repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
pyslam | pyslam-master/utils_files.py | # From torchvision.uitls
import smtplib, socket, os, os.path, hashlib, errno
import __main__ as main
from email.mime.text import MIMEText
from os import path, mkdir
def check_integrity(fpath, md5):
if not os.path.isfile(fpath):
return False
md5o = hashlib.md5()
with open(fpath, "rb") as f:
... | 3,694 | 31.412281 | 155 | py |
pyslam | pyslam-master/feature_hardnet.py | """
* This file is part of PYSLAM
* adapted from https://github.com/DagnyT/hardnet/blob/master/examples/extract_hardnet_desc_from_hpatches_file.py, see licence therein.
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
*... | 8,043 | 38.821782 | 155 | py |
pyslam | pyslam-master/feature_manager.py | """
* This file is part of PYSLAM
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
... | 63,509 | 62.957704 | 272 | py |
pyslam | pyslam-master/feature_delf.py | """
* This file is part of PYSLAM
* Adapted from https://github.com/tensorflow/models/blob/master/research/delf/delf/python/examples/extract_features.py, see the license therein.
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or ... | 12,100 | 40.871972 | 183 | py |
pyslam | pyslam-master/feature_keynet.py | """
* This file is part of PYSLAM
*
* Adpated from https://raw.githubusercontent.com/axelBarroso/Key.Net/master/extract_multiscale_features.py, see the license therein.
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it ... | 19,688 | 42.463576 | 146 | py |
pyslam | pyslam-master/feature_l2net_keras.py | """
* This file is part of PYSLAM
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
... | 2,773 | 32.829268 | 123 | py |
pyslam | pyslam-master/feature_sosnet.py | """
* This file is part of PYSLAM
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
... | 3,919 | 36.692308 | 142 | py |
pyslam | pyslam-master/feature_l2net.py | """
* This file is part of PYSLAM
* Adapted from https://github.com/vcg-uvic/image-matching-benchmark-baselines/blob/master/third_party/l2net_config/l2net_model.py, see licence therein.
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it ... | 7,936 | 39.28934 | 151 | py |
pyslam | pyslam-master/feature_logpolar.py | """
* This file is part of PYSLAM
* adapted from https://github.com/cvlab-epfl/log-polar-descriptors/blob/aed70f882cddcfe0c27b65768b9248bf1f2c65cb/example.py, see licence therein.
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/... | 10,571 | 36.094737 | 147 | py |
pyslam | pyslam-master/feature_geodesc.py | """
* This file is part of PYSLAM
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
... | 5,637 | 36.337748 | 130 | py |
pyslam | pyslam-master/feature_r2d2.py | """
* This file is part of PYSLAM.
* Adapted from https://raw.githubusercontent.com/naver/r2d2/master/extract.py, see the licence therein.
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU ... | 9,607 | 35.393939 | 146 | py |
pyslam | pyslam-master/feature_tfeat.py | """
* This file is part of PYSLAM
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
... | 3,989 | 34.625 | 114 | py |
pyslam | pyslam-master/feature_disk.py | """
* This file is part of PYSLAM
* Adapted from https://github.com/cvlab-epfl/disk/blob/master/detect.py, see licence therein.
*
* Copyright (C) 2016-present Luigi Freda <luigi dot freda at gmail dot com>
*
* PYSLAM is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Publ... | 12,929 | 37.254438 | 181 | py |
pyslam | pyslam-master/thirdparty/l2net_keras/src/LRN.py | from keras import backend as K
from keras.layers.core import Layer
# from https://github.com/ckoren1975/Machine-learning/blob/master/googlenet_custom_layers.py
# except channels have been moved from the 2nd position to the 4th postion
# and shape of input vector is now a tensor operation
# and default args are set to ... | 1,616 | 31.34 | 132 | py |
pyslam | pyslam-master/thirdparty/l2net_keras/src/L2_Net.py | import os
import warnings # to disable tensorflow-numpy warnings: from https://github.com/tensorflow/tensorflow/issues/30427
warnings.filterwarnings('ignore', category=FutureWarning)
import keras
from keras import backend as K
from keras.models import Sequential
from keras.layers import Conv2D, BatchNormalization, ... | 6,657 | 34.227513 | 159 | py |
pyslam | pyslam-master/thirdparty/l2net/l2net_model.py | import torch
import torch.nn.init
import torch.nn as nn
eps = 1e-10
class L2Norm(nn.Module):
def __init__(self):
super(L2Norm,self).__init__()
self.eps = 1e-10
def forward(self, x):
norm = torch.sqrt(torch.sum(x * x, dim = 1) + self.eps)
x= x / norm.unsqueeze(-1).expand_as(x)... | 2,081 | 34.288136 | 92 | py |
pyslam | pyslam-master/thirdparty/l2net/convert_l2net_weights_matconv_pytorch.py | import numpy as np
import scipy.io as sio
import torch
import torch.nn.init
from misc.l2net.l2net_model import L2Net
eps = 1e-10
def check_ported(l2net_model, test_patch, img_mean):
test_patch = test_patch.transpose(3, 2, 0, 1)-img_mean
desc = l2net_model(torch.from_numpy(test_patch))
print(desc)
ret... | 2,854 | 37.066667 | 146 | py |
pyslam | pyslam-master/thirdparty/contextdesc/models/cnn_wrapper/network.py | #!/usr/bin/env python3
"""
Copyright 2017, Zixin Luo, HKUST.
CNN layer wrapper.
Please be noted about following issues:
1. The center and scale paramter are disabled by default for all BN-related layers, as they have
shown little influence on final performance. In particular, scale params is officially considered
unn... | 17,219 | 38.586207 | 110 | py |
pyslam | pyslam-master/test/thirdparty/test_delf.py | # Copyright 2017 The TensorFlow 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 applicab... | 12,641 | 41.280936 | 183 | py |
pyslam | pyslam-master/test/thirdparty/test_tfeat.py | import sys
sys.path.append("../../")
import config
config.cfg.set_lib('tfeat')
import torchvision as tv
import phototour
import torch
from tqdm import tqdm
import numpy as np
import torch.nn as nn
import math
import tfeat_model
import torch.optim as optim
import torch.nn.functional as F
import torch.backends.cudnn... | 2,048 | 24.936709 | 79 | py |
pyslam | pyslam-master/test/thirdparty/test_hardnet_dense.py | #!/usr/bin/python3 -utt
# -*- coding: utf-8 -*-
import sys
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import torch.backends.cudnn as cudnn
import time
import os
#sys.path.insert(0, '/home/ubuntu/dev/opencv-3.1/build/lib')
import cv2
import math
import numpy as... | 4,912 | 35.93985 | 161 | py |
pyslam | pyslam-master/test/thirdparty/test_logpolar.py | # Copyright 2019 EPFL, Google LLC
#
# 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... | 7,015 | 34.979487 | 99 | py |
pyslam | pyslam-master/test/thirdparty/test_l2net_keras.py | import sys
sys.path.append("../../")
import config
config.cfg.set_lib('l2net_keras')
import cv2
import numpy as np
from L2_Net import L2Net
# One of "L2Net-HP", "L2Net-HP+", "L2Net-LIB", "L2Net-LIB+", "L2Net-ND", "L2Net-ND+", "L2Net-YOS", "L2Net-YOS+",
net_name = 'L2Net-HP'
l2net = L2Net(net_name,do_tf_loggin... | 537 | 22.391304 | 113 | py |
pyslam | pyslam-master/test/thirdparty/test_hardnet_patches.py | #!/usr/bin/python3 -utt
# -*- coding: utf-8 -*-
import sys
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import torch.backends.cudnn as cudnn
import time
import os
import cv2
import math
import numpy as np
hardnet_base_path='../../thirdparty/hardnet/'
class L2... | 4,935 | 33.517483 | 155 | py |
pyslam | pyslam-master/test/thirdparty/test_disk.py | # adapted from https://github.com/cvlab-epfl/disk/blob/master/detect.py
import torch, os, argparse, h5py, warnings, imageio
import numpy as np
from tqdm import tqdm
import sys
sys.path.append("../../")
import config
config.cfg.set_lib('disk')
config.cfg.set_lib('torch-dimcheck')
config.cfg.set_lib('torch-localize')... | 9,680 | 33.575 | 110 | py |
pyslam | pyslam-master/test/thirdparty/test_d2net.py | # adapted from https://github.com/mihaidusmanu/d2-net/blob/master/extract_features.py
import sys
sys.path.append("../../")
import config
config.cfg.set_lib('d2net')
import os
import argparse
import numpy as np
import imageio
import cv2
import torch
from tqdm import tqdm
import scipy
import scipy.io
import sc... | 4,953 | 26.370166 | 92 | py |
pyslam | pyslam-master/test/thirdparty/test_keynet.py | # from https://raw.githubusercontent.com/axelBarroso/Key.Net/master/extract_multiscale_features.py
import sys
sys.path.append("../../")
import config
config.cfg.set_lib('keynet')
import warnings # to disable tensorflow-numpy warnings: from https://github.com/tensorflow/tensorflow/issues/30427
warnings.filterwarning... | 13,674 | 40.189759 | 125 | py |
pyslam | pyslam-master/test/thirdparty/test_r2d2.py | # Copyright 2019-present NAVER Corp.
# CC BY-NC-SA 3.0
# Available only for non-commercial use
# from https://raw.githubusercontent.com/naver/r2d2/master/extract.py
import sys
sys.path.append("../../")
import config
config.cfg.set_lib('r2d2')
import os, pdb
from PIL import Image
import numpy as np
import torch
impo... | 6,659 | 32.807107 | 96 | py |
pyslam | pyslam-master/test/thirdparty/test_geodesc.py | #!/usr/bin/env python
"""
Copyright 2018, Zixin Luo, HKUST.
Conduct pair-wise image matching.
"""
# adapted from https://github.com/lzx551402/geodesc/blob/master/examples/image_matching.py
import sys
sys.path.append("../../")
import config
config.cfg.set_lib('geodesc')
#from __future__ import print_function
impor... | 7,192 | 35.328283 | 130 | py |
pyslam | pyslam-master/test/thirdparty/test_contextdesc.py | #!/usr/bin/env python3
# adpated from https://github.com/lzx551402/contextdesc/blob/master/image_matching.py
"""
Copyright 2019, Zixin Luo, HKUST.
Image matching example.
"""
import sys
sys.path.append("../../")
import config
config.cfg.set_lib('contextdesc',prepend=True)
contextdesc_base_path='../../thirdparty/con... | 8,106 | 41.668421 | 183 | py |
pyslam | pyslam-master/test/thirdparty/test_sosnet.py | import sys
sys.path.append("../../")
import config
config.cfg.set_lib('sosnet')
import torch
import sosnet_model
import os
tfeat_base_path='../../thirdparty/SOSNet/'
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
torch.set_grad_enabled(False)
sosnet32 = sosnet_model.SOSNet32x32()
net_name... | 570 | 23.826087 | 122 | py |
GANF | GANF-main/train_traffic.py | #%%
import os
import argparse
import torch
from models.GANF import GANF
import numpy as np
parser = argparse.ArgumentParser()
# files
parser.add_argument('--data_dir', type=str,
default='./data', help='Location of datasets.')
parser.add_argument('--output_dir', type=str,
defa... | 7,602 | 34.036866 | 138 | py |
GANF | GANF-main/utils.py | #%%
import torch
def h(A):
return torch.trace(torch.matrix_exp(A*A)) - A.shape[0]
def normalize(A):
D = A.sum(dim=0)
D_inv = D.pow_(-1)
D_inv.masked_fill_(D_inv == float('inf'), 0)
return A * D_inv
def thresholding(A, thre):
return torch.where(A.abs()>thre, A, torch.scalar_tensor(0.0... | 2,221 | 29.027027 | 103 | py |
GANF | GANF-main/dataset.py | #%%
import pandas as pd
import torch
from torch.utils.data import Dataset
import numpy as np
# %%
from torch.utils.data import DataLoader
def load_traffic(root, batch_size):
"""
Load traffic dataset
return train_loader, val_loader, test_loader
"""
df = pd.read_hdf(root)
df = df.reset_index()
... | 5,624 | 31.894737 | 104 | py |
GANF | GANF-main/train_water.py | #%%
import os
import argparse
import torch
from models.GANF import GANF
import numpy as np
from sklearn.metrics import roc_auc_score
# from data import fetch_dataloaders
parser = argparse.ArgumentParser()
# files
parser.add_argument('--data_dir', type=str,
default='./data/SWaT_Dataset_Attack_v0.c... | 8,511 | 34.319502 | 138 | py |
GANF | GANF-main/eval_water.py | #%%
import os
import argparse
import torch
from models.GANF import GANF
import numpy as np
from sklearn.metrics import roc_auc_score
# from data import fetch_dataloaders
parser = argparse.ArgumentParser()
# files
parser.add_argument('--data_dir', type=str,
default='./data/SWaT_Dataset_Attack_v0.c... | 2,593 | 35.535211 | 138 | py |
GANF | GANF-main/models/RNN.py | #%%
import torch
import torch.nn as nn
from functools import partial
class RecurrentEncoder(nn.Module):
"""Recurrent encoder"""
def __init__(self, n_features, latent_dim, rnn):
super().__init__()
self.rec_enc1 = rnn(n_features, latent_dim, batch_first=True)
def forward(self, x):
... | 2,929 | 26.904762 | 97 | py |
GANF | GANF-main/models/graph_layer.py | import torch
from torch.nn import Parameter, Linear, Sequential, BatchNorm1d, ReLU
import torch.nn.functional as F
from torch_geometric.nn.conv import MessagePassing
from torch_geometric.utils import remove_self_loops, add_self_loops, softmax
from torch_geometric.nn.inits import glorot, zeros
class GraphLayer(Message... | 4,099 | 32.333333 | 84 | py |
GANF | GANF-main/models/NF.py | #%%
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.distributions as D
import math
import copy
# --------------------
# Model layers and helpers
# --------------------
def create_masks(input_size, hidden_size, n_hidden, input_order='sequential', input_degrees=None):
# MADE paper ... | 17,494 | 39.780886 | 169 | py |
GANF | GANF-main/models/DROCC.py | import os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class LSTM_FC(nn.Module):
def __init__(self,
input_dim=32,
num_classes=1,
num_hidden_nodes=8
):
super(LSTM_FC, self).__init__()
self.input_dim = i... | 8,730 | 39.235023 | 106 | py |
GANF | GANF-main/models/DeepSAD.py |
#%%
import json
import torch
import logging
import time
import torch
import torch.optim as optim
class AETrainer:
def __init__(self, device: str = 'cuda'):
self.device = device
def train(self, train_loader, ae_net, args):
logger = logging.getLogger()
# Set device for network
... | 14,064 | 31.55787 | 129 | py |
GANF | GANF-main/models/GAN.py | #%%
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
from timeit import default_timer as timer
def ConvEncoder(activation = nn.LeakyReLU, in_channels:int = 3, n_c:int = 64,
k_size:int = 5):
enc = nn.Sequential(*(nn.Conv1d(in_channels, n_c, k_size, stride=2, paddi... | 10,849 | 34.113269 | 138 | py |
GANF | GANF-main/models/GANF.py |
#%%
import torch.nn as nn
import torch.nn.functional as F
from models.NF import MAF, RealNVP
import torch
class GNN(nn.Module):
"""
The GNN module applied in GANF
"""
def __init__(self, input_size, hidden_size):
super(GNN, self).__init__()
self.lin_n = nn.Linear(input_size, hidden_siz... | 2,705 | 28.413043 | 140 | py |
GANF | GANF-main/example_baseline/train_SVDD_water.py |
#%%
import os
import argparse
import torch
from models.RNN import RecurrentAE
import torch.nn.functional as F
from dataset import PMUTime
import numpy as np
parser = argparse.ArgumentParser()
# action
parser.add_argument('--data_dir', type=str,
default='/data', help='Location of datasets.')
pars... | 2,916 | 33.317647 | 126 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/generate_images.py | # code is partly based on https://huggingface.co/blog/stable_diffusion
import argparse
import math
import os
import pathlib
from datetime import datetime
import torch
from diffusers import AutoencoderKL, LMSDiscreteScheduler, UNet2DConditionModel
from PIL import Image
from rtpt import RTPT
from torch import autocast
... | 11,103 | 35.646865 | 112 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/perform_TPA.py | import argparse
import os
import random
from datetime import datetime
from unicodedata import *
import torch
from PIL import Image
from torch.utils.data import DataLoader
import wandb
from metrics import metrics
from utils.config_parser import ConfigParser
from utils.stable_diffusion_utils import generate
def main(... | 14,103 | 36.913978 | 173 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/perform_clip_retrieval.py | import argparse
import io
import os
import pathlib
import urllib
from datetime import datetime
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from rtpt import RTPT
from transformers import CLIPModel, CLIPTextModel, CLIPTokenizer
import wandb
def main():
args = create_parser()
if ar... | 6,088 | 31.047368 | 90 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/perform_TAA.py | import argparse
import os
from datetime import datetime
import torch
from PIL import Image
from torch.utils.data import DataLoader
from tqdm.auto import tqdm
import wandb
from metrics import metrics
from utils.attack_utils import inject_attribute_backdoor
from utils.config_parser import ConfigParser
from utils.stable... | 12,345 | 36.299094 | 128 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/perform_concept_removal.py | import argparse
import os
import random
from datetime import datetime
import torch
from PIL import Image
from torch.utils.data import DataLoader
from tqdm.auto import tqdm
import wandb
from metrics import metrics
from utils.config_parser import ConfigParser
from utils.stable_diffusion_utils import generate
def main... | 13,458 | 35.773224 | 128 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/metrics/metrics.py | import torch
from utils.attack_utils import inject_attribute_backdoor
from utils.encoder_utils import compute_text_embeddings
from torch.nn.functional import cosine_similarity
from torchmetrics.functional import pairwise_cosine_similarity
def z_score_text(text_encoder: torch.nn.Module,
tokenizer: tor... | 7,426 | 38.930108 | 127 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/utils/config_parser.py | from pathlib import Path
import torch.optim as optim
import yaml
from rtpt.rtpt import RTPT
from transformers import CLIPTextModel, CLIPTokenizer
import datasets
from losses import losses
from datasets import load_dataset
class ConfigParser:
def __init__(self, config_file):
with open(config_file, 'r') ... | 4,674 | 27.858025 | 127 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/utils/encoder_utils.py | import math
from typing import List
import torch
def compute_text_embeddings(tokenizer: torch.nn.Module,
encoder: torch.nn.Module,
prompts: List[str],
batch_size: int = 256) -> torch.Tensor:
with torch.no_grad():
encoder.... | 958 | 34.518519 | 69 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/utils/stable_diffusion_utils.py | from typing import List
import torch
from diffusers import AutoencoderKL, LMSDiscreteScheduler, UNet2DConditionModel
from PIL import Image
from torch import autocast
from tqdm.auto import tqdm
from transformers import CLIPTextModel, CLIPTokenizer
# code is partly based on https://huggingface.co/blog/stable_diffusion
... | 4,710 | 35.51938 | 108 | py |
Rickrolling-the-Artist | Rickrolling-the-Artist-main/losses/losses.py | import torch
from torch.nn.functional import cosine_similarity
class MSELoss(torch.nn.Module):
def __init__(self, flatten: bool = False, reduction: str = 'mean'):
super().__init__()
self.loss_fkt = torch.nn.MSELoss(reduction=reduction)
self.flatten = flatten
def forward(self, input: ... | 2,888 | 31.1 | 72 | py |
DPT-VO | DPT-VO-main/main.py | import numpy as np
import cv2
import argparse
from tqdm import tqdm
from dataloader.kitti import KITTI
from camera_model import CameraModel
from depth_model import DepthModel
from visual_odometry import VisualOdometry
from traj_utils import plot_trajectory, save_trajectory
import torch
if __name__ == "__main__":
... | 4,644 | 33.407407 | 130 | py |
DPT-VO | DPT-VO-main/depth_model.py | """
Build DPT depth model
- modified from https://github.com/isl-org/DPT
"""
import os
import torch
import cv2
import argparse
import util.io
from torchvision.transforms import Compose
from dpt.models import DPTDepthModel
from dpt.transforms import Resize, NormalizeImage, PrepareForNet
class DepthModel(object):
... | 6,129 | 28.052133 | 143 | py |
DPT-VO | DPT-VO-main/util/io.py | """Utils for monoDepth.
"""
import sys
import re
import numpy as np
import cv2
import torch
import matplotlib as mpl
from PIL import Image
from .pallete import get_mask_pallete
def read_pfm(path):
"""Read pfm file.
Args:
path (str): path to file
Returns:
tuple: (data, scale)
"""
... | 5,880 | 24.458874 | 122 | py |
DPT-VO | DPT-VO-main/dpt/base_model.py | import torch
class BaseModel(torch.nn.Module):
def load(self, path):
"""Load model from file.
Args:
path (str): file path
"""
parameters = torch.load(path, map_location=torch.device("cpu"))
if "optimizer" in parameters:
parameters = parameters["mod... | 367 | 20.647059 | 71 | py |
DPT-VO | DPT-VO-main/dpt/midas_net.py | """MidashNet: Network for monocular depth estimation trained by mixing several datasets.
This file contains code that is adapted from
https://github.com/thomasjpfan/pytorch_refinenet/blob/master/pytorch_refinenet/refinenet/refinenet_4cascade.py
"""
import torch
import torch.nn as nn
from .base_model import BaseModel
f... | 2,738 | 34.115385 | 110 | py |
DPT-VO | DPT-VO-main/dpt/vit.py | import torch
import torch.nn as nn
import timm
import types
import math
import torch.nn.functional as F
activations = {}
def get_activation(name):
def hook(model, input, output):
activations[name] = output
return hook
attention = {}
def get_attention(name):
def hook(module, input, output):
... | 17,106 | 28.64818 | 96 | py |
DPT-VO | DPT-VO-main/dpt/models.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from .base_model import BaseModel
from .blocks import (
FeatureFusionBlock,
FeatureFusionBlock_custom,
Interpolate,
_make_encoder,
forward_vit,
)
def _make_fusion_block(features, use_bn):
return FeatureFusionBlock_custom(
... | 4,563 | 28.636364 | 90 | py |
DPT-VO | DPT-VO-main/dpt/blocks.py | import torch
import torch.nn as nn
from .vit import (
_make_pretrained_vitb_rn50_384,
_make_pretrained_vitl16_384,
_make_pretrained_vitb16_384,
forward_vit,
)
def _make_encoder(
backbone,
features,
use_pretrained,
groups=1,
expand=False,
exportable=True,
hooks=None,
us... | 9,090 | 22.674479 | 85 | py |
GraSP | GraSP-master/main_prune_imagenet.py | import argparse
import os
import torch
import torch.nn as nn
from models.model_base import ModelBase
from tensorboardX import SummaryWriter
from models.base.init_utils import weights_init
from utils.common_utils import (get_logger, makedirs, process_config, str_to_list)
from pruner.GraSP_ImageNet import GraSP
import t... | 6,550 | 36.867052 | 106 | py |
GraSP | GraSP-master/main_prune_non_imagenet.py | import argparse
import json
import math
import os
import sys
import torch
import torch.nn as nn
import torch.optim as optim
from models.model_base import ModelBase
from tensorboardX import SummaryWriter
from tqdm import tqdm
from models.base.init_utils import weights_init
from utils.common_utils import (get_logger, ma... | 13,065 | 39.83125 | 119 | py |
GraSP | GraSP-master/main_finetune_imagenet.py | import argparse
import os
import random
import shutil
import time
import warnings
import sys
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.multiprocessing as mp
import torch.utils.data
import torch.utils... | 19,921 | 38.293886 | 112 | py |
GraSP | GraSP-master/pruner/GraSP_ImageNet.py | import torch
import torch.autograd as autograd
import torch.nn as nn
import torch.nn.functional as F
import copy
import types
def count_total_parameters(net):
total = 0
for m in net.modules():
if isinstance(m, (nn.Linear, nn.Conv2d)):
total += m.weight.numel()
return total
def count... | 4,231 | 30.348148 | 113 | py |
GraSP | GraSP-master/pruner/GraSP.py | import torch
import torch.autograd as autograd
import torch.nn as nn
import torch.nn.functional as F
import math
import copy
import types
def GraSP_fetch_data(dataloader, num_classes, samples_per_class):
datas = [[] for _ in range(num_classes)]
labels = [[] for _ in range(num_classes)]
mark = dict()
... | 5,239 | 31.75 | 119 | py |
GraSP | GraSP-master/models/model_base.py | import torch.nn as nn
from collections import OrderedDict
from utils.network_utils import get_network
from utils.prune_utils import filter_weights
class ModelBase(object):
def __init__(self, network, depth, dataset, model=None):
self._network = network
self._depth = depth
self._dataset = ... | 3,183 | 31.161616 | 73 | py |
GraSP | GraSP-master/models/base/resnet.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn.init as init
from utils.common_utils import try_cuda
from .init_utils import weights_init
__all__ = ['resnet'] # , 'resnet20', 'resnet32', 'resnet44', 'resnet56', 'resnet110', 'resnet1202']
_AFFINE = True
#_AFFINE = False
... | 3,943 | 33 | 114 | py |
GraSP | GraSP-master/models/base/vgg.py | import math
import torch
import torch.nn as nn
from .init_utils import weights_init
defaultcfg = {
11: [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512],
13: [64, 64, 'M', 128, 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512],
16: [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 'M', 512, 512, 512... | 2,823 | 35.675325 | 110 | py |
GraSP | GraSP-master/models/base/init_utils.py | import torch
import torch.nn as nn
import torch.nn.init as init
def weights_init(m):
# print('=> weights init')
if isinstance(m, nn.Conv2d):
nn.init.kaiming_normal_(m.weight, mode='fan_out', nonlinearity='relu')
# nn.init.normal_(m.weight, 0, 0.1)
if m.bias is not None:
m.b... | 767 | 32.391304 | 78 | py |
GraSP | GraSP-master/utils/prune_utils.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from .common_utils import try_contiguous
def _fetch_weights_collections(scores, _prev_masks):
weights = []
eps = 1e-10
if _prev_masks is None:
for m in scores.keys():
if isinstance(m, (nn.Linear, nn.... | 8,463 | 33.267206 | 105 | py |
GraSP | GraSP-master/utils/data_utils.py | import torch
import torchvision
import torchvision.transforms as transforms
def get_transforms(dataset):
transform_train = None
transform_test = None
if dataset == 'mnist':
# transforms.Normalize((0.1307,), (0.3081,))
t = transforms.Normalize((0.5,), (0.5,))
transform_train = trans... | 4,728 | 44.038095 | 113 | py |
GraSP | GraSP-master/utils/common_utils.py | import os
import time
import json
import logging
import torch
from pprint import pprint
from easydict import EasyDict as edict
def get_logger(name, logpath, filepath, package_files=[],
displaying=True, saving=True):
logger = logging.getLogger(name)
logger.setLevel(logging.INFO)
log_path =... | 4,926 | 27.982353 | 76 | py |
State-Frequency-Memory-stock-prediction | State-Frequency-Memory-stock-prediction-master/test/itosfm.py | # -*- coding: utf-8 -*-
from __future__ import absolute_import
import numpy as np
import theano.tensor as T
from keras import backend as K
from keras import activations, initializations, regularizers
from keras.engine import Layer, InputSpec
from keras.layers.recurrent import Recurrent
class ITOSFM(Recurrent):
d... | 8,589 | 42.604061 | 104 | py |
State-Frequency-Memory-stock-prediction | State-Frequency-Memory-stock-prediction-master/test/build.py | import time
import warnings
import numpy as np
import keras
from numpy import newaxis
from keras.layers.core import Dense, Activation, Dropout
from itosfm import ITOSFM
from keras.models import Sequential
warnings.filterwarnings("ignore")
#Load data from data file, and split the data into training, validation and tes... | 2,067 | 31.825397 | 88 | py |
State-Frequency-Memory-stock-prediction | State-Frequency-Memory-stock-prediction-master/train/itosfm.py | # -*- coding: utf-8 -*-
from __future__ import absolute_import
import numpy as np
import theano.tensor as T
from keras import backend as K
from keras import activations, initializations, regularizers
from keras.engine import Layer, InputSpec
from keras.layers.recurrent import Recurrent
class ITOSFM(Recurrent):
d... | 8,589 | 42.604061 | 104 | py |
State-Frequency-Memory-stock-prediction | State-Frequency-Memory-stock-prediction-master/train/build.py | import time
import warnings
import numpy as np
import keras
from numpy import newaxis
from keras.layers.core import Dense, Activation, Dropout
from itosfm import ITOSFM
from keras.models import Sequential
warnings.filterwarnings("ignore")
#Load data from data file, and split the data into training, validation and tes... | 2,067 | 31.825397 | 88 | py |
delora | delora-main/setup.py | import os
from setuptools import setup, find_packages
from setuptools.command.install import install
class CustomInstallCommand(install):
# This is only run for "python setup.py install" (not for "pip install -e .")
def run(self):
print("--------------------------------")
print("Writing enviro... | 1,125 | 32.117647 | 107 | py |
delora | delora-main/src/utility/linalg.py | #!/usr/bin/env python3
# Modified from: Modar M. Alfadly, https://discuss.pytorch.org/t/covariance-and-gradient-support/16217
import torch
def cov(point_neighbors, rowvar=True):
'''
Estimate a covariance matrix given data.
Covariance indicates the level to which two variables vary together.
If we exa... | 2,647 | 45.45614 | 102 | py |
delora | delora-main/src/utility/projection.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import numpy as np
import torch
import numba
class ImageProjectionLa... | 5,689 | 50.727273 | 119 | py |
delora | delora-main/src/utility/geometry.py | #!/usr/bin/env python3
# Parts of the code taken from pytorch3d (https://pytorch3d.readthedocs.io/)
import torch
def _angle_from_tan(
axis: str, other_axis: str, data, horizontal: bool, tait_bryan: bool
):
"""
Extract the first or third Euler angle from the two members of
the matrix which are posi... | 3,009 | 33.204545 | 78 | py |
delora | delora-main/src/models/model_parts.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import torch
import platform
if not "2.7" in platform.python_version(... | 3,940 | 41.836957 | 96 | py |
delora | delora-main/src/models/resnet_modified.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
# This model is build on top of the torchvision resnet model.
import t... | 7,993 | 43.910112 | 120 | py |
delora | delora-main/src/models/model.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
from __future__ import division
import torch
import models.model_par... | 6,108 | 51.213675 | 97 | py |
delora | delora-main/src/deploy/tester.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import mlflow
import numpy as np
import pickle
import torch
import de... | 8,233 | 49.515337 | 118 | py |
delora | delora-main/src/deploy/deployer.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import copy
import math
import torch
import mlflow
import numpy as np... | 20,390 | 53.231383 | 119 | py |
delora | delora-main/src/deploy/trainer.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import time
import mlflow
import mlflow.pytorch
import pickle
import ... | 9,336 | 48.930481 | 130 | py |
delora | delora-main/src/ros_utils/rosbag_pcl_extractor.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import numpy as np
import rosbag
import yaml
import sensor_msgs.msg
im... | 2,500 | 38.698413 | 118 | py |
delora | delora-main/src/ros_utils/odometry_publisher.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
from __future__ import division
import time
import cv2
import geometr... | 7,939 | 39.10101 | 119 | py |
delora | delora-main/src/ros_utils/odometry_integrator.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
from __future__ import division
import time
import cv2
import geometr... | 4,075 | 37.45283 | 84 | py |
delora | delora-main/src/ros_utils/publish_point_cloud_and_normals.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import copy
import numpy as np
import geometry_msgs.msg
import rospy
... | 5,759 | 39.851064 | 99 | py |
delora | delora-main/src/ros_utils/convert_to_rosbag.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import os
import rospy
import rosbag
import torch
import sensor_msgs.... | 4,014 | 43.120879 | 118 | py |
delora | delora-main/src/data/kitti_scans.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import os
import glob
import numpy as np
import pykitti
import torch
... | 2,322 | 39.754386 | 118 | py |
delora | delora-main/src/data/dataset.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import csv
import glob
import os
import torch
import numpy as np
# ... | 13,227 | 51.701195 | 120 | py |
delora | delora-main/src/data/rosbag_scans.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import os
import glob
import numpy as np
import torch
import ros_uti... | 1,574 | 37.414634 | 111 | py |
delora | delora-main/src/losses/icp_losses.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import scipy.spatial
import torch
class ICPLosses(torch.nn.Module):
... | 13,291 | 54.153527 | 109 | py |
delora | delora-main/src/preprocessing/normal_computation.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import numpy as np
import torch
import utility.linalg
# Need an ins... | 6,487 | 51.747967 | 101 | py |
delora | delora-main/bin/run_training.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import click
import numpy as np
import torch
import yaml
import deplo... | 3,837 | 39.4 | 110 | py |
delora | delora-main/bin/run_rosnode.py | #!/usr/bin/env python3
# Copyright 2021 by Julian Nubert, Robotic Systems Lab, ETH Zurich.
# All rights reserved.
# This file is released under the "BSD-3-Clause License".
# Please see the LICENSE file that has been included as part of this package.
import click
import numpy as np
import torch
import yaml
import ros_u... | 2,881 | 35.948718 | 117 | py |
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