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 |
|---|---|---|---|---|---|---|
CCasGNN | CCasGNN-main/main.py |
from CCasGNN import CCasGNN_Trainer
from utils import Logger
from param_parser import parameter_parser
import sys
import time
def main():
start = time.time()
args = parameter_parser()
sys.stdout = Logger(args.result_log)
model = CCasGNN_Trainer(args)
model.fit()
# model.test()
end = time.t... | 418 | 21.052632 | 53 | py |
CCasGNN | CCasGNN-main/utils.py |
import sys
class Logger(object):
def __init__ (self, fileN="Default.log"):
self.terminal = sys.stdout
self.log = open(fileN, "a")
def write (self, message):
self.terminal.write(message)
self.log.write(message)
self.log.flush()
def flush (self):
# self.log.... | 340 | 20.3125 | 45 | py |
CCasGNN | CCasGNN-main/layers.py | #encoding: utf-8
import torch
from torch_geometric.nn import GCNConv, GATConv
from math import sqrt
class Positional_GAT(torch.nn.Module):
def __init__(self, in_channels, out_channels, n_heads, location_embedding_dim, filters_1, filters_2, dropout):
super(Positional_GAT, self).__init__()
self.in... | 6,309 | 41.635135 | 180 | py |
CCasGNN | CCasGNN-main/param_parser.py | #encoding:utf-8
import argparse
def parameter_parser():
parser = argparse.ArgumentParser(description="Run CCasGNN.")
parser.add_argument('--graph-file-path',
nargs='?',
default='./weibo/weibo_24hours_obs120.json',
help='Folder with grap... | 4,184 | 35.710526 | 74 | py |
CCasGNN | CCasGNN-main/CCasGNN.py | #encoding: utf-8
import torch
import json
import numpy as np
import copy
import time
import sys
import math
from layers import Positional_GCN, MultiHeadGraphAttention, dens_Net, Positional_GAT, fuse_gate
import scipy.stats as sci
class CCasGNN(torch.nn.Module):
def __init__(self, args):
super(CCasGNN, se... | 13,767 | 50.373134 | 136 | py |
pyEPR | pyEPR-master/setup.py | """
Python (py) Energy-Participation-Ratio (EPR) package
pyEPR is an open source, BSD-licensed library providing high-efficiency,
easy-to-use analysis functions and automation for the design of quantum
chips based on superconducting quantum circuits, both distributed and lumped.
pyEPR interfaces the classical distribut... | 2,596 | 40.887097 | 89 | py |
pyEPR | pyEPR-master/_tutorial_notebooks/1A Startup_example_hfss_files/startup_example_script.py | # -*- coding: utf-8 -*-
"""
Example startup script to perform full quantization of a two qubit, one cavity Josephson circuit.
The results are saved, printed, and nicely plotted.
------~~~~!!!!------~~~~
Please also see the Jupyter notebook tutorials!
------~~~~!!!!------~~~~
@author: Zlatko
"""
from pyEPR import P... | 1,547 | 39.736842 | 142 | py |
pyEPR | pyEPR-master/scripts/Alec/7ghz/7ghz_pyEPR.py | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 23 10:34:00 2017
@author: alec-eickbusch
"""
from pyEPR import *
if 1:
# Specify the HFSS project to be analyzed
project_info = ProjectInfo(r"C:\Users\awe4\Documents\Simulations\HFSS\11ghz\\")
project_info.project_name = '2017_08_Zlatko_Shyam_AutStab' # Na... | 1,651 | 46.2 | 141 | py |
pyEPR | pyEPR-master/scripts/Alec/11ghz/EPR_test.py | # -*- coding: utf-8 -*-
"""
Created on Wed Aug 23 10:34:00 2017
@author: alec-eickbusch
"""
from pyEPR import *
if 0:
# Specify the HFSS project to be analyzed
project_info = ProjectInfo(r"C:\Users\awe4\Documents\Backed\hfss_simulations\11ghz\\")
project_info.project_name = '11ghz_alec' # Name of the p... | 1,540 | 39.552632 | 140 | py |
pyEPR | pyEPR-master/scripts/nick/import_pyEPR.py | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 22 11:21:01 2017
@author: Zlatko
"""
from pyEPR import *
if 0:
# Specify the HFSS project to be analyzed
project_info = ProjectInfo(r"X:\Simulation\\hfss\\KC\\")
project_info.project_name = '2013-12-03_9GHzCavity' # Name of the project file (string). "None... | 2,095 | 44.565217 | 143 | py |
pyEPR | pyEPR-master/scripts/minev/_low_level/com_browse.py | # -*- coding: utf-8 -*-
"""
Debug purpose only
@author: Zlatko Minev
"""
import win32com.client
import win32com.client.combrowse
#win32com.client.combrowse.main()
# A tree heading for registered type libraries"
c = win32com.client.combrowse.HLIHeadingRegisterdTypeLibs()
for s in c.GetSubList():
#print(s)
n... | 526 | 22.954545 | 68 | py |
pyEPR | pyEPR-master/scripts/minev/hfss-scripts/2017_10 R3C1 resim.py | # Zlatko
from pyEPR import *
import matplotlib.pyplot as plt
if 1:
# Specify the HFSS project to be analyzed
project_info = ProjectInfo(r"C:\Users\rslqulab\Desktop\zkm\2017_pyEPR_data\\")
project_info.project_name = '2017-10 re-sim SM22-R3C1'
project_info.design_name = '3. sweep both'
project_i... | 2,994 | 36.911392 | 140 | py |
pyEPR | pyEPR-master/scripts/minev/hfss-scripts/import_pyEPR.py | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 22 11:21:01 2017
@author: Zlatko
"""
from pyEPR import *
if 1:
# Specify the HFSS project to be analyzed
project_info = ProjectInfo(r"C:\\Users\\rslqulab\Desktop\\Lysander\participation_ratio_project\\Shyam's autonomous stabilization simulations\\")
project_... | 1,680 | 45.694444 | 148 | py |
pyEPR | pyEPR-master/scripts/my-name/example1.py | # -*- coding: utf-8 -*-
"""
My First pyEPR Script
"""
from pyEPR import *
# 1. Project and design. Open link to HFSS controls.
project_info = ProjectInfo(r'C:\zkm\my-first-pyEPR\\',
project_name = 'HelloWorld-pyEPR', # Project file name (string). "None" will get the current active one.
design_name =... | 1,258 | 34.971429 | 143 | py |
pyEPR | pyEPR-master/scripts/Kaicheng/import_pyEPR.py | # -*- coding: utf-8 -*-
"""
Created on Tue Aug 22 11:21:01 2017
@author: Zlatko
"""
from pyEPR import *
if 0:
# Specify the HFSS project to be analyzed
project_info = ProjectInfo(r"X:\Simulation\\hfss\\KC\\")
project_info.project_name = '2013-12-03_9GHzCavity' # Name of the project file (string). "None... | 2,038 | 44.311111 | 143 | py |
pyEPR | pyEPR-master/scripts/hanhee/run_vs_pass.py | # -*- coding: utf-8 -*-
"""
Example startup script to perform full quantization of a two qubit, one cavity Josephson circuit.
The results are saved, printed, and nicely plotted.
@author: Zlatko
"""
from pyEPR import ProjectInfo, DistributedAnalysis, QuantumAnalysis
# 1. Project and design. Open link to HFSS control... | 12,386 | 36.536364 | 153 | py |
pyEPR | pyEPR-master/tests/test_quantum_analysis.py | '''
Unit tests for quantum analysis. Takes in pre-made data with known results,
computes the results from the data and checks everything is correct.
'''
import unittest
import pickle
import numpy as np
import sys
sys.path.append('..') # noqa
import pyEPR as epr
# Files location
save_file = './data.npz'
correct_result... | 1,495 | 28.92 | 85 | py |
pyEPR | pyEPR-master/tests/test_project_info.py | import unittest
import sys; sys.path.insert(0, '..') # noqa
import pyEPR as epr
class TestProjectInfo(unittest.TestCase):
'''Test pyEPR.project_info.py'''
def setUp(self):
path_to_project = r'..\_example_files'
try:
self.pinfo = epr.ProjectInfo(project_path=path_to_project,
... | 2,076 | 55.135135 | 90 | py |
pyEPR | pyEPR-master/docs/source/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:
# http://www.sphinx-doc.org/en/master/config
# -- Path setup --------------------------------------------------------------
# If extensions (or module... | 7,220 | 33.716346 | 242 | py |
pyEPR | pyEPR-master/pyEPR/core.py | """
Main interface module to use pyEPR.
Contains code to connect to Ansys and to analyze HFSS files using the EPR method.
This module handles the microwave part of the analysis and connection to
Further contains code to be able to do autogenerated reports,
Copyright Zlatko Minev, Zaki Leghtas, and the pyEPR team
20... | 702 | 27.12 | 81 | py |
pyEPR | pyEPR-master/pyEPR/core_quantum_analysis.py | """
Main interface module to use pyEPR.
Contains code that works on the analysis after hfss, ansys, etc. These can now be closed.
Copyright Zlatko Minev, Zaki Leghtas, and the pyEPR team
2015, 2016, 2017, 2018, 2019, 2020
"""
# pylint: disable=invalid-name
# todo remove this pylint hack later
from __future__ import ... | 44,973 | 36.384871 | 154 | py |
pyEPR | pyEPR-master/pyEPR/project_info.py | """
Main interface module to use pyEPR.
Contains code to connect to Ansys and to analyze HFSS files using the EPR method.
This module handles the microwave part of the analysis and connection to
Further contains code to be able to do autogenerated reports,
Copyright Zlatko Minev, Zaki Leghtas, and the pyEPR team
20... | 18,897 | 37.488798 | 137 | py |
pyEPR | pyEPR-master/pyEPR/core_distributed_analysis.py | """
Main distributed analysis module to use pyEPR.
Contains code to connect to Ansys and to analyze HFSS files using the EPR method.
This module handles the microwave part of the analysis and connection to
Further contains code to be able to do autogenerated reports,
Copyright Zlatko Minev, Zaki Leghtas, and the py... | 62,094 | 36.610539 | 154 | py |
pyEPR | pyEPR-master/pyEPR/_config_default.py | """
--- DO NOT MODIFY THIS FILE ---
Default configuration file for pyEPR
This file is NOT meant for users to modify.
Rather, a user should update any config settings they want
in a dictionary called CONFIG in a file called config.py
@author: Zlatko Minev and the pyEPR team
@date: Created on Fri Oct 30 14:21:45 2015... | 6,018 | 30.186528 | 98 | py |
pyEPR | pyEPR-master/pyEPR/__config_user_old.py | """
User configuration file.
The dictionary of options specified here overwrites the pyEPR default
config defined in _config_default.py
Do not edit `_config_default.py` directly. Rather, overwrite attributes here
@author: Your name goes here
"""
from . import Dict
config = Dict(
# Folder to save result data t... | 2,592 | 30.621951 | 98 | py |
pyEPR | pyEPR-master/pyEPR/reports.py | """
Module for reporting utility functions
@author: Zlatko K Minev
"""
import pandas as pd
from .toolbox.plotting import legend_translucent, plt
def _style_plot_convergence(ax, ylabel=None, xlabel='Pass number', ylabel_col='k', y_title=False):
ax.set_xlabel(xlabel)
if ylabel:
if y_title:
... | 3,910 | 30.039683 | 98 | py |
pyEPR | pyEPR-master/pyEPR/__init__.py | # This file is part of pyEPR: Energy participation ratio (EPR) design of
# quantum circuits in python
#
# Copyright (c) 2015-2020 and later, Zlatko K. Minev and Zaki Leghtas
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided t... | 8,129 | 39.049261 | 95 | py |
pyEPR | pyEPR-master/pyEPR/ansys.py | '''
pyEPR.ansys
2014-present
Purpose:
Handles Ansys interaction and control from version 2014 onward.
Tested most extensively with V2016 and V2019R3.
@authors:
Originally contributed by Phil Reinhold.
Developed further by Zlatko Minev, Zaki Leghtas, and the pyEPR team.
For the base version of ... | 117,733 | 34.78541 | 223 | py |
pyEPR | pyEPR-master/pyEPR/_config_user.py | """
User configuration file.
The dictionary of options specified here overwrites the pyEPR default
config defined in _config_default.py
Do not edit `_config_default.py` directly. Rather, overwrite attributes here.
GIT: Do not track changes here.
Keep your changes only locally. Use the shell command
$ git update... | 3,435 | 32.038462 | 98 | py |
pyEPR | pyEPR-master/pyEPR/calcs/quantum.py | """
Implementation of basic quantum operation in numpy,
to effortlessly remove the need in the `qutip` package.
"""
import numpy as np
def create(n: int):
"""Returns matrix representation of an n-dimensional creation operator"""
diag = np.sqrt(np.arange(1,n))
mat = np.zeros([n, n])
np.fill_diagonal(ma... | 954 | 27.939394 | 90 | py |
pyEPR | pyEPR-master/pyEPR/calcs/constants.py | """
pyEPR constants and convenience definitions.
@author: Zlatko Minev
"""
# pylint: disable=invalid-name
from scipy.constants import Planck, elementary_charge, epsilon_0, pi # pylint: disable=unused-import
# Pi
π = pi
# Reduced Planks constant
ħ = hbar = Planck/(2*pi)
# Reduced Flux Quantum (3.29105976 × 10-16 ... | 457 | 20.809524 | 101 | py |
pyEPR | pyEPR-master/pyEPR/calcs/back_box_numeric.py | '''
Numerical diagonalization of quantum Hamiltonian and parameter
extraction.
@author: Phil Reinhold, Zlatko Minev, Lysander Christakis
Original code on black_box_hamiltonian and make_dispersive functions by Phil Reinhold
Revisions and updates by Zlatko Minev & Lysander Christakis
'''
# pylint: disable=invalid-name
... | 13,172 | 41.908795 | 566 | py |
pyEPR | pyEPR-master/pyEPR/calcs/hamiltonian.py | """
Hamiltonian and Matrix Operations.
Hamiltonian operations heavily draw on qutip package.
This package must be installed for them to work.
"""
try:
import qutip
from qutip import Qobj # basis, tensor,
except (ImportError, ModuleNotFoundError):
Qobj=None
pass
from ..toolbox.pythonic import fact
cl... | 2,628 | 27.576087 | 90 | py |
pyEPR | pyEPR-master/pyEPR/calcs/convert.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 19 18:14:08 2019
Unit and variable conversions.
@author: Zlatko Minev
"""
from __future__ import (absolute_import, # Python 2.7 and 3 compatibility
division, print_function)
import numpy as np
import pandas as pd
from num... | 7,260 | 29.897872 | 115 | py |
pyEPR | pyEPR-master/pyEPR/calcs/__init__.py | """
Main calculation module
"""
from . import constants
from .basic import CalcsBasic
from .convert import Convert
from .transmon import CalcsTransmon
| 151 | 18 | 35 | py |
pyEPR | pyEPR-master/pyEPR/calcs/transmon.py | """
Transmon calculations
"""
import math
import numpy as np
from numpy import pi, sqrt, exp
from numpy.linalg import inv
from .constants import e_el, fluxQ
from .convert import Convert
from ..toolbox.pythonic import divide_diagonal_by_2
class CalcsTransmon():
"""
Common calculations and parameter reporti... | 4,055 | 31.448 | 111 | py |
pyEPR | pyEPR-master/pyEPR/calcs/basic.py | """
Basic calculations that apply in general .
"""
import numpy as np
from numpy import sqrt
from .. import logger
class CalcsBasic():
@staticmethod
def epr_to_zpf(Pmj, SJ, Ω, EJ):
r'''
Arguments, All as matrices (numpy arrays):
:Pnj: MxJ energy-participation-ratio matrix, p_mj
... | 1,691 | 33.530612 | 96 | py |
pyEPR | pyEPR-master/pyEPR/toolbox/plotting.py | # -*- coding: utf-8 -*-
"""
Created on Fri Aug 25 19:30:12 2017
Plotting snippets and useful functions
@author: Zlatko K. Minev
"""
from __future__ import absolute_import, division, print_function
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.axes import Axes
from matpl... | 4,711 | 26.717647 | 117 | py |
pyEPR | pyEPR-master/pyEPR/toolbox/_logging.py | import logging
from .. import config
def set_up_logger(logger):
# add custom stream handler
logger.c_handler = logging.StreamHandler()
# Jupyter notebooks already has a stream handler on the default log,
# Do not propagate upstream to the root logger.
# https://stackoverflow.com/questions/3140367... | 655 | 31.8 | 125 | py |
pyEPR | pyEPR-master/pyEPR/toolbox/pythonic.py | # -*- coding: utf-8 -*-
"""
Created on Sat Feb 04 09:32:46 2017
@author: Zlatko K. Minev, pyEPR ream
"""
from __future__ import division, print_function, absolute_import # Python 2.7 and 3 compatibility
import platform # Which OS we run
import numpy as np
import pandas as pd
import warnings
import matplotlib... | 11,156 | 27.681234 | 134 | py |
pyEPR | pyEPR-master/pyEPR/toolbox/__init__.py | 0 | 0 | 0 | py | |
LogConcComp | LogConcComp-main/src/LCD.py | import numpy as np
from numpy import linalg as la
from scipy.spatial import ConvexHull
import scipy.stats as st
from gurobipy import *
import copy
import time
from functools import reduce
from numbers import Number
from multiprocessing import Pool as pyPool
import multiprocessing
import io
import contextlib
import n... | 57,405 | 42.000749 | 208 | py |
LogConcComp | LogConcComp-main/src/QMC.py | import numpy as np
import numpy.linalg as la
from numbers import Number
from scipy import stats
def sequ(n,d,lb=0,ub=1,method=None,randomized=True, random_state = 1, rng= None,return_likelihood = False):
if rng is None:
rng = np.random.RandomState(seed=random_state)
if method is None:
seq = np... | 2,883 | 36.454545 | 169 | py |
LogConcComp | LogConcComp-main/src/utils.py | import os
import numpy as np
import numba as nb
def create_folder(storage_path):
if not os.path.isdir(storage_path):
os.makedirs(storage_path,exist_ok=True)
lsdir = os.listdir(storage_path)
for item in ["info","hist","soln","figs"]:
if item not in lsdir:
os.makedirs(storage_pat... | 2,223 | 27.512821 | 78 | py |
FUNIT | FUNIT-master/test_k_shot.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import os
import numpy as np
from PIL import Image
import torch
import torch.backends.cudnn as cudnn
from torchvision import transforms
from ut... | 2,618 | 31.7375 | 80 | py |
FUNIT | FUNIT-master/utils.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import os
import yaml
import time
import torch
from torch.utils.data import DataLoader
from torchvision import transforms
import torchvision.uti... | 7,743 | 32.37931 | 77 | py |
FUNIT | FUNIT-master/data.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import os.path
from PIL import Image
import torch.utils.data as data
def default_loader(path):
return Image.open(path).convert('RGB')
de... | 1,913 | 29.870968 | 76 | py |
FUNIT | FUNIT-master/networks.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import numpy as np
import torch
from torch import nn
from torch import autograd
from blocks import LinearBlock, Conv2dBlock, ResBlocks, ActFirs... | 10,860 | 39.830827 | 78 | py |
FUNIT | FUNIT-master/funit_model.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import copy
import torch
import torch.nn as nn
from networks import FewShotGen, GPPatchMcResDis
def recon_criterion(predict, target):
ret... | 5,659 | 41.238806 | 85 | py |
FUNIT | FUNIT-master/train.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import torch
import os
import sys
import argparse
import shutil
from tensorboardX import SummaryWriter
from utils import get_config, get_train_... | 5,178 | 37.93985 | 78 | py |
FUNIT | FUNIT-master/trainer.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import copy
import os
import math
import torch
import torch.nn as nn
import torch.nn.init as init
from torch.optim import lr_scheduler
from fun... | 6,871 | 39.662722 | 79 | py |
FUNIT | FUNIT-master/blocks.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import torch
import torch.nn.functional as F
from torch import nn
class ResBlocks(nn.Module):
def __init__(self, num_blocks, dim, norm, act... | 6,986 | 34.647959 | 79 | py |
FUNIT | FUNIT-master/tools/extract_animalfaces.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import os
import argparse
from PIL import Image
parser = argparse.ArgumentParser()
parser.add_argument('imagenet_folder', type=str)
parser.add_... | 1,077 | 27.368421 | 71 | py |
FUNIT | FUNIT-master/datasets/intermediate_and_scripts/split_and_filter.py | #split and filter the maximum amount of images according to the most restricting datasets in INIT dataset
from math import floor
#filenames of the files containing the paths for the dataset images
TRAIN_FILENAME_PATHS = ["cloudy_list.txt", "night_list.txt", "sunny_list.txt"]
TEST_FILENAME_PATHS = ["rainy_list.txt"]
... | 1,791 | 40.674419 | 139 | py |
SimSiam-91.9-top1-acc-on-CIFAR10 | SimSiam-91.9-top1-acc-on-CIFAR10-main/main.py | import argparse
import time
import math
from os import path, makedirs
import torch
from torch import optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
from torch.backends import cudnn
from torchvision import datasets
from torchvision import transforms
from simsiam.loader ... | 9,087 | 33.687023 | 99 | py |
SimSiam-91.9-top1-acc-on-CIFAR10 | SimSiam-91.9-top1-acc-on-CIFAR10-main/main_lincls.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
import argparse
import builtins
import os
import random
import shutil
import time
import warnings
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dis... | 20,587 | 38.066414 | 95 | py |
SimSiam-91.9-top1-acc-on-CIFAR10 | SimSiam-91.9-top1-acc-on-CIFAR10-main/simsiam/model_factory.py | from torch import nn
from .resnet_cifar import ResNet18, ResNet34, ResNet50, ResNet101, ResNet152
class projection_MLP(nn.Module):
def __init__(self, in_dim, out_dim, num_layers=2):
super().__init__()
hidden_dim = out_dim
self.num_layers = num_layers
self.layer1 = nn.Sequential(
... | 2,575 | 24.76 | 76 | py |
SimSiam-91.9-top1-acc-on-CIFAR10 | SimSiam-91.9-top1-acc-on-CIFAR10-main/simsiam/validation.py | # https://github.com/zhirongw/lemniscate.pytorch/blob/master/test.py
import torch
from torch.utils.data import DataLoader
from torchvision import transforms
from torchvision import datasets
from torch import nn
class KNNValidation(object):
def __init__(self, args, model, K=1):
self.model = model
s... | 3,662 | 38.815217 | 113 | py |
SimSiam-91.9-top1-acc-on-CIFAR10 | SimSiam-91.9-top1-acc-on-CIFAR10-main/simsiam/resnet_cifar.py | '''ResNet in PyTorch.
For Pre-activation ResNet, see 'preact_resnet.py'.
Reference:
[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. arXiv:1512.03385
'''
import torch
import torch.nn as nn
import torch.nn.functional as F
# from lib.normalize import Normalize
fro... | 4,245 | 32.433071 | 102 | py |
SimSiam-91.9-top1-acc-on-CIFAR10 | SimSiam-91.9-top1-acc-on-CIFAR10-main/simsiam/criterion.py | from torch import nn
class SimSiamLoss(nn.Module):
def __init__(self, version='simplified'):
super().__init__()
self.ver = version
def asymmetric_loss(self, p, z):
if self.ver == 'original':
z = z.detach() # stop gradient
p = nn.functional.normalize(p, dim=1)... | 751 | 24.066667 | 73 | py |
SimSiam-91.9-top1-acc-on-CIFAR10 | SimSiam-91.9-top1-acc-on-CIFAR10-main/simsiam/loader.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
from PIL import ImageFilter
import random
class TwoCropsTransform:
"""Take two random crops of one image as the query and key."""
def __init__(self, base_transform):
self.base_transform = base_transform
def __call__(self, x):... | 758 | 26.107143 | 79 | py |
mIOHMM | mIOHMM-main/src/utils.py | import numpy as np
import pickle
import torch
def save_pickle(data, filename):
with open(filename, "wb") as f:
pickle.dump(data, f, pickle.HIGHEST_PROTOCOL)
def load_pickle(filepath):
with open(filepath, "rb") as handle:
data = pickle.load(handle)
return data
def normalize(A, axis=None... | 586 | 19.964286 | 53 | py |
mIOHMM | mIOHMM-main/src/piomhmm.py | from scipy.special import gamma as gamma_fn
from sklearn.cluster import KMeans
from src.utils import normalize_exp
import math
import numpy as np
import pickle
import torch
torch.set_default_dtype(torch.float64)
class mHMM:
def __init__(
self,
data,
ins=None,
K=2,
k=5,
... | 89,160 | 37.867044 | 136 | py |
mIOHMM | mIOHMM-main/src/__init__.py | 0 | 0 | 0 | py | |
mIOHMM | mIOHMM-main/experiments/synthetic.py | from src.piomhmm import mHMM
from src.utils import save_pickle
import matplotlib.pyplot as plt
import numpy as np
import torch
def pred(model_name, model, params, b_hat):
model_mps = model.predict_sequence(params, n_sample=b_hat)
xhat = np.zeros((n, t))
xvar = np.zeros((n, t))
for i in range(n):
... | 8,235 | 28 | 110 | py |
mIOHMM | mIOHMM-main/experiments/real.py | from src.piomhmm import mHMM
import numpy as np
import random
import torch
from src.utils import save_pickle, load_pickle
RANDOM_SEED = 0
torch.manual_seed(RANDOM_SEED)
random.seed(RANDOM_SEED)
np.random.seed(RANDOM_SEED)
torch.set_default_dtype(torch.float64)
torch.set_printoptions(precision=2)
def preprocess(x, d)... | 2,760 | 26.61 | 85 | py |
FADO | FADO-master/documentation.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 1,937 | 30.258065 | 80 | py |
FADO | FADO-master/variable.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 5,558 | 30.948276 | 104 | py |
FADO | FADO-master/function.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 8,997 | 28.405229 | 92 | py |
FADO | FADO-master/__init__.py | from variable import *
from function import *
from evaluation import *
from documentation import *
from tools import LabelReplacer
from tools import ArrayLabelReplacer
from tools import PreStringHandler
from tools import TableReader
from tools import LabeledTableReader
from tools import TableWriter
from tools import Bo... | 640 | 29.52381 | 41 | py |
FADO | FADO-master/evaluation.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 8,188 | 33.552743 | 95 | py |
FADO | FADO-master/tools/__init__.py | from tools.file_parser import *
from tools.variable_transformation import *
| 76 | 24.666667 | 43 | py |
FADO | FADO-master/tools/file_parser.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 9,742 | 28.346386 | 99 | py |
FADO | FADO-master/tools/variable_transformation.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 2,065 | 28.514286 | 90 | py |
FADO | FADO-master/drivers/base_driver.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 12,580 | 35.466667 | 131 | py |
FADO | FADO-master/drivers/ipopt_driver.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 5,641 | 33.402439 | 104 | py |
FADO | FADO-master/drivers/constrained_optim_driver.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 3,450 | 34.214286 | 99 | py |
FADO | FADO-master/drivers/exterior_penalty.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 9,411 | 35.48062 | 105 | py |
FADO | FADO-master/drivers/scipy_driver.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 5,647 | 32.820359 | 97 | py |
FADO | FADO-master/drivers/__init__.py | from drivers.exterior_penalty import *
from drivers.scipy_driver import *
# Import IpOpt driver if possible.
try: from drivers.ipopt_driver import *
except: pass
| 162 | 26.166667 | 39 | py |
FADO | FADO-master/drivers/parallel_eval_driver.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 9,839 | 33.647887 | 86 | py |
FADO | FADO-master/examples/example4_SU2/example.py | # Shape optimization of fluid structure interaction
from FADO import *
import subprocess
subprocess.call("unzip -o data.zip",shell=True)
# Design variables ----------------------------------------------------- #
x0 = np.zeros((17,))
ffd = InputVariable(x0,ArrayLabelReplacer("__FFD_PTS__"),0,(1/0.03),-0.03,0.03)
# P... | 5,417 | 31.25 | 109 | py |
FADO | FADO-master/examples/ipopt/topology_su2.py | # Plain topology optimization example
from FADO import *
import subprocess
import ipyopt
subprocess.call("unzip -o ../example1_SU2/data.zip",shell=True)
# Design variables
rho = InputVariable(0.5,TableWriter(" ",(1,-1)),1600,1.0,0.0,1.0)
# Parameters
adjointOutput = Parameter(["= NONE"], LabelReplacer("= RESTART"))... | 3,508 | 34.09 | 97 | py |
FADO | FADO-master/examples/ipopt/rosenbrock.py | # The basic Rosenbrock example using Ipopt via IPyOpt
from FADO import *
import ipyopt
from shutil import copy
copy("../rosenbrock/direct.py",".")
copy("../rosenbrock/adjoint.py",".")
copy("../rosenbrock/config_tmpl.txt",".")
copy("../rosenbrock/data1.txt",".")
copy("../rosenbrock/data2.txt",".")
# Design variables ... | 3,438 | 34.091837 | 80 | py |
FADO | FADO-master/examples/example1_SU2/example.py | # Plain topology optimization example
from FADO import *
import scipy.optimize
import subprocess
subprocess.call("unzip -o data.zip",shell=True)
# Design variables
rho = InputVariable(0.5,TableWriter(" ",(1,-1)),1600,1.0,0.0,1.0)
# Parameters
output_adjoint = Parameter(["OUTPUT_FILES= NONE"],
LabelRep... | 2,994 | 33.825581 | 90 | py |
FADO | FADO-master/examples/example3_SU2/example.py | # Shape and Topology optimization with 2 load cases
from FADO import *
import scipy.optimize
import os
import subprocess
subprocess.call("unzip -o data.zip",shell=True)
# Design variables
ffd = InputVariable(0.0,PreStringHandler("DV_VALUE= "),9,1.0,-15.0,15.0)
rho = InputVariable(0.5,TableWriter(" ",(1,-1)),4800,1.... | 7,200 | 37.303191 | 108 | py |
FADO | FADO-master/examples/rosenbrock/example.py | # This example mimics the way an external code might work.
#
# For generality:
# 3 functions that result from 2 evaluation of the primal function
#
# Files:
# - direct.py is the primal "solver", it takes a data file and a config.
# Two data files form the two evaluations, it computes 2 functions.
# - adjoint.py co... | 4,047 | 35.468468 | 93 | py |
FADO | FADO-master/examples/rosenbrock/adjoint.py | import sys
import time
#time.sleep(3)
config = sys.argv[1]
fid = open(config,"r")
lines = fid.readlines()
fid.close()
data = lines[0][0:-1]
x = float(lines[1])
y = float(lines[2])
mode = lines[3]
fid = open(data,"r")
lines = fid.readlines()
fid.close()
a = float(lines[0])
b = float(lines[1])
# Rosenbrock's funct... | 613 | 13.97561 | 47 | py |
FADO | FADO-master/examples/rosenbrock/direct.py | import sys
import time
#time.sleep(3)
config = sys.argv[1]
fid = open(config,"r")
lines = fid.readlines()
fid.close()
data = lines[0][0:-1]
x = float(lines[1])
y = float(lines[2])
fid = open(data,"r")
lines = fid.readlines()
fid.close()
a = float(lines[0])
b = float(lines[1])
# Rosenbrock's function
f1 = (a-x)**... | 462 | 13.46875 | 43 | py |
FADO | FADO-master/examples/example2_SU2/example.py | # Plain topology optimization example using the Fletcher-Reeves method
from FADO import *
import subprocess
subprocess.call("unzip -o ../example1_SU2/data.zip",shell=True)
# Design variables
rho = InputVariable(0.5,TableWriter(" ",(1,-1)),1600,1.0,0.0,1.0)
# Parameters
fType_objective = Parameter(["REFERENCE_NODE"]... | 2,755 | 32.609756 | 103 | py |
FADO | FADO-master/optimizers/fletcher_reeves.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 4,882 | 33.146853 | 91 | py |
FADO | FADO-master/optimizers/line_searches.py | # Copyright 2019-2023, FADO Contributors (cf. AUTHORS.md)
#
# This file is part of FADO.
#
# FADO 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 opt... | 4,086 | 24.704403 | 96 | py |
FADO | FADO-master/optimizers/__init__.py | from optimizers.fletcher_reeves import *
from optimizers.line_searches import *
| 80 | 26 | 40 | py |
MostAccurableMNIST_keras | MostAccurableMNIST_keras-master/DeepCNN.py | import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Dropout, Activation, Flatten, Conv2D, pooling, Input
from keras.layers.convolutional import Conv2D, ZeroPadding2D
from keras.layers.pooling import MaxPooling2D
from keras.utils import np_utils
from keras.datasets import mnist
from ke... | 2,673 | 32.012346 | 87 | py |
EHR-features | EHR-features-master/boxplots_removing.py | import numpy as np
import matplotlib.pyplot as plt
import csv
file_name = './results/performance_removing.csv'
case_array = []
accuracy_rate = []
miss_rate = []
with open(file_name, 'r') as csvFile:
reader = csv.reader(csvFile)
next(reader)
for row in reader:
case_array.append(int(row[0]))
... | 2,543 | 35.342857 | 277 | py |
EHR-features | EHR-features-master/boxplots_adding.py | import numpy as np
import matplotlib.pyplot as plt
import csv
file_name = './results/performance_adding.csv'
case_array = []
accuracy_rate = []
miss_rate = []
with open(file_name, 'r') as csvFile:
reader = csv.reader(csvFile)
next(reader)
for row in reader:
case_array.append(int(row[0]))
... | 2,213 | 32.044776 | 208 | py |
EDGY | EDGY-master/DDF.py | import hydra
import hydra.utils as utils
import json
from pathlib import Path
import torch
import numpy as np
import librosa
from tqdm import tqdm
import pyloudnorm
from preprocess import preemphasis
from model import Encoder, Decoder
@hydra.main(config_path="Training/VQ-VAE/Configuration_files/DDF.yaml")
def DDF(cfg... | 6,913 | 43.320513 | 111 | py |
EDGY | EDGY-master/Training/VQ-VAE/dataset.py | import numpy as np
import torch
from torch.utils.data import Dataset
import json
from random import randint
from pathlib import Path
class SpeechDataset(Dataset):
def __init__(self, root, hop_length, sr, sample_frames):
self.root = Path(root)
self.hop_length = hop_length
self.sample_frames... | 1,381 | 31.139535 | 93 | py |
EDGY | EDGY-master/Training/VQ-VAE/models.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.distributions import Categorical
from tqdm import tqdm
import numpy as np
from preprocess import mulaw_decode
def get_gru_cell(gru):
gru_cell = nn.GRUCell(gru.input_size, gru.hidden_size)
gru_cell.weight_hh.data = gru.weight_hh_l0.... | 7,998 | 35.861751 | 105 | py |
EDGY | EDGY-master/Training/VQ-VAE/train_VQ.py | import hydra
from hydra import utils
from itertools import chain
from pathlib import Path
from tqdm import tqdm
import apex.amp as amp
import torch
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter
from dataset import Sp... | 4,714 | 37.647541 | 97 | py |
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