint: disable=superfluous-parens
from argparse import Namespace
from datetime import datetime
import os... | 6,624 | 37.517442 | 90 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/unittest_general_utils.py | """
Test cases for functions in general_utils.py
-- [email protected]
"""
# pylint: disable=import-error
# pylint: disable=no-member
# pylint: disable=invalid-name
# pylint: disable=relative-import
import numpy as np
import general_utils
from base_test_class import BaseTestClass, execute_tests
class GeneralU... | 3,943 | 34.854545 | 83 | py |
MFTreeSearchCV | MFTreeSearchCV-master/utils/direct_fortran/__init__.py | 0 | 0 | 0 | py | |
MFTreeSearchCV | MFTreeSearchCV-master/utils/direct_fortran/simple_direct_test.py |
import numpy as np
import direct
def main():
""" Main function. """
obj = lambda x: (np.dot(x-0.1,x), 0)
lower_bounds = [-1] * 4
upper_bounds = [1] * 4;
dim = len(lower_bounds)
eps = 1e-5
max_func_evals = 1000
max_iterations = max_func_evals
algmethod = 0
# _log_file = 'dir_file_name'
_log_file ... | 1,367 | 22.586207 | 74 | py |
Tamanduatei_Vulnerability | Tamanduatei_Vulnerability-main/vulnerability.py | import igraph as ig
import numpy as np
import time
import multiprocessing as mp
f2 = open("screen.out", 'w')
f = open("result.dat", "w")
# Calculating the efficiency of a given network
def eff_global(g, weights):
N = g.vcount()
eff = 0.0
sp = g.shortest_paths(weights=weights)
for l i... | 2,290 | 27.283951 | 108 | py |
uMatrix | uMatrix-master/tools/make-firefox-meta.py | #!/usr/bin/env python3
import os
import json
import re
import sys
if len(sys.argv) == 1 or not sys.argv[1]:
raise SystemExit('Build dir missing.')
proj_dir = os.path.join(os.path.split(os.path.abspath(__file__))[0], '..')
build_dir = os.path.abspath(sys.argv[1])
version = ''
with open(os.path.join(proj_dir, 'di... | 1,077 | 29.8 | 84 | py |
uMatrix | uMatrix-master/tools/make-opera-meta.py | #!/usr/bin/env python3
import os
import json
import re
import sys
if len(sys.argv) == 1 or not sys.argv[1]:
raise SystemExit('Build dir missing.')
proj_dir = os.path.join(os.path.split(os.path.abspath(__file__))[0], '..')
build_dir = os.path.abspath(sys.argv[1])
version = ''
with open(os.path.join(proj_dir, 'di... | 1,623 | 29.641509 | 90 | py |
uMatrix | uMatrix-master/tools/make-chromium-meta.py | #!/usr/bin/env python3
import os
import json
import re
import sys
if len(sys.argv) == 1 or not sys.argv[1]:
raise SystemExit('Build dir missing.')
proj_dir = os.path.join(os.path.split(os.path.abspath(__file__))[0], '..')
build_dir = os.path.abspath(sys.argv[1])
version = ''
with open(os.path.join(proj_dir, 'di... | 1,140 | 27.525 | 80 | py |
uMatrix | uMatrix-master/dist/chromium/publish-beta.py | #!/usr/bin/env python3
import datetime
import json
import jwt
import os
import re
import requests
import shutil
import subprocess
import sys
import tempfile
import time
import zipfile
from distutils.version import StrictVersion
from string import Template
# - Download target (raw) uMatrix.chromium.zip from GitHub
# ... | 6,489 | 32.626943 | 118 | py |
uMatrix | uMatrix-master/dist/firefox/publish-signed-beta.py | #!/usr/bin/env python3
import datetime
import json
import jwt
import os
import re
import requests
import shutil
import subprocess
import sys
import tempfile
import time
import zipfile
from distutils.version import LooseVersion
from string import Template
# - Download target (raw) uMatrix.firefox.xpi from GitHub
# ... | 12,565 | 38.024845 | 189 | py |
oscimpDigital | oscimpDigital-master/doc/tutorials/plutosdr/2-PRN_on_PL/project_gps/app/top_block.py | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
##################################################
# GNU Radio Python Flow Graph
# Title: Top Block
# GNU Radio version: 3.7.13.5
##################################################
from distutils.version import StrictVersion
if __name__ == '__main__':
import ctypes
... | 12,615 | 42.805556 | 163 | py |
oscimpDigital | oscimpDigital-master/doc/tutorials/plutosdr/99-gnuradio-audio/top_block.py | #!/usr/bin/env python2
# -*- coding: utf-8 -*-
##################################################
# GNU Radio Python Flow Graph
# Title: Top Block
# Generated: Tue Feb 26 16:54:22 2019
##################################################
from gnuradio import analog
from gnuradio import audio
from gnuradio import eng_no... | 2,691 | 31.433735 | 148 | py |
lydia | lydia-main/scripts/run-clang-format.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# This file is part of Lydia.
#
# Lydia is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later ... | 12,277 | 29.926952 | 87 | py |
lydia | lydia-main/scripts/check_copyright_notice.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# This file is part of Lydia.
#
# Lydia is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later ... | 4,260 | 36.052174 | 86 | py |
sciann-applications | sciann-applications-master/SciANN-LaplaceEq-Forward/sciann_datagenerator.py | # ==============================================================================
# Copyright 2021 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# A guide for generating collocation points for PINN solvers.
#
# Includes:
# - DataGeneratorX:
# Generate 1D collo... | 20,752 | 31.477308 | 98 | py |
sciann-applications | sciann-applications-master/SciANN-SolidMechanics/SciANN-SolidMechanics.py | """ SciANN-SolidMechanics.py
Description:
SciANN code for solution and discovery of solid mechanics from data.
For additional details, please check our paper at: https://arxiv.org/abs/2003.02751
Created by Ehsan Haghighat on 2/14/20.
"""
import os, sys, time
import numpy as np
from sciann.utils.math impo... | 13,624 | 39.19174 | 157 | py |
sciann-applications | sciann-applications-master/SciANN-ElastoPlasticity/plotting.py | """
Description:
Plotting for von-Mises elasto-plasticity problem:
https://arxiv.org/abs/2003.02751
Created by Ehsan Haghighat on 6/10/20.
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm, Normalize
import matplotlib.ticker as ticker
import matplotlib.ticke... | 1,102 | 29.638889 | 72 | py |
sciann-applications | sciann-applications-master/SciANN-ElastoPlasticity/utility_functions.py | """
Description:
Utility functions for data preparation.
Created by Ehsan Haghighat on 6/10/20.
"""
import os, time
import sys
import numpy as np
import pandas as pd
from scipy.interpolate import griddata
RADI = 50.0
def eval_mu_sig(X):
return X.mean(), X.std()
def std(X, mu, sig):
return (X-m... | 3,014 | 27.714286 | 114 | py |
sciann-applications | sciann-applications-master/SciANN-Elasticity/sciann_datagenerator.py | # ==============================================================================
# Copyright 2021 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# A guide for generating collocation points for PINN solvers.
#
# Includes:
# - DataGeneratorX:
# Generate 1D collo... | 20,752 | 31.477308 | 98 | py |
sciann-applications | sciann-applications-master/SciANN-DataGenerator/sciann-datagenerator.py | # ==============================================================================
# Copyright 2021 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# A guide for generating collocation points for PINN solvers.
#
# Includes:
# - DataGeneratorX:
# Generate 1D collo... | 20,752 | 31.477308 | 98 | py |
sciann-applications | sciann-applications-master/SciANN-ConstitutiveModeling/vonMises_isotropic_stochastic.py | # Copyright 2022 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# vonMises_isotropic_stochastic.py
#
# Using transfer learning to perform material characterization
#
# Requirements:
# - data/vonMisesGeneral-random.csv
# - transfer_learning_weights/vonMises_isotropic_stochast... | 10,430 | 26.377953 | 96 | py |
sciann-applications | sciann-applications-master/SciANN-ConstitutiveModeling/Tensor.py | # Copyright 2022 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# Tensor class:
# Abstract 3x3 tensorial operations, on vectorized data (batch),
# with elasto-plasticity applications in mind.
#
import numpy as np
import sciann as sn
class BaseTensor:
""" BaseTenso... | 3,280 | 22.775362 | 113 | py |
sciann-applications | sciann-applications-master/SciANN-ConstitutiveModeling/vonMises_isotropic_dimensionless.py | # Copyright 2022 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# vonMises_isotropic_dimensionless.py
#
# Main code characterizing vonMises model with isotropic hardening
#
# Requirements:
# - data/vonMises.csv
#
import numpy as np
import matplotlib.pyplot as plt
from ... | 10,131 | 26.911846 | 114 | py |
sciann-applications | sciann-applications-master/SciANN-ConstitutiveModeling/druckerPrager_dimensionless-biaxial.py | # Copyright 2022 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# druckerPrager_dimensionless-biaxial.py
#
# Main code for characterizing Drucker-Prager model for biaxial loading
#
# Requirements:
# - data/druckerPrager-biaxial.csv
#
import numpy as np
import matplotlib... | 10,077 | 25.803191 | 114 | py |
sciann-applications | sciann-applications-master/SciANN-ConstitutiveModeling/druckerPrager_dimensionless-biaxial-undrained.py | # Copyright 2022 SciANN -- Ehsan Haghighat.
# All Rights Reserved.
#
# Licensed under the MIT License.
#
# druckerPrager_dimensionless-biaxial-undrained.py
#
# Main code for characterizing Drucker-Prager model for undrained biaxial loading
#
# Requirements:
# - data/druckerPrager-biaxial-undrained.csv
#
import... | 10,126 | 25.862069 | 114 | py |
sciann-applications | sciann-applications-master/SciANN-SolidMechanics-BCs/SciANN-SolidMechanics-BCs.py | """ SciANN-SolidMechanics.py
Description:
SciANN code for solution and discovery of solid mechanics from data.
For additional details, please check our paper at: https://arxiv.org/abs/2003.02751
Created by Ehsan Haghighat on 2/14/20.
"""
import os, sys, time
import numpy as np
from sciann.utils.math impo... | 14,462 | 40.088068 | 157 | py |
sciann-applications | sciann-applications-master/SciANN-Vibrations/PlateVibration/membrane.py | import numpy as np
import matplotlib.pyplot as plt
import sciann as sn
from sciann.utils.math import diff, sign, sin
from gen_dataset import gen_grid
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
Lx =... | 2,735 | 27.206186 | 115 | py |
sciann-applications | sciann-applications-master/SciANN-Vibrations/PlateVibration/membrane_inv.py | import numpy as np
import matplotlib.pyplot as plt
import sciann as sn
from sciann.utils.math import diff, sign, sin
from gen_dataset import gen_grid
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from m... | 3,060 | 25.617391 | 118 | py |
sciann-applications | sciann-applications-master/SciANN-Vibrations/PlateVibration/plate.py | import numpy as np
import sciann as sn
from sciann.utils.math import diff, sign, sin
from gen_dataset import gen_grid
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, Form... | 2,749 | 24.462963 | 124 | py |
sciann-applications | sciann-applications-master/SciANN-Vibrations/PlateVibration/gen_dataset.py | import numpy as np
def gen_grid(nx=5, ny=5, nt=10, Lx=1.0, Ly=1.0, T=1.0):
# domain grids
x_grid, y_grid, t_grid = np.meshgrid(
np.linspace(0, Lx, nx)[1:-1],
np.linspace(0, Ly, ny)[1:-1],
np.linspace(0, T, nt)[1:],
indexing='ij'
)
x_grid, y_grid, t_grid = [x.reshape(... | 2,634 | 27.641304 | 114 | py |
vampire | vampire-master/scripts/stat_plotter.py | #!/usr/bin/python
#
# see https://docs.google.com/document/pub?id=1vsmC80shh7qCpwgaNTrLzRyz61I0BZWJFvIqiE9yIG8
# for documentation
#
import sys
import platform
import subprocess
import re
import time
import tempfile
import os
import math
timeDataRE = re.compile("^(.* t[0-9]+) at ([0-9]+): (.*)$")
labelRE = re.compil... | 9,326 | 24.414169 | 115 | py |
vampire | vampire-master/scripts/determinism_checker.py | #!/usr/bin/python
"""
Will run two vampires in parallel and compare their output.
Attempts to change the memory alignment of the second vampire by
creating a lot of environment variables (this should make stack
start from a different place in memory).
Command line:
[-p] [-a alternative_executable] executable arg1 ...... | 4,220 | 25.71519 | 90 | py |
vampire | vampire-master/scripts/infXpostFx.py | #!/usr/bin/python
postfix = []
temp = []
operator = -10
operand = -20
leftparentheses = -30
rightparentheses = -40
space = -50
#convert a string into usable tokens
def strToTokens(str):
strArr = []
strArr = str
tempStr = ''
tokens = []
tokens_index = 0
count = 0
for x in strArr:
co... | 5,395 | 30.190751 | 101 | py |
vampire | vampire-master/scripts/proof_checker.py | #!/usr/bin/env python
# @Author Giles
import os
import sys
import subprocess
if(len(sys.argv)<2):
print "You should provide a command to proof_check i.e. ../vampire_rel_master -sa inst_gen TPTP/Problems/SYN/SYN001+1.p"
sys.exit(0)
TPTP='~/TPTP-v6.4.0/'
VAMPIRE_ROOT = sys.argv[1]+' --include '+TPTP
VAMPIRE_CHEC... | 3,382 | 29.754545 | 270 | py |
vampire | vampire-master/scripts/annotateCode.py | #!/usr/bin/env python
import sys, os, time, getopt
from subprocess import Popen, list2cmdline
import subprocess
import argparse
import insertInv
import tempfile
def cpu_count():
if sys.platform =="win32":
try:
num = int(os.environ['NUMBER_OF_PROCESORS'])
except(ValueError, KeyError):... | 13,937 | 36.069149 | 149 | py |
vampire | vampire-master/scripts/insertInv.py | #!/usr/bin/python
import os
import sys
import re
import string
import infXpostFx
def split_line(line):
# return a tuple (loop invariant) , (![...] and the rest)
s= line.split(",",1)
s1 = s[1]... | 6,403 | 45.405797 | 174 | py |
vampire | vampire-master/scripts/history_search.py | #!/opt/local/bin/python3.2
#!/usr/bin/python
"""
Will find a svn revision that is the last to give a specified output
Command line:
[-f first_revision] [-l last_revision] [-d regex] executable arg1 ...
default first_revision is 1500
default last_revision is the current one
default regex is "Refutation found."
Looks ... | 4,426 | 23.731844 | 78 | py |
vampire | vampire-master/scripts/generate_proof_checking_problems.py | import random
import os
import subprocess
N=1000
VAMPIRE='../vampire_rel_master'
TPTP='~/TPTP/TPTP-v6.1.0/'
read_from='all_relevant_problems'
directory='generated_proof_obligations'
if not os.path.exists(directory):
os.makedirs(directory)
#randomly generate N problems for proof checking
all_problems=set()
with o... | 1,714 | 24.220588 | 137 | py |
vampire | vampire-master/scripts/papers/compare_preproc_analyzer.py | #!/usr/bin/python
import fileinput
import os
strategyCnt = None
benchs = []
intInfty = 10000000000000000
def readInpVal(v):
if v=="TO":
return intInfty
else:
return int(v)
class Rec:
idx = 0
def __init__(self, idx, vals):
... | 4,832 | 31.655405 | 94 | py |
vampire | vampire-master/scripts/papers/get_cpa_interpolant_results.py | #!/usr/bin/python
import fileinput
import os
import re
printLatex = os.getenv("PRINT_LATEX", "ON")=="ON"
#if variable is set, benchmark names will be restricted only to those appearing in the specified file
restrFName = os.getenv("RESTRICTING_FILE", "")
reIgnoredLine = re.compile("(%)|(sh: line 1: .* Alarm clock)... | 19,577 | 35.390335 | 145 | py |
vampire | vampire-master/scripts/papers/z3_interpolant_stat_analyzer.py | #!/usr/bin/python
import fileinput
import os
import re
reYicesGarbaggeLine = re.compile("sh: line 1: .* Alarm clock");
benchSep = re.compile("============#$")
colorSep = re.compile("------#$")
reName = re.compile("F: (.*)$")
reRedStart = re.compile("Rq:$")
reBlueStart = re.compile("Bq:$")
reDerLocal = re.compile(... | 17,818 | 38.774554 | 117 | py |
openslide | openslide-main/scripts/dist.py | #!/usr/bin/python3
import os
from pathlib import Path
import shutil
import subprocess
base = Path(os.getenv('MESON_DIST_ROOT'))
subprocess.run(['meson', 'compile', 'doc/html'], check=True)
shutil.copytree('doc/html', base / 'doc/html', symlinks=True)
| 254 | 20.25 | 61 | py |
neuralqa | neuralqa-master/setup.py | import os
from importlib.machinery import SourceFileLoader
from setuptools import setup, find_packages
version = SourceFileLoader('neuralqa.version', os.path.join(
'neuralqa', 'version.py')).load_module().VERSION
def package_files(directory):
paths = []
for (path, _, filenames) in os.walk(directory):
... | 1,762 | 27.435484 | 83 | py |
neuralqa | neuralqa-master/neuralqa/cli.py | import click
from neuralqa.server import launch_server
from neuralqa.utils import cli_args
from neuralqa.utils import import_sample_data, ConfigParser
import os
from neuralqa.retriever import RetrieverPool
import logging
@click.group()
@click.version_option()
def cli():
pass
# @cli.command()
# @cli_args.HOST
# ... | 1,233 | 22.283019 | 75 | py |
neuralqa | neuralqa-master/neuralqa/version.py |
VERSION = "0.0.31-alpha"
| 26 | 8 | 24 | py |
neuralqa | neuralqa-master/neuralqa/__init__.py | import logging
from neuralqa.version import VERSION as __version__
from neuralqa.reader import BERTReader
from neuralqa.utils import import_sample_data
logging.getLogger("transformers").setLevel(logging.ERROR)
logging.getLogger("tensorflow").setLevel(logging.ERROR)
logging.getLogger("elasticsearch").setLevel(logging.... | 378 | 30.583333 | 61 | py |
neuralqa | neuralqa-master/neuralqa/expander/mlmexpander.py | from neuralqa.expander import Expander
import logging
from transformers import AutoTokenizer, TFBertForMaskedLM
import tensorflow as tf
import time
import spacy
logger = logging.getLogger(__name__)
class MLMExpander(Expander):
def __init__(self, index_type="mlm", model_path="bert-base-uncased", **kwargs):
... | 4,286 | 41.87 | 217 | py |
neuralqa | neuralqa-master/neuralqa/expander/expander.py |
class Expander:
def __init__(self, expander_type, **kwargs):
self.expander_type = expander_type
| 109 | 21 | 48 | py |
neuralqa | neuralqa-master/neuralqa/expander/__init__.py | from .expander import *
from .mlmexpander import *
from .expanderpool import *
| 79 | 19 | 27 | py |
neuralqa | neuralqa-master/neuralqa/expander/expanderpool.py |
from neuralqa.expander import MLMExpander
import logging
logger = logging.getLogger(__name__)
class ExpanderPool():
def __init__(self, expanders):
self._selected_expander = expanders["selected"]
self.expander_pool = {}
for expander in expanders["options"]:
if (expander["type"... | 1,398 | 34.871795 | 182 | py |
neuralqa | neuralqa-master/neuralqa/reader/reader.py |
import tensorflow as tf
import numpy as np
from transformers import AutoTokenizer, TFAutoModelForQuestionAnswering
import time
import logging
logger = logging.getLogger(__name__)
class Reader:
def __init__(self, model_name, model_path, model_type, **kwargs):
self.load_model(model_name, model_path, mod... | 758 | 28.192308 | 71 | py |
neuralqa | neuralqa-master/neuralqa/reader/bertreader.py | from neuralqa.reader import Reader
import tensorflow as tf
import numpy as np
import time
import logging
logger = logging.getLogger(__name__)
class BERTReader(Reader):
def __init__(self, model_name, model_path, model_type="bert", **kwargs):
Reader.__init__(self, model_name, model_path, model_type)
... | 10,473 | 42.641667 | 187 | py |
neuralqa | neuralqa-master/neuralqa/reader/readerpool.py |
from neuralqa.reader import BERTReader
import logging
logger = logging.getLogger(__name__)
class ReaderPool():
def __init__(self, models):
self._selected_model = models["selected"]
self.reader_pool = {}
for model in models["options"]:
if (model["type"] == "bert" or model["typ... | 1,331 | 32.3 | 167 | py |
neuralqa | neuralqa-master/neuralqa/reader/__init__.py | from .reader import *
from .bertreader import *
from .readerpool import *
| 74 | 17.75 | 25 | py |
neuralqa | neuralqa-master/neuralqa/utils/config_utils.py | import yaml
import os
import logging
import shutil
logger = logging.getLogger(__name__)
class ConfigParser:
def __init__(self, config_path):
module_file_path = os.path.dirname(os.path.abspath(__file__))
self.default_config_path = os.path.join(
module_file_path, "../config_default.ya... | 2,359 | 34.757576 | 85 | py |
neuralqa | neuralqa-master/neuralqa/utils/data_utils.py | from elasticsearch import Elasticsearch
import os
import zipfile
import shutil
import urllib.request
import logging
import lzma
import json
import tarfile
import hashlib
logger = logging.getLogger(__name__)
# index settings with analyzer to automatically remove stop words
index_settings = {
"settings": {
... | 6,518 | 32.260204 | 94 | py |
neuralqa | neuralqa-master/neuralqa/utils/file_utils.py | 0 | 0 | 0 | py | |
neuralqa | neuralqa-master/neuralqa/utils/__init__.py | from .config_utils import ConfigParser
from .file_utils import *
from .data_utils import import_sample_data, parse_field_content
| 129 | 31.5 | 63 | py |
neuralqa | neuralqa-master/neuralqa/utils/cli_args.py | """
Definitions of click options shared by several CLI commands.
"""
import click
HOST = click.option("--host", "-h", default="127.0.0.1",
help="The network address to listen on (default: 127.0.0.1). "
"Use 0.0.0.0 to bind to all addresses if you want to access the trackin... | 1,118 | 43.76 | 140 | py |
neuralqa | neuralqa-master/neuralqa/retriever/solrretriever.py | from neuralqa.retriever import Retriever
from neuralqa.utils import parse_field_content
import requests
import logging
logger = logging.getLogger(__name__)
class SolrRetriever(Retriever):
def __init__(self, index_type="solr", host="localhost", port=8983, protocol="http", ** kwargs):
Retriever.__init__(s... | 2,910 | 36.320513 | 138 | py |
neuralqa | neuralqa-master/neuralqa/retriever/elasticsearchretriever.py | from neuralqa.retriever import Retriever
from neuralqa.utils import parse_field_content
from elasticsearch import Elasticsearch, ConnectionError, NotFoundError
import logging
logger = logging.getLogger(__name__)
class ElasticSearchRetriever(Retriever):
def __init__(self, index_type="elasticsearch", host="localh... | 3,559 | 34.959596 | 138 | py |
neuralqa | neuralqa-master/neuralqa/retriever/retriever.py |
class Retriever:
def __init__(self, index_type):
self.index_type = index_type
| 92 | 14.5 | 36 | py |
neuralqa | neuralqa-master/neuralqa/retriever/__init__.py | from .retriever import *
from .elasticsearchretriever import *
from .solrretriever import *
from .retrieverpool import *
| 121 | 23.4 | 37 | py |
neuralqa | neuralqa-master/neuralqa/retriever/retrieverpool.py |
from neuralqa.retriever import ElasticSearchRetriever
import logging
logger = logging.getLogger(__name__)
class RetrieverPool():
def __init__(self, retrievers):
self.retriever_pool = {}
for retriever in retrievers["options"]:
if (retriever["value"] in self.retriever_pool):
... | 1,751 | 37.086957 | 189 | py |
neuralqa | neuralqa-master/neuralqa/server/serve.py |
from neuralqa.reader import BERTReader, ReaderPool
from neuralqa.server.routehandlers import Handler
from neuralqa.retriever import ElasticSearchRetriever, RetrieverPool
from neuralqa.utils import ConfigParser
from neuralqa.expander import ExpanderPool
import os
import logging
import time
import uvicorn
from fastapi... | 2,057 | 28.4 | 80 | py |
neuralqa | neuralqa-master/neuralqa/server/routemodels.py |
from pydantic import BaseModel
from typing import Optional
class Document(BaseModel):
max_documents: Optional[int] = 5
query: str = "what is a fourth amendment right violation?"
fragment_size: int = 250
retriever: Optional[str] = None
relsnip: Optional[bool] = True
class Answer(BaseModel):
... | 1,108 | 28.184211 | 127 | py |
neuralqa | neuralqa-master/neuralqa/server/server_app.py |
import uvicorn
import os
def launch_server(host="127.0.0.1", port=5000, workers=1, reload=False):
uvicorn.run("neuralqa.server.serve:app", host=host, port=port, workers=workers,
log_level="info", reload=reload)
if __name__ == "__main__":
launch_server()
| 283 | 20.846154 | 83 | py |
neuralqa | neuralqa-master/neuralqa/server/__init__.py | from .server_app import launch_server
| 38 | 18.5 | 37 | py |
neuralqa | neuralqa-master/neuralqa/server/routehandlers.py |
from neuralqa.utils import ConfigParser
import time
from fastapi import APIRouter
from typing import Optional
from neuralqa.server.routemodels import Document, Answer, Explanation, Expansion
import logging
logger = logging.getLogger(__name__)
class Handler:
def __init__(self, reader_pool, retriever_pool, expan... | 5,890 | 40.485915 | 176 | py |
neuralqa | neuralqa-master/tests/expander/test_expander.py | from neuralqa.expander import MLMExpander
def test_mlm_expander():
expander_kwargs = {
# "model_path": "distilbert-base-uncased"
}
test_string = "Steve jobs created the apple computer in which year"
expander = MLMExpander(**expander_kwargs)
expansion = expander.expand_query(test_string)
... | 400 | 24.0625 | 71 | py |
neuralqa | neuralqa-master/tests/reader/test_reader.py | 0 | 0 | 0 | py | |
neuralqa | neuralqa-master/tests/retriever/test_retriever.py | from neuralqa.retriever import ElasticSearchRetriever
from neuralqa.utils import ConfigParser
def test_elasticserch_retriever():
app_config = ConfigParser("config.yaml")
rkwargs = app_config.config["retriever"]["options"][1]["connection"]
retriever = ElasticSearchRetriever(**rkwargs)
results = retriev... | 452 | 29.2 | 72 | py |
neuralqa | neuralqa-master/docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 1,992 | 33.362069 | 79 | py |
LRMI | LRMI-main/feature/svm.py | import numpy as np
from sklearn.model_selection import KFold
from sklearn.preprocessing import StandardScaler
from sklearn.svm import SVC
# data = np.loadtxt('dataset/waveform/waveform-+noise.data', dtype=np.float64, delimiter=',')
# features = [
# [6, 10, 15, 9, 12, 11, 30, 37, 23, 29, ], # MRMI
# [6, 10, 15, 9, 5,... | 3,828 | 31.176471 | 93 | py |
LRMI | LRMI-main/feature/knn.py | import numpy as np
from sklearn.model_selection import train_test_split, KFold
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import classification_report, confusion_matrix, mutual_info_score
from sklearn.feature_selection import mutual_info_clas... | 4,257 | 33.33871 | 86 | py |
BeatTheBookie | BeatTheBookie-master/src/Figure2A.py | import numpy as np
import pandas as pd
import matplotlib as mpl
from scipy.stats import norm
import random
import bisect
bet = 50 # money on each bet
marg = 0.05 # margin odds above the mean.
n_samples = 10 # number of returns to calculate (with replacement) for the random strategy
#rand('seed',1) # use always the sa... | 8,610 | 44.803191 | 150 | py |
BeatTheBookie | BeatTheBookie-master/src/collect.py | import os, fnmatch
from itertools import cycle
dest = open('odds_series.csv','w') # replace by 'odds_series_b.csv' for b dataset
flatten = lambda l: [item for sublist in l for item in sublist]
header_cols = ['match_id','match_date','match_time','score_home','score_away'] \
+ flatten([[''.join(map(str,t)) for t in zi... | 1,542 | 31.829787 | 181 | py |
BeatTheBookie | BeatTheBookie-master/src/unpack.py | import os
source = open('../data/odds_series.csv','r') # replace path for '../data/odds_series_b.csv' for the other dataset
path = "../data/odds_series/" # replace path for "../data/odds_series_b/" for the other dataset
header = True
for line in source.readlines():
if header:
header = False
continue... | 727 | 41.823529 | 149 | py |
BeatTheBookie | BeatTheBookie-master/src/Figure1.py | import numpy as np
import pandas as pd
import matplotlib as mpl
dir_path = '../data/'
data = pd.read_csv(dir_path + "closing_odds.csv")
#data = np.genfromtxt(dir_path + "closing_odds.csv", delimiter=',')
# Fields:
# 1. match_table_id: unique identifier of the game
# 2. league of the game
# 3. match date
# 4. home tea... | 4,908 | 36.473282 | 100 | py |
DeepAligned-Clustering | DeepAligned-Clustering-main/pretrain.py | from util import *
from model import *
from dataloader import *
class PretrainModelManager:
def __init__(self, args, data):
set_seed(args.seed)
self.model = BertForModel.from_pretrained(args.bert_model, cache_dir = "", num_labels = data.n_known_cls)
if args.freeze_bert_parameters:
... | 4,907 | 40.59322 | 129 | py |
DeepAligned-Clustering | DeepAligned-Clustering-main/DeepAligned.py | from model import *
from init_parameter import *
from dataloader import *
from pretrain import *
from util import *
class ModelManager:
def __init__(self, args, data, pretrained_model=None):
if pretrained_model is None:
pretrained_model = BertForModel.from_pretrained(args.bert_mod... | 10,443 | 36.3 | 136 | py |
DeepAligned-Clustering | DeepAligned-Clustering-main/dataloader.py | from util import *
def set_seed(seed):
random.seed(seed)
np.random.seed(seed)
torch.manual_seed(seed)
class Data:
def __init__(self, args):
set_seed(args.seed)
max_seq_lengths = {'clinc':30, 'stackoverflow':45,'banking':55}
args.max_seq_length = max_seq_lengths[args.da... | 13,724 | 44.598007 | 175 | py |
DeepAligned-Clustering | DeepAligned-Clustering-main/model.py | from util import *
class BertForModel(BertPreTrainedModel):
def __init__(self,config,num_labels):
super(BertForModel, self).__init__(config)
self.num_labels = num_labels
self.bert = BertModel(config)
self.dense = nn.Linear(config.hidden_size, config.hidden_size)
self... | 1,273 | 42.931034 | 169 | py |
DeepAligned-Clustering | DeepAligned-Clustering-main/util.py | import itertools
import subprocess
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import torch
import copy
import torch.nn.functional as F
import random
import csv
import sys
from torch import nn
from tqdm import tqdm_notebook, trange, tqdm
from pytorch_pretrained_bert.optimization imp... | 1,544 | 31.87234 | 110 | py |
DeepAligned-Clustering | DeepAligned-Clustering-main/init_parameter.py | from argparse import ArgumentParser
def init_model():
parser = ArgumentParser()
parser.add_argument("--data_dir", default='data', type=str,
help="The input data dir. Should contain the .csv files (or other data files) for the task.")
parser.add_argument("--save_results_pat... | 3,278 | 46.521739 | 151 | py |
lm-intervention | lm-intervention-master/experiment_num_agreement.py |
import torch
# import torch.nn as nn
import torch.nn.functional as F
import numpy as np
# import random
from functools import partial
from tqdm import tqdm
# from tqdm import tqdm_notebook
import math
import statistics
from utils_num_agreement import batch, convert_results_to_pd
from transformers import (
GPT2LMH... | 37,950 | 44.724096 | 129 | py |
lm-intervention | lm-intervention-master/aggregate_total_effect_bar_plot.py | import pandas as pd
import matplotlib.pyplot as plt
import sys
import seaborn as sns
sns.set()
PATH = sys.argv[1]
FIGURES_PATH = sys.argv[2]
MODELS = ['Distil', 'Small', 'Medium', 'Large', 'XL']
EXAMPLE_TYPES = ['None', 'Distractor', 'Plural attractor',
'Singular attractor']
FORMAT = '.pdf'
def save_aggrega... | 1,324 | 31.317073 | 77 | py |
lm-intervention | lm-intervention-master/attention_utils.py | import torch
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
from tqdm import tqdm
import pandas as pd
import numpy as np
from scipy.stats import ttest_ind
def perform_intervention(intervention, model, effect_types=('indirect', 'direct')):
"""Perform intervention and return results for specified ... | 9,550 | 44.265403 | 142 | py |
lm-intervention | lm-intervention-master/attention_figures3.py | """Creates figures showing attention for specific examples, based on JSON files"""
import json
import math
from operator import itemgetter
import numpy as np
import seaborn as sns
import torch
from matplotlib import pyplot as plt
from transformers import GPT2Model, GPT2Tokenizer
BLACK = '#000000'
GRAY = '#303030'
d... | 8,088 | 38.847291 | 128 | py |
lm-intervention | lm-intervention-master/generate_sentences.py | import os
import csv
from vocab_utils import get_nouns, get_verbs
PATH = "vocab/"
def get_nouns2():
noun2_list = []
with open(os.path.join(PATH, "noun2.txt"), "r") as noun2_file:
for noun2 in noun2_file:
noun2s, noun2p = noun2.split()
noun2_list.append((noun2s, noun2p))
ret... | 3,852 | 37.148515 | 102 | py |
lm-intervention | lm-intervention-master/attention_figures4.py | """Creates summary figure of various effects for attention intervention from JSON file"""
import json
import matplotlib as mpl
import numpy as np
import seaborn as sns
from matplotlib import pyplot as plt
sns.set()
import pandas as pd
import os
def main():
#models = ['distilgpt2', 'gpt2', 'gpt2-medium', 'gpt2-... | 3,438 | 35.2 | 125 | py |
lm-intervention | lm-intervention-master/neuron_experiment_multiple_templates_num_agreement.py |
from datetime import datetime
import os
import sys
import random
from utils_num_agreement import convert_results_to_pd
from experiment_num_agreement import Intervention, Model
from transformers import (
GPT2Tokenizer, TransfoXLTokenizer, XLNetTokenizer, BertTokenizer
)
from vocab_utils import get_nouns, get_nouns... | 6,895 | 42.64557 | 123 | py |
lm-intervention | lm-intervention-master/vocab_utils.py | #!/usr/bin/env python
# coding: utf-8
import pandas as pd
PATH = 'vocab/'
simple = pd.read_csv(PATH + 'simple.txt', sep=' |\t',
engine='python',
names=['The','noun','verb','number',
'grammaticality','id'])
nounpp = pd.read_csv(PATH + 'nounpp.tx... | 4,098 | 32.876033 | 80 | py |
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