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
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correlate | correlate-master/regret.py | import numpy as np
import pandas as pd
from config import target_label, verbosity_thesis
def get_last_outcome(ts_measured_actual, n_samples_per_generation):
"""
in the last n_samples_per_generation of ts_measured_actual get value of the target_label
"""
outcome_last = np.array(ts_measured_actual.loc[... | 3,012 | 44.651515 | 155 | py |
correlate | correlate-master/apis/weather.py | import json
import time
import urllib.request
import numpy as np
import pandas as pd
from keys import key_open_weather
def flatten_data(y):
"""flatten json"""
out = {}
def flatten(x, name=''):
if type(x) is dict:
for a in x:
flatten(x[a], name + a + '_')
elif ... | 4,049 | 38.320388 | 143 | py |
correlate | correlate-master/venvCorrleateOnly3.9Fuck/lib/python3.9/site-packages/tigramite/plotting.py | """Tigramite plotting package."""
# Author: Jakob Runge <[email protected]>
#
# License: GNU General Public License v3.0
import numpy as np
import matplotlib
from matplotlib.colors import ListedColormap
import matplotlib.transforms as transforms
from matplotlib import pyplot, ticker
from matplotlib.ticker import F... | 110,838 | 33.680538 | 109 | py |
correlate | correlate-master/venvCorrleateOnly3.9Fuck/lib/python3.9/site-packages/tigramite/independence_tests/independence_tests_base.py | """Tigramite causal discovery for time series."""
# Author: Jakob Runge <[email protected]>
#
# License: GNU General Public License v3.0
from __future__ import print_function
import warnings
import math
import abc
import numpy as np
import six
from hashlib import sha1
@six.add_metaclass(abc.ABCMeta)
class CondI... | 38,744 | 36.616505 | 151 | py |
correlate | correlate-master/intervention_proposal/test_get_intervention.py | import pickle
import numpy as np
from config import checkpoint_path
from intervention_proposal.get_intervention import find_optimistic_intervention, \
drop_redundant_information_due_to_symmetry, get_ambiguous_graph_locations, create_all_graph_combinations, \
graph_to_scm, lin_f, make_redundant_information_wit... | 5,350 | 45.12931 | 139 | py |
correlate | correlate-master/intervention_proposal/simulate.py | 3 | 0 | 0 | py | |
correlate | correlate-master/intervention_proposal/propose_from_eq.py | import numpy as np
from config import target_label, verbosity_thesis
def drop_unintervenable_variables(target_eq, measured_labels):
"""
drop variables from equations which can't be intervened upon
"""
# names of unintervenable vars
# targetlabel
unintervenable_vars = ['u_'+str(target_label)... | 3,319 | 34.319149 | 112 | py |
correlate | correlate-master/intervention_proposal/get_intervention.py | import itertools
from multiprocessing import Pool
from matplotlib import pyplot as plt
from scipy.stats import norm
from tigramite import plotting as tp
from tqdm import tqdm
from config import private_folder_path, show_plots
import numpy as np
import pandas as pd
from config import verbosity_thesis, target_label, t... | 25,836 | 42.496633 | 203 | py |
correlate | correlate-master/causal_discovery/preprocessing.py | # Imports
## use `%matplotlib notebook` for interactive figures
# plt.style.use('ggplot')
from datetime import timedelta
import numpy as np
import pandas as pd
def remove_nan_seq_from_top_and_bot(df):
for column in df:
# reset index
df = df.set_index('Date')
df = df.reset_index()
... | 2,986 | 30.442105 | 103 | py |
correlate | correlate-master/causal_discovery/gen_configs.py | import numpy as np
from config import n_scms
def define_settings():
"""
generate settings for simulation study
"""
settings_default_and_list = {
# n obs before first intervention
'n_ini_obs': [50, [10, 50, 100]],
# n measured vars
'n_vars_measured': [5, np.arange(5, ... | 5,113 | 38.643411 | 125 | py |
correlate | correlate-master/causal_discovery/interventional_discovery.py | import numpy as np
import pandas as pd
import pingouin as pg
from scipy.stats import pearsonr
from config import verbosity_thesis, tau_max, target_label, interventional_discovery_on
from data_generation import labels_to_ints
def interventional_pass_filter(ts, was_intervened, tau):
"""
return only data with i... | 16,762 | 42.427461 | 178 | py |
correlate | correlate-master/causal_discovery/helper.py | import numpy as np
def parabola(x, a, b, c):
x = np.array(x)
return a * x ** 2 + b * x + c
def arg_closest(lst, x):
lst = np.subtract(lst, x)
return np.where(lst == min(lst, key=abs))[0][0]
# def reduce_tau_max(correlations):
# # 3d-> 2D via reshape, 2D->1D via amax, abs
# abs_max_corr_coe... | 1,695 | 41.4 | 115 | py |
correlate | correlate-master/causal_discovery/scratch_pad.py | 0 | 0 | 0 | py | |
correlate | correlate-master/causal_discovery/read_results.py | import math
import pickle
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt
from config import checkpoint_path, n_scms, plots_path
def boxplot_from_df(regret_of_setting_df, x_label, y_label, save_name):
n_settings = regret_of_setting_df.shape[1]
data_values =... | 7,413 | 37.414508 | 145 | py |
correlate | correlate-master/causal_discovery/test_interventional_discovery.py | import numpy as np
import pandas as pd
from pandas.testing import assert_frame_equal
from causal_discovery import interventional_discovery
from causal_discovery.interventional_discovery import remove_weaker_links_of_contempt_cycles, \
get_interv_tau_aligned_cause_eff_df
from config import checkpoint_path
class T... | 10,390 | 45.388393 | 120 | py |
correlate | correlate-master/causal_discovery/LPCMCI/compute_experiments.py | # """
# research module causal discovery:
# simulate data, causal discovery, evaluate
#
# """
# import math
# import os
# import pickle
# import random as rd
# import time
#
# import numpy as np
# import tigramite.data_processing as pp
# from matplotlib import pyplot as plt
# from tigramite import plotting as tp
# from... | 20,531 | 38.790698 | 187 | py |
correlate | correlate-master/causal_discovery/LPCMCI/plan.py | import pickle
import numpy as np
import pandas as pd
from tqdm import tqdm
from causal_discovery.LPCMCI.observational_discovery import observational_causal_discovery
from causal_discovery.gen_configs import define_settings
from causal_discovery.interventional_discovery import get_independencies_from_interv_data
from ... | 18,416 | 41.144165 | 215 | py |
correlate | correlate-master/causal_discovery/LPCMCI/svarrfci.py | # import numpy as np
# from itertools import product, combinations
# import os
#
# class SVARRFCI():
# r"""
# This class implements an adapation of the RFCI algorithm to stationary time series with the assumption of no selection variables. The RFCI algorithm was introduced in:
#
# Colombo, D., Maathuis,... | 106,886 | 46.696118 | 702 | py |
correlate | correlate-master/causal_discovery/LPCMCI/plot_experiments.py | import matplotlib as mpl
# print([key for key in list(mpl.rcParams.keys()) if 'pad' in key])
params = { 'figure.figsize': (8, 10),
'legend.fontsize': 8,
# 'title.fontsize': 8,
'lines.color':'black',
'lines.linewidth':1,
'xtick.labelsize':4,
'xtick.majo... | 28,125 | 35.814136 | 165 | py |
correlate | correlate-master/causal_discovery/LPCMCI/test_observational_discovery.py | import pickle
from matplotlib import pyplot as plt
from tigramite import plotting as tp
from tigramite.independence_tests import ParCorr
from causal_discovery.LPCMCI.lpcmci import LPCMCI
from config import checkpoint_path
class TestLPCMCI:
def test_orient_with_interv_data(self):
interv_independencies ... | 6,955 | 52.507692 | 155 | py |
correlate | correlate-master/causal_discovery/LPCMCI/utilities.py | from collections import OrderedDict
from itertools import product
import numpy as np
import tigramite.data_processing as pp
from causal_discovery.LPCMCI.svarfci import SVARFCI
class OracleCI:
r"""Oracle of conditional independence test X _|_ Y | Z given a graph.
Class around link_coeff causal ground truth.... | 32,514 | 38.700855 | 117 | py |
correlate | correlate-master/causal_discovery/LPCMCI/generate_data_mod.py | from collections import defaultdict
import numpy as np
def check_stationarity(links):
"""Returns stationarity according to a unit root test
Assuming a Gaussian Vector autoregressive process
Three conditions are necessary for stationarity of the VAR(p) model:
- Absence of mean shifts;
- The nois... | 15,012 | 30.606316 | 124 | py |
correlate | correlate-master/causal_discovery/LPCMCI/observational_discovery.py | from time import time
import numpy as np
from tigramite import data_processing as pp
from tigramite.independence_tests import ParCorr
from tigramite.pcmci import PCMCI
from tigramite import plotting as tp
import matplotlib.pyplot as plt
from causal_discovery.LPCMCI.lpcmci import LPCMCI
from config import causal_discov... | 8,472 | 41.365 | 136 | py |
correlate | correlate-master/causal_discovery/LPCMCI/metrics_mod.py | import numpy as np
def get_masks(true_graphs):
n_realizations, N, N, taumaxplusone = true_graphs.shape
tau_max = taumaxplusone - 1
cross_mask = np.repeat(np.identity(N).reshape(N, N, 1) == False, tau_max + 1, axis=2).astype('bool')
cross_mask[range(N), range(N), 0] = False
contemp_cross_mask_tril... | 18,678 | 58.677316 | 149 | py |
correlate | correlate-master/causal_discovery/LPCMCI/simulate_discrete_scm.py | # import numpy as np
# from numpy.random import binomial
# from scipy.special import expit
# from tigramite.data_processing import Graph
#
# def binomial_scp(links, T, n_binom, random_state = None, extremity = 4/5, scale = 1/2,
# centralize = True, cut_off = True):
#
# if random_state is None:
# random_... | 5,084 | 35.321429 | 128 | py |
correlate | correlate-master/causal_discovery/LPCMCI/discG2.py | # import numpy as np
# from scipy.stats import chi2
# from scipy.special import xlogy
# from tigramite.independence_tests import CondIndTest
#
# class DiscG2(CondIndTest):
#
# @property
# def measure(self):
# """
# Concrete property to return the measure of the independence test
# """
# ... | 4,975 | 40.815126 | 97 | py |
correlate | correlate-master/causal_discovery/LPCMCI/svarfci.py | import numpy as np
from itertools import product, combinations
import os
class SVARFCI():
r"""
This class implements the SVAR-FCI algorithm introduced in:
Malinsky, D. and Spirtes, P. (2018). Causal Structure Learning from Multivariate Time Series in Settings with Unmeasured Confounding. In Le, T. D.,... | 98,763 | 45.985728 | 672 | py |
correlate | correlate-master/causal_discovery/LPCMCI/lpcmci.py | from itertools import product, combinations
import numpy as np
class LPCMCI():
r"""
This class implements the LPCMCI algorithm for constraint-based causal discovery on stationary times series with
latent confounders and without selection variables, which we introduce in the main text of this submission.
... | 162,086 | 47.601799 | 552 | py |
correlate | correlate-master/1_data_extraction/weather.py | import os
from datetime import datetime
import pandas as pd
from helper import histograms
"""
go through csv files
create aggregation df for each file
select which aggregation is needed: max, min, mean, sum
append to data frame
write dataframe
"""
path_to_csv_files = '/home/chrei/code/quantifiedSelfData/2022/'
outpu... | 3,373 | 36.488889 | 119 | py |
correlate | correlate-master/1_data_extraction/netatmo.py | from datetime import datetime
from math import isnan
from tqdm import tqdm
from config import private_folder_path
from helper import histograms
import numpy as np
import pandas as pd
"""
1. export:
https://my.netatmo.com/app/station -> settings -> data management -> download
-> format csv -> download 3 months junks... | 6,756 | 37.392045 | 109 | py |
correlate | correlate-master/1_data_extraction/mfp.py | from datetime import datetime
import numpy as np
import pandas as pd
from config import private_folder_path
output_name = str(private_folder_path)+'mfp_daily_summaries.csv'
df = pd.read_csv('/home/chrei/PycharmProjects/correlate/0_data_raw/MFP/meals.csv') # , index_col=0
currentDay = datetime.strptime(df.columns[0]... | 1,912 | 29.854839 | 104 | py |
correlate | correlate-master/1_data_extraction/gFit_to_dailyAggrgations.py | import os
import pandas as pd
from tqdm import tqdm
from helper import histograms
"""
go through csv files
create aggregation df for each file
select which aggregation is needed: max, min, mean, sum
append to data frame
write dataframe
"""
path_to_csv_files = '/home/chrei/code/quantifiedSelfData/2022/takeout-2022050... | 14,365 | 48.367698 | 127 | py |
correlate | correlate-master/1_data_extraction/exist_to_csv_2021_06_15.py | import pandas as pd
import os
"""
correlate
load data form json, into df, correlation matrix, visualize
"""
path_to_json_files = '/home/chrei/code/quantifiedSelfData/2022/ChrisG_a7bdb31dddb7586bea95f752ca7883740c77ae2dde615633ca99b40c74ef9192'
verbose = False
excludedFiles = ['averages.json', 'correlations.json', 'w... | 2,188 | 31.191176 | 135 | py |
correlate | correlate-master/1_data_extraction/google_meditation.py | import os
from datetime import datetime, timedelta
import json
import dateutil
import pandas as pd
from math import floor
path_to_json_files = '/home/chrei/PycharmProjects/correlate/0_data_raw/google/takeout-20210625T075514Z-001/Takeout/Fit/All Sessions'
output_filename = 'google_meditation.csv'
verbose = True
exclu... | 2,527 | 31.831169 | 132 | py |
correlate | correlate-master/1_data_extraction/fitbit_vo2max_json_to_csv.py | import os
from datetime import datetime, timedelta
import pandas as pd
path_to_json_files = '/home/chrei/code/quantifiedSelfData/walter_fitbit/2022/MyFitbitData/Walter/Physical Activity'
output_filename = 'walter_fitbit_vo2max.csv'
verbose = True
excludedFiles = ['']
if verbose:
print('start running...')
def ... | 2,687 | 35.324324 | 115 | py |
correlate | correlate-master/1_data_extraction/fitbit_sleep_json_to_csv.py | import math
import os
from datetime import datetime, timedelta
import pandas as pd
"""
MyFitbitData/ChrisRe/Sleep/sleep_score.csv
reverse sorting: add column with numbers to sort -> add order numbers -> select all cells -> data -> sort... -> select column to sort
check for missing dates or zeros
responsiveness point... | 5,576 | 34.75 | 133 | py |
correlate | correlate-master/1_data_extraction/moonIlluminationByDate.py | import datetime
import pylunar
"""
This script is used to extract the moon illumination data for all dates between "base" and "today".
data is printed and can be copy pasted in to csv.
uncomment printing date-list temporarily and check at https://www.timeanddate.com/moon/phases/germany/stuttgart if correct
"""
mi = py... | 710 | 27.44 | 122 | py |
correlate | correlate-master/prediction/fully_connected.py | import math
import numpy as np
import torch
import torch.utils.data as data_utils
from sklearn.preprocessing import MinMaxScaler
from torch import nn
from torch.utils.tensorboard import SummaryWriter
from config import target_label, fully_connected_nn_prediction_on
writer = SummaryWriter()
epochs = 4115
lr = 0.0001... | 4,817 | 32.227586 | 108 | py |
correlate | correlate-master/prediction/linear_regression.py | import numpy as np
import pandas as pd
from sklearn.linear_model import ElasticNet
from sklearn.model_selection import TimeSeriesSplit
from config import target_label, ensemble_weights, multiple_linear_regression_ensemble_on, \
regularization_strengths, l1_ratios, private_folder_path
from helper import histograms,... | 8,120 | 57.007143 | 111 | py |
ClariQ | ClariQ-master/src/clariq_eval_tool.py | import pandas as pd
import argparse
import pickle
from os import path
import json
from statistics import mean
from sklearn.metrics import precision_score
from sklearn.metrics import recall_score
from sklearn.metrics import f1_score
def evaluate_clarification_need(experiment_type, data_dir, run_file, out_file, leaderb... | 13,590 | 48.421818 | 124 | py |
DeepOnto | DeepOnto-main/src/deeponto/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 1,805 | 38.26087 | 96 | py |
DeepOnto | DeepOnto-main/src/deeponto/probe/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 589 | 44.384615 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/probe/ontolama/inference.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 9,867 | 34.624549 | 114 | py |
DeepOnto | DeepOnto-main/src/deeponto/probe/ontolama/data_processor.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 4,208 | 39.864078 | 111 | py |
DeepOnto | DeepOnto-main/src/deeponto/probe/ontolama/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 627 | 40.866667 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/probe/ontolama/subsumption_sampler.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 13,498 | 47.383513 | 150 | py |
DeepOnto | DeepOnto-main/src/deeponto/subs/__init__.py | # Copyright 2021 Yuan He (KRR-Oxford). 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 applicable l... | 602 | 45.384615 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/subs/bertsubs/pipeline_inter.py | # Copyright 2023 Jiaoyan Chen. 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 applicable law or ag... | 16,303 | 50.432177 | 152 | py |
DeepOnto | DeepOnto-main/src/deeponto/subs/bertsubs/pipeline_intra.py | # Copyright 2023 Jiaoyan Chen. 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 applicable law or ag... | 17,435 | 44.76378 | 120 | py |
DeepOnto | DeepOnto-main/src/deeponto/subs/bertsubs/__init__.py | # Copyright 2023 Jiaoyan Chen. 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 applicable law or ag... | 796 | 45.882353 | 76 | py |
DeepOnto | DeepOnto-main/src/deeponto/subs/bertsubs/text_semantics.py | # Copyright 2023 Jiaoyan Chen. 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 applicable law or ag... | 25,122 | 43.702847 | 146 | py |
DeepOnto | DeepOnto-main/src/deeponto/subs/bertsubs/bert_classifier.py | # Copyright 2023 Jiaoyan Chen. 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 applicable law or ag... | 5,560 | 38.721429 | 116 | py |
DeepOnto | DeepOnto-main/src/deeponto/onto/ontology.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 41,129 | 46.384793 | 211 | py |
DeepOnto | DeepOnto-main/src/deeponto/onto/normalisation.py | # The original code is licensed under the following:
# BSD 3-Clause License
# Copyright (c) 2022, Bio-Ontology Research Group
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# 1. Redistributions ... | 7,223 | 40.28 | 149 | py |
DeepOnto | DeepOnto-main/src/deeponto/onto/verbalisation.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 28,640 | 46.262376 | 910 | py |
DeepOnto | DeepOnto-main/src/deeponto/onto/projection.py | # The original code is licensed under the following:
# BSD 3-Clause License
# Copyright (c) 2022, Bio-Ontology Research Group
# All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# 1. Redistributions ... | 4,274 | 44 | 116 | py |
DeepOnto | DeepOnto-main/src/deeponto/onto/pruning.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 3,170 | 40.181818 | 188 | py |
DeepOnto | DeepOnto-main/src/deeponto/onto/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 831 | 42.789474 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/utils/logging.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 2,609 | 34.27027 | 119 | py |
DeepOnto | DeepOnto-main/src/deeponto/utils/data_utils.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 1,215 | 37 | 88 | py |
DeepOnto | DeepOnto-main/src/deeponto/utils/text_utils.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 7,121 | 41.142012 | 138 | py |
DeepOnto | DeepOnto-main/src/deeponto/utils/file_utils.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 5,752 | 37.871622 | 128 | py |
DeepOnto | DeepOnto-main/src/deeponto/utils/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 719 | 39 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/utils/decorators.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 2,271 | 32.411765 | 94 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 590 | 41.214286 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/evaluation.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 4,843 | 42.63964 | 116 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/mapping.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 28,009 | 50.583794 | 182 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/bertmap/mapping_prediction.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 15,548 | 49.980328 | 161 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/bertmap/mapping_refinement.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 16,390 | 46.648256 | 146 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/bertmap/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 797 | 38.9 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/bertmap/text_semantics.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 28,876 | 48.702238 | 168 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/bertmap/pipeline.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 16,546 | 48.247024 | 161 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/bertmap/bert_classifier.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 10,098 | 44.084821 | 150 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/bertsubs/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 646 | 45.214286 | 74 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/logmap/__init__.py | # Copyright 2021 Yuan He. 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 applicable law or agreed ... | 1,527 | 36.268293 | 84 | py |
DeepOnto | DeepOnto-main/src/deeponto/align/logmap/java-dependencies/__init__.py | # Copyright 2021 Yuan He (KRR-Oxford). 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 applicable l... | 602 | 45.384615 | 74 | py |
DeepOnto | DeepOnto-main/scripts/bertmap.py | # Copyright 2021 Yuan He (KRR-Oxford). 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 applicable l... | 1,675 | 36.244444 | 82 | py |
DeepOnto | DeepOnto-main/scripts/bertsubs_intra_evaluate.py | # Copyright 2023 Jiaoyan Chen. 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 applicable law or ag... | 8,070 | 49.761006 | 124 | py |
DeepOnto | DeepOnto-main/scripts/bertsubs_simple_test.py | # Copyright 2023 Jiaoyan Chen. 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 applicable law or ag... | 2,647 | 43.133333 | 133 | py |
ACE | ACE-main/example.py | import torch
import torch.nn.functional as F
import timm
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from ace import attack_confidence_estimation
def attack_example(file_name, true_label, transform, normalization):
image = Image.open(f'.... | 1,864 | 57.28125 | 149 | py |
ACE | ACE-main/ace.py | import torch
def softmax_response(logits):
return torch.nn.functional.softmax(logits, dim=1)
def attack_confidence_estimation(model, input, label, normalization, proxy=None, epsilon=0.005, epsilon_decay=0.5, max_iterations=15, confidence_score_function=softmax_response, device='cuda'):
input = input.to(devic... | 2,151 | 42.04 | 193 | py |
Fengshenbang-LM | Fengshenbang-LM-main/setup.py | from setuptools import setup, find_packages
setup(
name="fengshen",
version="0.0.1",
description="fengshen",
long_description="fengshen",
license="MIT Licence",
url="https://idea.edu.cn",
author="gaoxinyu",
author_email="[email protected]",
packages=find_packages(),
include_... | 733 | 21.9375 | 69 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/__init__.py | # coding=utf-8
# Copyright 2021 The IDEA 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 a... | 849 | 41.5 | 74 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/cli/fengshen_pipeline.py | import sys
from importlib import import_module
from datasets import load_dataset
import argparse
def main():
if len(sys.argv) < 3:
raise Exception(
'args len < 3, example: fengshen_pipeline text_classification predict xxxxx')
pipeline_name = sys.argv[1]
method = sys.argv[2]
pipelin... | 1,161 | 32.2 | 94 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/strategies/megatron_deepspeed.py | # Copyright The Lightning AI team.
#
# 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 wri... | 18,750 | 45.8775 | 120 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/API/main.py | import uvicorn
import click
import argparse
import json
from importlib import import_module
from fastapi import FastAPI, WebSocket
from starlette.middleware.cors import CORSMiddleware
from utils import user_config, api_logger, setup_logger, RequestDataStructure
# 命令行启动时只输入一个参数，即配置文件的名字，eg: text_classification.json
# 其... | 2,051 | 25.649351 | 102 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/API/utils.py | from dataclasses import dataclass, field
import os
import json
import logging
from argparse import Namespace
from typing import List, Literal, Optional, Union
from pydantic import AnyHttpUrl, BaseSettings, HttpUrl, validator, BaseModel
CURRENT_DIR_PATH = os.path.dirname(os.path.abspath(__file__))
# request body
# 使用... | 6,002 | 34.732143 | 139 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/pretrain_t5/process_data.py | # coding=utf8
import argparse
import sys
import os
from concurrent.futures import ProcessPoolExecutor
def _generate_cache_arrow(index, ds, path):
print('saving dataset shard {}'.format(index))
ds.save_to_disk(os.path.join(path, 'part_{}'.format(index)))
return 'saving dataset shard {} done'.format(index)
... | 2,746 | 40.621212 | 117 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/pretrain_t5/pretrain_t5.py | import time
from builtins import print
import sys
import os
import torch
import argparse
import json
import pytorch_lightning as pl
from transformers import MT5Config, MT5Tokenizer
from pytorch_lightning import Trainer, loggers
from transformers import MT5ForConditionalGeneration
from pytorch_lightning.callbacks import... | 8,139 | 45.25 | 110 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/pretrain_t5/convert_ckpt_to_bin.py | import time
from builtins import print
import argparse
import torch
# os.environ["CUDA_VISIBLE_DEVICES"] = '3'
def get_time_str():
return time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
def main():
total_parser = argparse.ArgumentParser("Pretrain Unsupervise.")
total_parser.add_argument('--ckpt_pa... | 1,071 | 27.210526 | 68 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/pretrain_t5/finetune_t5.py | import time
from builtins import print
import sys
import os
import torch
import argparse
import pytorch_lightning as pl
from pytorch_lightning import Trainer, loggers
from transformers import MT5ForConditionalGeneration
from pytorch_lightning.callbacks import LearningRateMonitor
# os.environ["CUDA_VISIBLE_DEVICES"] = '... | 6,184 | 41.655172 | 110 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/stable_diffusion_dreambooth/train.py | # -*- encoding: utf-8 -*-
'''
Copyright 2022 The International Digital Economy Academy (IDEA). CCNL 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.o... | 11,678 | 41.162455 | 118 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/zen2_finetune/fengshen_token_level_ft_task.py | # coding=utf-8
# Copyright 2021 The IDEA 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 a... | 28,463 | 40.920471 | 163 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/zen2_finetune/fengshen_sequence_level_ft_task.py | # coding=utf-8
# Copyright 2021 The IDEA 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 a... | 27,189 | 40.830769 | 130 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/classification/finetune_classification.py | # coding=utf-8
# Copyright 2021 The IDEA 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 a... | 15,787 | 39.482051 | 117 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/DAVAE/generate.py | # -*- encoding: utf-8 -*-
'''
Copyright 2022 The International Digital Economy Academy (IDEA). CCNL 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.o... | 1,595 | 42.135135 | 157 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/disco_project/st_disco.py | # from disco_huge import Diffuser
# from utils import *
from disco import Diffuser
import streamlit as st
from io import BytesIO
from PIL import Image
from disco import steps
@st.cache(show_spinner=False, allow_output_mutation=True) # 加装饰器， 只加载一次。
class ST_Diffuser(Diffuser):
def __init__(self, custom_path):
... | 2,215 | 37.877193 | 87 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/disco_project/disco.py | import os
import sys
# sys.path.insert(0, f'{PROJECT_DIR}/guided-diffusion') # 加在前面，不再读取库文件的东西。
import subprocess
import io
import torch.nn as nn
from torch.nn import functional as F
import torch
import torchvision.transforms.functional as TF
import torchvision.transforms as T
import math
import requests
import cv2
f... | 29,225 | 38.709239 | 150 | py |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/disco_project/guided_diffusion/__init__.py | 0 | 0 | 0 | py | |
Fengshenbang-LM | Fengshenbang-LM-main/fengshen/examples/disco_project/guided_diffusion/guided_diffusion/resample.py | from abc import ABC, abstractmethod
import numpy as np
import torch as th
import torch.distributed as dist
def create_named_schedule_sampler(name, diffusion):
"""
Create a ScheduleSampler from a library of pre-defined samplers.
:param name: the name of the sampler.
:param diffusion: the diffusion ob... | 5,689 | 35.709677 | 87 | py |
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