Search is not available for this dataset
repo stringlengths 2 152 ⌀ | file stringlengths 15 239 | code stringlengths 0 58.4M | file_length int64 0 58.4M | avg_line_length float64 0 1.81M | max_line_length int64 0 12.7M | extension_type stringclasses 364
values |
|---|---|---|---|---|---|---|
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_379.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt and https://github.com/rte-france/Grid2Op/pull/319
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you ca... | 1,742 | 33.86 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_380.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt and https://github.com/rte-france/Grid2Op/pull/319
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you ca... | 3,716 | 51.352113 | 119 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_389.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt and https://github.com/rte-france/Grid2Op/pull/319
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you ca... | 1,719 | 36.391304 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_396.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt and https://github.com/rte-france/Grid2Op/pull/319
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you ca... | 1,691 | 35.782609 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_403.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 2,696 | 47.160714 | 123 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_407.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 1,413 | 32.666667 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_418.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 2,239 | 39 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_issue_433.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 1,374 | 34.25641 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_l2rpn_idf_2023.py | # Copyright (c) 2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-Lice... | 12,053 | 48.809917 | 125 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_legacygym_compat.py | # Copyright (c) 2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-Lice... | 3,912 | 35.570093 | 122 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_limit_curtail.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 9,379 | 42.425926 | 123 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_multi_steps_env.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 12,288 | 43.687273 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_multi_steps_forecasts.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 23,664 | 42.027273 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_nb_simulate_called.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 7,797 | 38.18593 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_no_backend_copy.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 3,425 | 36.23913 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_noisy_obs.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 7,922 | 35.680556 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_opp_with_area.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 11,281 | 46.403361 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_pickling.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 3,343 | 32.777778 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_recopowerlineperarea.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 4,794 | 41.8125 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_redisp_extreme.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 38,665 | 41.028261 | 116 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_remove_line_status_from_topo.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt and https://github.com/rte-france/Grid2Op/pull/319
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you ca... | 7,262 | 48.074324 | 123 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_render.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 1,030 | 32.258065 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_reward_to_obs.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 3,864 | 38.040404 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_runner_kwargs_backend.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 3,730 | 36.686869 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_score_idf_2023.py | # Copyright (c) 2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-Lice... | 12,114 | 53.327354 | 145 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_score_wcci_2022.py | # Copyright (c) 2019-2022, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 9,831 | 46.269231 | 135 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_simulator.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 14,952 | 36.3825 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_timeOutEnvironment.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 10,818 | 35.550676 | 112 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_ts_handlers.py | # Copyright (c) 2019-2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 39,818 | 53.546575 | 184 | py |
Grid2Op | Grid2Op-master/grid2op/tests/test_utils.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 22,214 | 41.314286 | 125 | py |
Grid2Op | Grid2Op-master/grid2op/utils/__init__.py | __all__ = ["EpisodeStatistics", "ScoreL2RPN2020", "ScoreICAPS2021", "ScoreL2RPN2022", "ScoreL2RPN2023"]
from grid2op.utils.underlying_statistics import EpisodeStatistics
from grid2op.utils.l2rpn_2020_scores import ScoreL2RPN2020
from grid2op.utils.icaps_2021_scores import ScoreICAPS2021
from grid2op.utils.l2rpn_wcci_2... | 416 | 51.125 | 103 | py |
Grid2Op | Grid2Op-master/grid2op/utils/icaps_2021_scores.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 6,515 | 35 | 120 | py |
Grid2Op | Grid2Op-master/grid2op/utils/l2rpn_2020_scores.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 15,987 | 36.268065 | 120 | py |
Grid2Op | Grid2Op-master/grid2op/utils/l2rpn_idf_2023_scores.py | # Copyright (c) 2023, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX-Lice... | 8,080 | 42.213904 | 129 | py |
Grid2Op | Grid2Op-master/grid2op/utils/l2rpn_wcci_2022_scores.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 1,257 | 43.928571 | 147 | py |
Grid2Op | Grid2Op-master/grid2op/utils/underlying_statistics.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 32,419 | 39.323383 | 128 | py |
Grid2Op | Grid2Op-master/utils/edit_layout.py | #!/usr/bin/env python3
import sys
import os
import json
import argparse
import grid2op
from grid2op.PlotGrid import PlotMatplot
def edit_layout(ds_name, test=False):
env = grid2op.make(ds_name, test=test)
plotter = PlotMatplot(env.observation_space)
fig = plotter.plot_layout()
fig.show()
user_i... | 2,049 | 27.082192 | 72 | py |
Grid2Op | Grid2Op-master/utils/make_release.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 10,440 | 44.199134 | 262 | py |
Grid2Op | Grid2Op-master/utils/push_docker.sh | #/bin/bash
# Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/... | 818 | 30.5 | 112 | sh |
Grid2Op | Grid2Op-master/utils/rounder.py | import pandas as pd
files = [
"load_p.csv.bz2",
"load_p_forecasted.csv.bz2",
"load_q.csv.bz2",
"load_q_forecasted.csv.bz2",
"prices.csv.bz2",
"prod_p.csv.bz2",
"prod_p_forecasted.csv.bz2",
"prod_v.csv.bz2"
]
for f in files:
df = pd.read_csv(f, sep=";")
df = df.round(decimals=1)... | 375 | 18.789474 | 38 | py |
Grid2Op | Grid2Op-master/utils/trigger_readthedocs.io.py | # Copyright (c) 2019-2020, RTE (https://www.rte-france.com)
# See AUTHORS.txt
# This Source Code Form is subject to the terms of the Mozilla Public License, version 2.0.
# If a copy of the Mozilla Public License, version 2.0 was not distributed with this file,
# you can obtain one at http://mozilla.org/MPL/2.0/.
# SPDX... | 3,307 | 40.873418 | 171 | py |
null | Vid-ODE-main/README.md | # Vid-ODE - Official PyTorch Implementation
<p align="left"><img width="95%" src="assets/teaser.jpg" /></p>
This repository provides the official PyTorch implementation of the following paper:
> **Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation**<br>
> [Sunghyun Park*](https://ps... | 4,896 | 55.94186 | 1,373 | md |
null | Vid-ODE-main/dataloader.py | import numpy as np
import os
import random
import torch
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms as T
import video_transforms as vtransforms
import utils
class Dataset_base(Dataset):
def __init__(self, opt, train=True):
# Get options
self.opt =... | 13,123 | 40.27044 | 170 | py |
null | Vid-ODE-main/evaluate.py | import argparse
import os
import numpy as np
from PIL import Image
from skimage.metrics import structural_similarity as ssim
from math import log10
import torch
import torch.nn.functional as F
import torchvision.transforms as Transforms
import eval_models as models
def get_opt():
parser = argparse.ArgumentParse... | 2,707 | 31.626506 | 112 | py |
null | Vid-ODE-main/main.py | import torch
import torch.optim as optim
import argparse
import os
import time
import datetime
import json
from pathlib import Path
import numpy as np
from dataloader import parse_datasets
from models.conv_odegru import *
from models.gan import *
from tester import Tester
import utils
import visualize
def get_opt()... | 10,063 | 39.580645 | 152 | py |
null | Vid-ODE-main/tester.py | from pathlib import Path
import os
import json
import utils
import torch
import visualize
import evaluate
from dataloader import remove_files_under_sample_size
class Tester:
def __init__(self):
return
def _load_json(self, opt):
keep_opt_list = ['phase', 'split_time']
... | 3,130 | 40.746667 | 163 | py |
null | Vid-ODE-main/utils.py | import os
import numpy as np
from pathlib import Path
import torch
def create_folder_ifnotexist(folder_path):
folder_path = Path(folder_path)
if not folder_path.exists():
folder_path.mkdir(parents=True, exist_ok=False)
return folder_path
class Tracker(object):
def __init__(self):
... | 6,743 | 31.57971 | 114 | py |
null | Vid-ODE-main/video_transforms.py | import collections
import math
import torch
import random
import numpy as np
import numbers
import cv2
import PIL
from PIL import Image
import torchvision.transforms.functional as F
import skimage
def resize(video, size, interpolation):
if interpolation == 'bilinear':
inter = cv2.INTER_LINEAR
elif inte... | 15,050 | 35.355072 | 114 | py |
null | Vid-ODE-main/visualize.py | import matplotlib
matplotlib.use('Agg')
import torch
from torchvision.utils import save_image
import os
import utils
def save_test_images(opt, preds, batch_dict, path, index):
preds = preds.cpu().detach()
if opt.dataset == 'hurricane':
gt = batch_dict['orignal_data_to_predict'].cpu().detach()
el... | 3,680 | 31.575221 | 155 | py |
null | Vid-ODE-main/eval_models/__init__.py |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from skimage.measure import compare_ssim
import torch
from torch.autograd import Variable
from eval_models import dist_model
class PerceptualLoss(torch.nn.Module):
def __init__(self, m... | 5,726 | 34.571429 | 172 | py |
null | Vid-ODE-main/eval_models/base_model.py | import os
import torch
import numpy as np
class BaseModel():
def __init__(self):
pass;
def name(self):
return 'BaseModel'
def initialize(self, use_gpu=True, gpu_ids=[0]):
self.use_gpu = use_gpu
self.gpu_ids = gpu_ids
def forward(self):
pass
def ge... | 1,525 | 25.77193 | 77 | py |
null | Vid-ODE-main/eval_models/dist_model.py |
from __future__ import absolute_import
import sys
import numpy as np
import torch
from torch import nn
import os
from collections import OrderedDict
from torch.autograd import Variable
import itertools
from .base_model import BaseModel
from scipy.ndimage import zoom
import fractions
import functools
import skimage.tr... | 11,777 | 40.326316 | 177 | py |
null | Vid-ODE-main/eval_models/networks_basic.py |
from __future__ import absolute_import
import sys
import torch
import torch.nn as nn
import torch.nn.init as init
from torch.autograd import Variable
import numpy as np
from skimage import color
from IPython import embed
from . import pretrained_networks as pn
import eval_models as util
def spatial_average(in_tens,... | 7,447 | 38.828877 | 134 | py |
null | Vid-ODE-main/eval_models/pretrained_networks.py | from collections import namedtuple
import torch
from torchvision import models as tv
from IPython import embed
class squeezenet(torch.nn.Module):
def __init__(self, requires_grad=False, pretrained=True):
super(squeezenet, self).__init__()
pretrained_features = tv.squeezenet1_1(pretrained=pretrained... | 6,533 | 34.901099 | 109 | py |
null | Vid-ODE-main/models/__init__.py | 0 | 0 | 0 | py | |
null | Vid-ODE-main/models/base_conv_gru.py | import torch
import torch.nn as nn
import sys
sys.path.append('../')
sys.path.append('./')
import utils
class ConvGRUCell(nn.Module):
def __init__(self, input_size, input_dim, hidden_dim, kernel_size, bias, dtype):
"""
:param input_size: (int, int) / Height and width of input tensor as (height,... | 9,941 | 36.946565 | 112 | py |
null | Vid-ODE-main/models/conv_odegru.py | import torch
import torch.nn as nn
from models.base_conv_gru import *
from models.ode_func import ODEFunc, DiffeqSolver
from models.layers import create_convnet
class VidODE(nn.Module):
def __init__(self, opt, device):
super(VidODE, self).__init__()
self.opt = opt
self.devic... | 12,161 | 43.065217 | 151 | py |
null | Vid-ODE-main/models/gan.py | import torch
import torch.nn as nn
import torch.optim as optim
class ConvNormAct(nn.Module):
def __init__(self, in_ch, out_ch, kernel_size, stride, padding, act_type='relu'):
super(ConvNormAct, self).__init__()
layers = []
layers += [nn.Conv2d(in_ch, out_ch, kernel_si... | 5,314 | 33.512987 | 107 | py |
null | Vid-ODE-main/models/layers.py | import torch.nn as nn
def create_net(n_inputs, n_outputs, n_layers=1,
n_units=100, nonlinear=nn.Tanh):
layers = [nn.Linear(n_inputs, n_units)]
for i in range(n_layers):
layers.append(nonlinear())
layers.append(nn.Linear(n_units, n_units))
layers.append(nonlinear())
l... | 984 | 29.78125 | 83 | py |
null | Vid-ODE-main/models/ode_func.py | import torch
import torch.nn as nn
# git clone https://github.com/rtqichen/torchdiffeq.git
from torchdiffeq import odeint as odeint
class DiffeqSolver(nn.Module):
def __init__(self, input_dim, ode_func, method, latents,
odeint_rtol=1e-4, odeint_atol=1e-5, device=torch.device("cpu")):
sup... | 2,907 | 33.211765 | 135 | py |
null | EMSAFormer-main/.gitlab-ci.yml | stages:
- stylecheck
- test
- deploy
.conda_env: &conda_env
before_script:
# update conda
- conda config --set always_yes yes
- conda update -q conda
# create and activate environment
- conda create -q -n testenv_${CI_JOB_ID}_py${PYTHON_VERSION_TO_USE//./} python=${PY... | 3,569 | 34.7 | 136 | yml |
null | EMSAFormer-main/README.md | # EMSAFormer: Efficient Multi-Task Scene Analysis with RGB-D Transformers
This repository contains the code to our paper
"EMSAFormer: Efficient Multi-Task Scene Analysis with RGB-D Transformers"
([arXiv](https://arxiv.org/pdf/2306.05242.pdf))
EMSAFormer builds on top of our previous work,
[EMSANet](https://github.c... | 22,285 | 38.72549 | 220 | md |
null | EMSAFormer-main/emsaformer_environment_pytorch_2_0.yml | name: emsaformer
channels:
- pytorch
- nvidia
- defaults
dependencies:
- _anaconda_depends=2023.03=py38_0
- _libgcc_mutex=0.1=main
- _openmp_mutex=5.1=1_gnu
- alabaster=0.7.12=pyhd3eb1b0_0
- anaconda=custom=py38_1
- anyio=3.5.0=py38h06a4308_0
- appdirs=1.4.4=pyhd3eb1b0_0
- argon2-cffi=21.3.0=pyhd3... | 14,701 | 31.59867 | 52 | yml |
null | EMSAFormer-main/inference_dataset.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from copy import deepcopy
from datetime import datetime
from functools import partial
import getpass
import json
import os
from pprint import pprint
import sys
from time import time
import warnings
import cv2
import numpy... | 30,738 | 38.05845 | 153 | py |
null | EMSAFormer-main/inference_samples.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Mona Koehler <mona.koehler@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
"""
from glob import glob
import os
import cv2
import matplotlib.pyplot as plt
import nump... | 8,393 | 31.534884 | 96 | py |
null | EMSAFormer-main/main.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
.. codeauthor:: Mona Koehler <mona.koehler@tu-ilmenau.de>
"""
from typing import Tuple
from copy import deepcopy
from datetime import datetime
impor... | 26,219 | 37.110465 | 80 | py |
null | EMSAFormer-main/emsaformer/__init__.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
| 96 | 18.4 | 63 | py |
null | EMSAFormer-main/emsaformer/args.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
.. codeauthor:: Mona Koehler <mona.koehler@tu-ilmenau.de>
"""
import argparse as ap
import json
import os
import shlex
import shutil
import socket
f... | 60,757 | 40.930987 | 93 | py |
null | EMSAFormer-main/emsaformer/data.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from typing import Optional, Iterable, Tuple
from collections import OrderedDict
from copy import deepcopy
from dataclasses import asdict
from f... | 19,253 | 38.946058 | 87 | py |
null | EMSAFormer-main/emsaformer/decoder.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from typing import Tuple, Union
from torch import nn
from nicr_mt_scene_analysis.model.activation import get_activation_class
from nicr_mt_scen... | 9,414 | 45.608911 | 96 | py |
null | EMSAFormer-main/emsaformer/loss_weighting.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from nicr_mt_scene_analysis.loss_weighting import FixedLossWeighting
from nicr_mt_scene_analysis.loss_weighting import LossWeightingType
from nicr_mt_scene_analysis.task_helper.base import get_total_loss_key
def get_loss_... | 1,939 | 37.8 | 80 | py |
null | EMSAFormer-main/emsaformer/lr_scheduler.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from torch.optim.lr_scheduler import OneCycleLR
KNOWN_LR_SCHEDULERS = ('onecycle', )
LrSchedulerType = OneCycleLR
def get_lr_scheduler(args, optimizer) -> LrSchedulerType:
name = args.learning_rate_scheduler
n_... | 818 | 23.088235 | 70 | py |
null | EMSAFormer-main/emsaformer/model.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from typing import Any, Dict
from collections import ChainMap
from nicr_mt_scene_analysis.model.block import get_block_class
from nicr_mt_scene... | 9,460 | 39.431624 | 96 | py |
null | EMSAFormer-main/emsaformer/optimizer.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from typing import Union
from torch.optim import Adam
from torch.optim import AdamW
from torch.optim import RAdam
from torch.optim import SGD
KNOWN_OPTIMIZERS = ('adam', 'adamw', 'radam', 'sgd')
OptimizerType = Union[Ad... | 1,424 | 22.75 | 63 | py |
null | EMSAFormer-main/emsaformer/preprocessing.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from typing import Optional, Tuple
from nicr_mt_scene_analysis.data.preprocessing import CloneEntries
from nicr_mt_scene_analysis.data.preproces... | 9,116 | 37.795745 | 84 | py |
null | EMSAFormer-main/emsaformer/task_helper.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from typing import Tuple
from nicr_mt_scene_analysis.task_helper import NormalTaskHelper
from nicr_mt_scene_analysis.task_helper import Semantic... | 2,775 | 37.027397 | 94 | py |
null | EMSAFormer-main/emsaformer/visualization.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from typing import Any, Dict, Optional, Sequence, Union
import os
import warnings
import cv2
import numpy as np
import PIL
from nicr_mt_scene... | 29,466 | 36.39467 | 84 | py |
null | EMSAFormer-main/emsaformer/weights.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
import torch
from nicr_scene_analysis_datasets import ScanNet
def load_weights(args, model, state_dict, verbose=True):
# this function accounts for:
# - renamed keys, e.g., fused_encoders.* -> encoder.*
# - m... | 5,946 | 47.349593 | 82 | py |
null | EMSAFormer-main/emsaformer/tests/__init__.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
Note that this file is import for test discovery.
"""
| 147 | 20.142857 | 63 | py |
null | EMSAFormer-main/emsaformer/tests/conftest.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
import os
import shutil
import pytest
def pytest_addoption(parser):
parser.addoption('--keep-files', action='store_true', default=False)
parser.addoption('--force-onnx-export', action='store_true', default=False)
... | 1,356 | 28.5 | 79 | py |
null | EMSAFormer-main/emsaformer/tests/test_emsanet_model_weights.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Mona Koehler <mona.koehler@tu-ilmenau.de>
"""
from nicr_mt_scene_analysis.testing.onnx import export_onnx_model
import onnx
import torch
from emsaformer.args import ArgParserEMSAFormer
from emsaformer.data import get_datahelper
from emsaformer.model import EMSAFormer
def t... | 2,485 | 33.054795 | 80 | py |
null | EMSAFormer-main/emsaformer/tests/test_interface_dataset.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
import pytest
import time
from nicr_scene_analysis_datasets.utils.testing import DATASET_PATH_DICT
from emsaformer.args import ArgParserEMSAFor... | 2,551 | 27.355556 | 78 | py |
null | EMSAFormer-main/emsaformer/tests/test_interface_decoders.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
import os
import pytest
import torch
from nicr_mt_scene_analysis.testing.onnx import export_onnx_model
from emsaformer.args import ArgParserE... | 8,676 | 36.240343 | 79 | py |
null | EMSAFormer-main/emsaformer/tests/test_interface_emsaformer_model.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
"""
import os
from nicr_mt_scene_analysis.testing.onnx import export_onnx_model
import pytest
import torch
from emsaformer.args import ArgParserEMS... | 6,571 | 36.554286 | 105 | py |
null | EMSAFormer-main/emsaformer/tests/test_interface_emsanet_model.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
import os
from nicr_mt_scene_analysis.testing.onnx import export_onnx_model
import pytest
import torch
from emsaformer.args import ArgParserEMSAFormer
from emsaformer.data import get_dataset
from emsaformer.model import EM... | 6,470 | 35.559322 | 86 | py |
null | EMSAFormer-main/emsaformer/tests/test_interface_preprocessing.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Daniel Seichter <daniel.seichter@tu-ilmenau.de>
"""
from functools import partial
from nicr_mt_scene_analysis.data import mt_collate
from nicr_mt_scene_analysis.data import CollateIgnoredDict
from nicr_mt_scene_analysis.testing.preprocessing import show_results
from nicr_mt_... | 3,402 | 35.98913 | 75 | py |
null | EMSAFormer-main/emsaformer/tests/test_metrics_with_model.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Soehnke Fischedick <soehnke-benedikt.fischedick@tu-ilmenau.de>
"""
import json
import os
import torch
import numpy as np
import pytest
import PIL.Image as Image
from tqdm import tqdm
from nicr_mt_scene_analysis import metric
from nicr_mt_scene_analysis.data import move_batc... | 9,468 | 39.465812 | 120 | py |
null | EMSAFormer-main/emsaformer/tests/test_semantic_loss.py | # -*- coding: utf-8 -*-
"""
.. codeauthor:: Mona Koehler <mona.koehler@tu-ilmenau.de>
"""
import numpy as np
import torch
from torch import nn
from nicr_mt_scene_analysis.loss.ce import CrossEntropyLossSemantic
DEVICE = 'cuda:0' if torch.cuda.is_available() else 'cpu'
# copied from: https://github.com/TUI-NICR/ESAN... | 3,614 | 33.759615 | 80 | py |
fancyimpute | fancyimpute-master/.travis.yml | sudo: false # Use container-based infrastructure
language: python
env:
global:
- KERAS_BACKEND=tensorflow
- CUDA_VISIBLE_DEVICES=""
matrix:
include:
- python: 3.6
before_install:
# Commands below copied from: http://conda.pydata.org/docs/travis.html
# We do this conditionally because it saves us so... | 2,333 | 42.222222 | 698 | yml |
fancyimpute | fancyimpute-master/README.md | [](https://travis-ci.org/iskandr/fancyimpute) [](https://coveralls.io/github/iskandr/fancyimpute?branch=master) [;
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... | 2,228 | 32.772727 | 99 | py |
fancyimpute | fancyimpute-master/experiments/complete_faces.py | from os import mkdir
from os.path import exists, join
from collections import defaultdict
import pylab
from sklearn.datasets import fetch_lfw_people
from sklearn.impute import IterativeImputer
import numpy as np
from fancyimpute import (
SimpleFill,
IterativeSVD,
SoftImpute,
BiScaler,
KNN
)
from ... | 10,454 | 33.50495 | 86 | py |
fancyimpute | fancyimpute-master/experiments/readme_example.py | import numpy as np
from fancyimpute import (
BiScaler,
KNN,
NuclearNormMinimization,
SoftImpute,
SimpleFill
)
n = 200
m = 20
inner_rank = 4
X = np.dot(np.random.randn(n, inner_rank), np.random.randn(inner_rank, m))
print("Mean squared element: %0.4f" % (X ** 2).mean())
# X is a data matrix which w... | 2,321 | 34.181818 | 84 | py |
fancyimpute | fancyimpute-master/fancyimpute/__init__.py | from __future__ import absolute_import, print_function, division
from .solver import Solver
from .nuclear_norm_minimization import NuclearNormMinimization
from .matrix_factorization import MatrixFactorization
from .iterative_svd import IterativeSVD
from .simple_fill import SimpleFill
from .soft_impute import SoftImput... | 865 | 26.935484 | 70 | py |
fancyimpute | fancyimpute-master/fancyimpute/common.py | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... | 3,268 | 30.432692 | 76 | py |
fancyimpute | fancyimpute-master/fancyimpute/dictionary_helpers.py | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... | 9,665 | 28.379939 | 80 | py |
fancyimpute | fancyimpute-master/fancyimpute/iterative_svd.py | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... | 3,371 | 35.258065 | 74 | py |
fancyimpute | fancyimpute-master/fancyimpute/knn.py | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... | 3,824 | 31.415254 | 97 | py |
fancyimpute | fancyimpute-master/fancyimpute/matrix_factorization.py | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... | 4,625 | 35.714286 | 112 | py |
fancyimpute | fancyimpute-master/fancyimpute/nuclear_norm_minimization.py | # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under th... | 3,999 | 30.007752 | 78 | py |