index int64 | repo_name string | branch_name string | path string | content string | import_graph string |
|---|---|---|---|---|---|
21,119 | phdesign/microbit_games | refs/heads/main | /bop_it.py | from microbit import *
from time import sleep
from random import randint
import math
import music
# The starting time in milliseconds we will wait for a response.
WAIT_START_MS = 1500
# How quickly the wait time reduces. A smaller value means it shortens more quickly.
DECAY_RATE = 50
# Starting sound volume
START_VOL... | {"/bop_it.py": ["/music/__init__.py"], "/test/test_bop_it.py": ["/bop_it.py"]} |
21,120 | phdesign/microbit_games | refs/heads/main | /music/__init__.py | def play(music, pin="", wait=True, loop=False):
pass
| {"/bop_it.py": ["/music/__init__.py"], "/test/test_bop_it.py": ["/bop_it.py"]} |
21,121 | phdesign/microbit_games | refs/heads/main | /test/test_bop_it.py | from unittest.mock import patch
from bop_it import create_exponential_decay, volume_to_step, change_volume
def test_create_exponential_decay():
fn = create_exponential_decay(1500, 200)
assert fn(0) == 1500
assert round(fn(10)) == 1427
assert round(fn(100)) == 910
assert round(fn(1000)) == 10
def... | {"/bop_it.py": ["/music/__init__.py"], "/test/test_bop_it.py": ["/bop_it.py"]} |
21,123 | xiaywang/QuantLab | refs/heads/master | /quantlab/BCI-CompIV-2a/utils/meter.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
import math
class Meter(object):
def __init__(self, pp_pr, pp_gt):
self.n_tracked = None
self.loss = None
self.avg_loss = None
# main metric is classification error
self.pp_pr = pp_pr
self.pp_gt... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,124 | xiaywang/QuantLab | refs/heads/master | /quantlab/treat/daemon.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import torch
import torch.optim as optim
import torch.utils.data as tud
import itertools
from quantlab.treat.thermo.thermostat import Thermostat
import quantlab.treat.algo.lr_schedulers as lr_schedulers
class DynamicSu... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,125 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/ResNet/resnet.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
# large parts of the code taken or adapted from torchvision
import math
import torch
import torch.nn as nn
#from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLinear, StochasticConv2d
from quantlab.indiv.inq_ops import INQController, INQLinear, I... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,126 | xiaywang/QuantLab | refs/heads/master | /quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import torch
import torch.nn as nn
import math
from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLinear, StochasticConv2d
class MeyerNet(nn.Module):
"""Audio Event Detection quantized Network."""
def __init__(self, capacityFactor=1.0, v... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,127 | xiaywang/QuantLab | refs/heads/master | /quantlab/indiv/stochastic_ops.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import math
# from scipy.stats import norm, uniform
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.modules.utils import _single, _pair, _triple
#from .cuda import init_ffi_lib,... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,128 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import math
import torch.nn as nn
#from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLinear, StochasticConv2d
from quantlab.indiv.inq_ops import INQController, INQLinear, INQConv2d
#from quantlab.... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,129 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/AlexNet/alexnetbaseline.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import torch
import torch.nn as nn
# In order for the baselines to be launched with the same logic as quantized
# models, an empty quantization scheme and an empty thermostat schedule need
# to be configured.
# Use the ... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,130 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/ResNet/postprocess.py | ../MobileNetv2/postprocess.py | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,131 | xiaywang/QuantLab | refs/heads/master | /quantlab/ETHZ-CVL-AED/MeyerNet/preprocess.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import torchvision as tv
import pickle
import os
import numpy as np
import torch
class PickleDictionaryNumpyDataset(tv.datasets.VisionDataset):
"""Looks for a train.pickle or test.pickle file within root. The file has
to contain a dictionary with classes as ke... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,132 | xiaywang/QuantLab | refs/heads/master | /quantlab/CIFAR-10/VGG/preprocess.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
import torchvision
from torchvision.transforms import RandomCrop, RandomHorizontalFlip, ToTensor, Normalize, Compose
from quantlab.treat.data.split import transform_random_split
_CIFAR10 = {
'Normalize': {
'mean': (0.4914, 0.4822, 0.4465),
'std': ... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,133 | xiaywang/QuantLab | refs/heads/master | /quantlab/BCI-CompIV-2a/EEGNet/eegnetbaseline.py | # Copyright (c) 2019 Tibor Schneider
import numpy as np
import torch as t
import torch.nn.functional as F
class EEGNetBaseline(t.nn.Module):
"""
EEGNet
In order for the baseline to be launched with the same logic as the quantized models, an empty
quantization scheme and an empty thermostat schedule ... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,134 | xiaywang/QuantLab | refs/heads/master | /quantlab/ETHZ-CVL-AED/utils/meter.py | ../../CIFAR-10/utils/meter.py | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,135 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/MobileNetv2/mobilenetv2residuals.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import math
import torch.nn as nn
from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLinear, StochasticConv2d
from quantlab.indiv.inq_ops import INQController, INQLinear, INQConv2d
from quantlab.in... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,136 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/AlexNet/alexnet.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import torch
import torch.nn as nn
from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLinear, StochasticConv2d
from quantlab.indiv.inq_ops import INQController, INQLinear, INQConv2d
from quantlab.i... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,137 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/GoogLeNet/__init__.py | from .preprocess import load_data_sets
from .postprocess import postprocess_pr, postprocess_gt
from .googlenet import GoogLeNet
| {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,138 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/GoogLeNet/googlenet.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
# large parts of the code taken or adapted from torchvision
import warnings
from collections import namedtuple
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
#from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLine... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,139 | xiaywang/QuantLab | refs/heads/master | /quantlab/ETHZ-CVL-AED/MeyerNet/postprocess.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
import torch
def postprocess_pr(pr_outs):
_, pr_outs = torch.max(pr_outs, dim=1)
return [p.item() for p in pr_outs.detach().cpu()]
def postprocess_gt(gt_labels):
return [l.item() for l in gt_labels.detach().cpu()]
| {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,140 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/MobileNetv2/preprocess.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import os
import torch
import torchvision
from torchvision.transforms import RandomResizedCrop, RandomHorizontalFlip, Resize, RandomCrop, CenterCrop, ToTensor, Normalize, Compose
_ImageNet = {
'Normalize': {
... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,141 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/MobileNetv2/__init__.py | from .preprocess import load_data_sets
from .postprocess import postprocess_pr, postprocess_gt
from .mobilenetv2baseline import MobileNetv2Baseline
from .mobilenetv2residuals import MobileNetv2Residuals
from .mobilenetv2quantWeight import MobileNetv2QuantWeight
| {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,142 | xiaywang/QuantLab | refs/heads/master | /quantlab/indiv/daemon.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
import torch
import torch.nn as nn
from .transfer import load_pretrained
def get_topo(logbook):
"""Return a network for the experiment and the loss function for training."""
# create the network
net_config = logbook.config['indiv']['net']
if net_... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,143 | xiaywang/QuantLab | refs/heads/master | /quantlab/indiv/ste_ops.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import torch
import quantlab.indiv as indiv
class ClampWithGradInwards(torch.autograd.Function):
"""Clamps the input, passes the grads for inputs inside or at the
"""
@staticmethod
def forward(ctx, x, low, high):
ctx.save_for_backward(x, low, hi... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,144 | xiaywang/QuantLab | refs/heads/master | /eegnet_run.py | import os
import shutil
import json
import sys
import numpy as np
from contextlib import redirect_stdout, redirect_stderr
import progress
from tqdm import tqdm
import pickle
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
from main import main as quantlab_main
PROBLEM = "BCI-CompI... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,145 | xiaywang/QuantLab | refs/heads/master | /quantlab/BCI-CompIV-2a/EEGNet/eegnet.py | # Copyright (c) 2019 Tibor Schneider
import numpy as np
import torch as t
import torch.nn.functional as F
from quantlab.indiv.inq_ops import INQController, INQLinear, INQConv2d
from quantlab.indiv.ste_ops import STEActivation, STEController
class EEGNet(t.nn.Module):
"""
Quantized EEGNet
"""
def __... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,146 | xiaywang/QuantLab | refs/heads/master | /quantlab/MNIST/MLP/mlp.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import math
import torch
import torch.nn as nn
from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLinear
from quantlab.indiv.inq_ops import INQController, INQLinear
class MLP(nn.Module):
"""Quantized Multi-Layer Perceptron (both weights and ... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,147 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/GoogLeNet/preprocess.py | ../MobileNetv2/preprocess.py | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,148 | xiaywang/QuantLab | refs/heads/master | /quantlab/ETHZ-CVL-AED/MeyerNet/__init__.py | from .preprocess import load_data_sets
from .postprocess import postprocess_pr, postprocess_gt
from .meyernet import MeyerNet
| {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,149 | xiaywang/QuantLab | refs/heads/master | /export_net_data.py | import os
import numpy as np
import argparse
import json
import torch
import shutil
from main import main as quantlab_main
parser = argparse.ArgumentParser()
parser.add_argument('-e', '--exp_id', help='experiment identification', type=int, default=999)
parser.add_argument('-s', '--sample', help='index of the sample',... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,150 | xiaywang/QuantLab | refs/heads/master | /main.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import argparse
from quantlab.protocol.logbook import Logbook
from quantlab.indiv.daemon import get_topo
from quantlab.treat.daemon import get_algo, get_data
from quantlab.protocol.rooms import train, test
import quantla... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,151 | xiaywang/QuantLab | refs/heads/master | /quantlab/MNIST/MLP/mlpbaseline.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
import torch.nn as nn
# In order for the baselines to be launched with the same logic as quantized
# models, an empty quantization scheme and an empty thermostat schedule need
# to be configured.
# Use the following templates for the `net` and `thermostat` configurati... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,152 | xiaywang/QuantLab | refs/heads/master | /quantlab/BCI-CompIV-2a/EEGNet/__init__.py | from .preprocess import load_data_sets
from .postprocess import postprocess_pr, postprocess_gt
from .eegnet import EEGNet
from .eegnetbaseline import EEGNetBaseline
| {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,153 | xiaywang/QuantLab | refs/heads/master | /quantlab/CIFAR-10/VGG/vgg.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import torch
import torch.nn as nn
from quantlab.indiv.stochastic_ops import StochasticActivation, StochasticLinear, StochasticConv2d
from quantlab.indiv.inq_ops import INQController, INQLinear, INQConv2d
from quantlab.i... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,154 | xiaywang/QuantLab | refs/heads/master | /quantlab/indiv/inq_ops.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import math
import itertools
import torch
import torch.nn as nn
import quantlab.indiv as indiv
class INQController(indiv.Controller):
"""Instantiate typically once per network, provide it with a list of INQ
modules to control and a INQ schedule, and insert a ... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,155 | xiaywang/QuantLab | refs/heads/master | /quantlab/protocol/rooms.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
from progress.bar import FillingSquaresBar
import torch
import quantlab.indiv as indiv
def train(logbook, net, device, loss_fn, opt, train_l):
"""Run one epoch of the training experiment."""
logbook.meter.reset()... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,156 | xiaywang/QuantLab | refs/heads/master | /plot_npz_tb.py | import os
import numpy as np
import argparse
import matplotlib.pyplot as plt
def plot_npz(filename, export=None, act_quant_line=None):
data = dict(np.load(filename))
if 'num_trials' in data:
del data['num_trials']
plot_data(data, export, act_quant_line)
def plot_tb(filename, export=None, act_qua... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,157 | xiaywang/QuantLab | refs/heads/master | /quantlab/indiv/__init__.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
class Controller(object):
def __init__(self):
pass
def step(self, epoch, optimizer=None, tensorboardWriter=None):
pass
def step_preTraining(self, *args, **kwargs):
self.step(*args, **kwargs)
def step_preVali... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,158 | xiaywang/QuantLab | refs/heads/master | /quantlab/indiv/transfer.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import os
import torch
from quantlab.protocol.logbook import _exp_align_, _ckpt_align_
def load_pretrained(logbook, net):
#get path to pretrained network
pre_config = logbook.config['indiv']['net']['pretra... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,159 | xiaywang/QuantLab | refs/heads/master | /quantlab/ETHZ-CVL-AED/MeyerNet/acousticEventDetDatasetConvert.py | # Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import numpy as np
import re
import os
import pickle
def readSingleFile(fname):
with open(fname) as f:
fileCont = f.read()
arrs = re.findall('array\(\[(.*)\]\)', fileCont)
arrs = [np.fromstring(a, sep=',', dtype=np.int16) for a in arrs]
# ... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,160 | xiaywang/QuantLab | refs/heads/master | /quantlab/BCI-CompIV-2a/EEGNet/preprocess.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani, Tibor Schneider
from os import path
import numpy as np
import scipy.io as sio
from scipy.signal import butter, sosfilt
import numpy as np
import torch as t
from torchvision.transforms import ToTensor, Normalize, Compose
from quantlab.treat.data.split import transform... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,161 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/ResNet/__init__.py | from .preprocess import load_data_sets
from .postprocess import postprocess_pr, postprocess_gt
from .resnet import ResNet
| {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,162 | xiaywang/QuantLab | refs/heads/master | /quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py | # Copyright (c) 2019 UniMoRe, Matteo Spallanzani
# Copyright (c) 2019 ETH Zurich, Lukas Cavigelli
import math
import torch.nn as nn
# In order for the baselines to be launched with the same logic as quantized
# models, an empty quantization scheme and an empty thermostat schedule need
# to be configured.
# Use the f... | {"/quantlab/ImageNet/ResNet/resnet.py": ["/quantlab/indiv/inq_ops.py"], "/quantlab/ETHZ-CVL-AED/MeyerNet/meyernet.py": ["/quantlab/indiv/stochastic_ops.py"], "/quantlab/ImageNet/MobileNetv2/mobilenetv2quantWeight.py": ["/quantlab/indiv/inq_ops.py", "/quantlab/ImageNet/MobileNetv2/mobilenetv2baseline.py"], "/quantlab/Im... |
21,196 | Lila14/multimds | refs/heads/master | /scripts/tad_negative_control.py | import numpy as np
import os
from matplotlib import pyplot as plt
import sys
mat = np.loadtxt("A_background_filtered.bed", dtype=object)
m = len(mat)
ns = []
num_peaks = int(sys.argv[1])
num_overlap = int(sys.argv[2])
for i in range(100):
indices = np.random.randint(0, m-1, num_peaks)
rand_mat = mat[indices]
np.sa... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,197 | Lila14/multimds | refs/heads/master | /scripts/loop_partners_polycomb.py | import os
import numpy as np
from matplotlib import pyplot as plt
from scipy import stats as st
import sys
res_kb = int(sys.argv[1])
if os.path.isfile("polycomb_enrichment.txt"):
os.system("rm polycomb_enrichment.txt")
if os.path.isfile("enhancer_enrichment.txt"):
os.system("rm enhancer_enrichment.txt")
chroms = ... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,198 | Lila14/multimds | refs/heads/master | /scripts/sup3.py | import os
import numpy as np
import sys
sys.path.append("..")
import data_tools as dt
import plotting as plot
os.system("python ../multimds.py -P 0.1 -w 0 ctrl_Scer_13_32kb.bed galactose_Scer_13_32kb.bed")
struct1 = dt.structure_from_file("ctrl_Suva_13_32kb_structure.tsv")
struct2 = dt.structure_from_file("galactose_S... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,199 | Lila14/multimds | refs/heads/master | /scripts/dist_vs_compartment.py | import sys
sys.path.append("..")
from matplotlib import pyplot as plt
import data_tools as dt
import numpy as np
import compartment_analysis as ca
from scipy import stats as st
import linear_algebra as la
import os
from sklearn import svm
res_kb = 100
cell_type1 = "GM12878_combined"
cell_type2 = "K562"
chroms = (1, 2... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,200 | Lila14/multimds | refs/heads/master | /scripts/get_sig.py | from statsmodels.stats.multitest import multipletests
import sys
import os
in_path = sys.argv[1]
prefix = in_path.split(".")[0]
res = int(sys.argv[2])
ps = []
with open(in_path) as in_file:
for line in in_file:
line = line.strip().split()
if line[0] != "\"logFC\"": #skip header
ps.append(float(line[4]))
in_... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,201 | Lila14/multimds | refs/heads/master | /scripts/test_plot.py | import sys
sys.path.append("..")
import data_tools as dt
import plotting as plot
struct1 = dt.structure_from_file("GM12878_combined_21_100kb_structure.tsv")
struct2 = dt.structure_from_file("K562_21_100kb_structure.tsv")
plot.plot_structures_interactive((struct1, struct2))
| {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,202 | Lila14/multimds | refs/heads/master | /scripts/plot_compartment_strength.py | from matplotlib import pyplot as plt
import sys
sys.path.append("..")
import compartment_analysis as ca
import data_tools as dt
import os
paths = sys.argv[1:len(sys.argv)]
prefixes = [os.path.basename(path) for path in paths]
structs = [dt.structureFromBed(path) for path in paths]
mats = [dt.matFromBed(path, struct) f... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,203 | Lila14/multimds | refs/heads/master | /scripts/tadlib_input.py | import sys
sys.path.append("..")
import data_tools as dt
import os
cell_type = sys.argv[1]
os.system("mkdir -p {}_tadlib_input".format(cell_type))
for chrom in (1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22):
path = "hic_data/{}_{}_100kb.bed".format(cell_type, chrom)
structure = dt.str... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,204 | Lila14/multimds | refs/heads/master | /scripts/convert_to_bed.py | import os
chrom_bins = {}
with open("GSE88952_Sc_Su.32000.bed") as in_file:
for line in in_file:
line = line.strip().split()
chrom_bins[line[3]] = "{}\t{}\t{}".format(line[0], line[1], line[2])
in_file.close()
if not os.path.isfile("ctrl_32kb.bed"):
with open("ctrl_32kb.bed", "w") as out_file:
with open("ct... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,205 | Lila14/multimds | refs/heads/master | /scripts/edger_input.py | import sys
sys.path.append("..")
import data_tools as dt
import array_tools as at
import numpy as np
def compatible_chroms(paths):
chroms = [dt.chromFromBed(path) for path in paths]
all_min_pos = [chrom.minPos for chrom in chroms]
all_max_pos = [chrom.maxPos for chrom in chroms]
consensus_min = max(all_min_pos)
c... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,206 | Lila14/multimds | refs/heads/master | /relocalization_peaks.py | import numpy as np
import data_tools as dt
import sys
import os
import linear_algebra as la
import array_tools as at
from scipy import signal as sg
from hmmlearn import hmm
import argparse
def call_peaks(data):
"""Calls peaks using Gaussian hidden markov model"""
reshaped_data = data.reshape(-1,1)
model = hmm.Gauss... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,207 | Lila14/multimds | refs/heads/master | /scripts/call_peaks.py | import numpy as np
import sys
chrom = sys.argv[1]
res = 100000
mat = np.loadtxt("{}_relocalization.tsv".format(chrom))
with open("{}_peaks.bed".format(chrom), "w") as out:
for i, row in enumerate(mat):
if i == 0:
prev = 0
else:
prev = mat[i-1,1]
if i == len(mat) - 1:
next = 0
else:
next = mat[i+... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,208 | Lila14/multimds | refs/heads/master | /scripts/plot_relocalization.py | import os
import sys
sys.path.append("/home/lur159/git/miniMDS")
import data_tools as dt
import linear_algebra as la
from matplotlib import pyplot as plt
import numpy as np
gene_name = sys.argv[1]
chrom_num = sys.argv[2]
gene_loc = int(sys.argv[3])
prefix1 = sys.argv[4]
prefix2 = sys.argv[5]
res_kb = 32
max_dists = [... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,209 | Lila14/multimds | refs/heads/master | /scripts/wig_to_bed.py | """"Convert fixedStep wig to binned bed"""
import sys
sys.path.append("..")
from tools import Tracker
wig = sys.argv[1]
bin_size = int(sys.argv[2])
file_size = int(sys.argv[3])
prefix = wig.split(".")[0]
tracker = Tracker("Converting {}".format(wig), file_size)
tot = 0
count = 0
with open(wig) as in_file:
with o... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,210 | Lila14/multimds | refs/heads/master | /scripts/superenhancer_pie.py | from matplotlib import pyplot as plt
import sys
from scipy import stats as st
plt.pie((int(sys.argv[1]), int(sys.argv[2])), labels=("Enhancer", "No enhancer"))
plt.title("Relocalization peaks")
plt.savefig("relocalization_superenhancer_pie")
plt.close()
plt.pie((int(sys.argv[3]), int(sys.argv[4])), labels=("Enhancer",... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,211 | Lila14/multimds | refs/heads/master | /scripts/test_multimds.py | import sys
sys.path.append("..")
import data_tools as dt
import numpy as np
from joint_mds import Joint_MDS
chrom = sys.argv[1]
res_kb = 100
prefix1 = "GM12878_combined"
prefix2 = "K562"
path1 = "hic_data/{}_{}_{}kb.bed".format(prefix1, chrom, res_kb)
path2 = "hic_data/{}_{}_{}kb.bed".format(prefix2, chrom, res_kb)
... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,212 | Lila14/multimds | refs/heads/master | /scripts/test_quantify_z.py | from sklearn import svm
import numpy as np
import sys
sys.path.append("..")
import data_tools as dt
import compartment_analysis as ca
from matplotlib import pyplot as plt
import os
import linear_algebra as la
import array_tools as at
from scipy import stats as st
#import plotting as plot
res_kb = 100
cell_type1 = sys.... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,213 | Lila14/multimds | refs/heads/master | /scripts/relocalization_peaks.py | import numpy as np
import sys
sys.path.append("..")
import data_tools as dt
import compartment_analysis as ca
import os
import linear_algebra as la
import array_tools as at
from scipy import signal as sg
from hmmlearn import hmm
def normalize(values):
return np.array(values)/max(values)
def format_celltype(cell_type... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,214 | Lila14/multimds | refs/heads/master | /scripts/differential_tad_boundaries.py | cell_type1 = "GM12878_combined"
cell_type2 = "K562"
res = 100000
boundaries = []
with open("{}_tadlib_output.txt".format(cell_type1)) as in_file:
for line in in_file:
line = line.split()
boundary1 = line[0] + "-" + line[1]
if boundary1 not in boundaries:
boundaries.append(boundary1)
boundary2 = line[0] + ... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,215 | Lila14/multimds | refs/heads/master | /joint_mds.py | """
Jointly perform multi-dimensional Scaling (MDS) on two datasets
"""
# original author: Nelle Varoquaux <nelle.varoquaux@gmail.com>
# modified by: Lila Rieber <lur159@psu.edu>
# License: BSD
import numpy as np
import sys
import warnings
from sklearn.base import BaseEstimator
from sklearn.metrics import euclidean_d... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,216 | Lila14/multimds | refs/heads/master | /scripts/get_a_compartment.py | import sys
sys.path.append("..")
import compartment_analysis as ca
import data_tools as dt
import array_tools as at
import os
import numpy as np
res = int(sys.argv[1])
res_kb = res/1000
if os.path.isfile("A_compartment_{}kb.bed".format(res_kb)):
os.system("rm A_compartment_{}kb.bed".format(res_kb))
for chrom in (1,... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,217 | Lila14/multimds | refs/heads/master | /scripts/ttest.py | import numpy as np
from scipy import stats as st
import sys
from matplotlib import pyplot as plt
mat1 = np.loadtxt(sys.argv[1], dtype=object)
enrichments1 = np.array(mat1[:,6], dtype=float)
mat2 = np.loadtxt(sys.argv[2], dtype=object)
enrichments2 = np.array(mat2[:,6], dtype=float)
print st.ttest_ind(enrichments1, enr... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,218 | Lila14/multimds | refs/heads/master | /scripts/enhancer_pie.py | from matplotlib import pyplot as plt
import sys
plt.pie((int(sys.argv[1]), int(sys.argv[2])), labels=("Enhancer", "No enhancer"))
plt.title("Relocalization peaks")
plt.savefig("relocalization_enhancer_pie")
plt.close()
plt.pie((int(sys.argv[3]), int(sys.argv[4])), labels=("Enhancer", "No enhancer"))
plt.title("Backgro... | {"/scripts/test_multimds.py": ["/joint_mds.py"]} |
21,219 | chavarera/Cinfo | refs/heads/master | /lib/windows/NetworkInfo.py | import socket
from lib.windows.common.CommandHandler import CommandHandler
from uuid import getnode as get_mac
from lib.windows.common import Utility as utl
from lib.windows import SystemInfo
#import SystemInfo
import re
class NetworkInfo:
'''
class Name:NetworkInfo
Description: used to Find out network r... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,220 | chavarera/Cinfo | refs/heads/master | /lib/windows/HardwareInfo.py |
from lib.windows.common.CommandHandler import CommandHandler
from lib.windows.common.RegistryHandler import RegistryHandler
from lib.windows.common import Utility as utl
class HardwareInfo:
'''
class_Name:HardwareInfo
Output:Return bios,cpu,usb information
Functions:
getBiosInfo()
getCpuInfo(s... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,221 | chavarera/Cinfo | refs/heads/master | /lib/windows/ServiceInfo.py | from lib.windows.common.CommandHandler import CommandHandler
from lib.windows.common import Utility as utl
class ServiceInfo:
def __init__(self):
self.cmd=CommandHandler()
def Preprocess(self,text):
cmd=f'wmic {text} list /format:csv'
Command_res=self.cmd.getCmdOutput(cmd)
... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,222 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_browsers.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
class get_browsers:
'''
********* THIS SCRIPT RETURNS A LIST CONTAINING BROWSERS INSTALLED ON USER'S LINUX SYSTEM *********
CLASS get_browsers DOCINFO:
get_browsers HAVE TWO FUNCTIONS I.E.,
1) _... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,223 | chavarera/Cinfo | refs/heads/master | /lib/windows/MiscInfo.py | from lib.windows.common.CommandHandler import CommandHandler
from lib.windows.common import Utility as utl
class MiscInfo:
def __init__(self):
self.cmd=CommandHandler()
def Preprocess(self,text):
cmd=f'wmic {text} list /format:csv'
Command_res=self.cmd.getCmdOutput(cmd)
... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,224 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_network_info.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
from tabulate import tabulate
class get_network_info:
'''
CLASS get_network_info PROVIDES THE CURRENT NETWORK CONNECTION STATUS, IP ADDRESS, NET MASK ADDRESS AND BROADCAST ADDRESS ALONGWITH ALL INT... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,225 | chavarera/Cinfo | refs/heads/master | /lib/windows/common/CommandHandler.py | from subprocess import getoutput
class CommandHandler:
def __init__(self,command_text=""):
self.command_text=command_text
def getCmdOutput(self,cmdtext):
try:
return getoutput(cmdtext)
except Exception as ex:
return ex
| {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,226 | chavarera/Cinfo | refs/heads/master | /lib/windows/FileInfo.py | import os
import win32api
class FileInfo:
'''
class Name:
FileInfo
Function Names:
getDrives()
getFileList(path)
GetCount()
'''
def getDrives(self):
'''
getDrives()
Function Return a object list containing all drives List
Output:
List-->All... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,227 | chavarera/Cinfo | refs/heads/master | /MainUi.py | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'Cinfo.ui'
#
# Created by: PyQt5 UI code generator 5.13.0
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore, QtGui, QtWidgets
from lib.windows import SystemInfo,NetworkInfo,SoftwareInfo,StorageInfo
from lib.w... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,228 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_hw_info.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
from tabulate import tabulate
class get_hw_info:
'''
get_hw_info HAVE A SINGLE METHOD AND A CONSTRUCTOR FUNCTION WHICH ARE NAMED AS :
1) __init__
2) work()
__init__ DOCFILE:
__init__ CON... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,229 | chavarera/Cinfo | refs/heads/master | /lib/windows/DeviceInfo.py | from lib.windows.common.CommandHandler import CommandHandler
from lib.windows.common import Utility as utl
class DeviceInfo:
def __init__(self):
self.cmd=CommandHandler()
def Preprocess(self,text):
cmd=f'wmic {text} list /format:csv'
Command_res=self.cmd.getCmdOutput(cmd)
... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,230 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_package_list.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
class get_package_list:
'''
get_package_list CLASS COMBINE A SINGLE METHOD AND A CONSTRUCTOR, WHICH ARE AS FOLLOWS:
1) __init__
2) work()
__init__ DOCFILE:
__init__ SERVES THE PURPOS... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,231 | chavarera/Cinfo | refs/heads/master | /lib/windows/StorageInfo.py | from lib.windows.common.CommandHandler import CommandHandler
import math
from lib.windows.common import Utility as utl
import wmi
class StorageInfo:
'''
className:StorageInfo
Description:this will return the Disk Total Size and partitions details and Ram Details
call this method:
objectName.ge... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,232 | chavarera/Cinfo | refs/heads/master | /lib/linux/list_files.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
import filetype
import json
from datetime import datetime
class list_files:
'''
LIST_FILES CLASS CONTAINS THREE FUNCTIONS:
1) __INIT__
2) WORK()
3) TYPE_COUNT()
INIT BLOCK DOCKINFO :
INIT B... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,233 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_os_info.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
from tabulate import tabulate
class get_os_info:
'''
CLASS get_base_info PROVIDES ALL DETAILS REGARDING OS, CPU AND USERS IN MACHINE,
IT CONTAINS TWO FUNCTIONS I.E.
1) __init__
2) work()
__ini... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,234 | chavarera/Cinfo | refs/heads/master | /WindowsInfo.py | from lib.windows import SystemInfo,NetworkInfo,SoftwareInfo,StorageInfo
from lib.windows import HardwareInfo,FileInfo,DeviceInfo,MiscInfo,ServiceInfo
import os
import json
import pickle
def Display(d, indent=0):
return json.dumps(d,sort_keys=True, indent=4)
def SavePickle(data):
with open('result.pickle','wb')... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,235 | chavarera/Cinfo | refs/heads/master | /lib/windows/common/Utility.py | import time
import json
def CsvTextToDict(text):
lines = text.strip().splitlines()
keys=lines[0].split(",")
items=[]
for line in lines[1:]:
if len(line)>0:
items.append(dict(zip(keys,line.split(","))))
return items
def ExportTOJson(data):
timestr = time.strftime("%... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,236 | chavarera/Cinfo | refs/heads/master | /lib/windows/SoftwareInfo.py | try:
import _winreg as reg
except:
import winreg as reg
class SoftwareInfo:
'''
className:SoftwareInfo
Description:Return the Installed Software name with version and publisher name
'''
def getVal(self,name,asubkey):
try:
return reg.QueryValueEx(asubkey, name)[0]
... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,237 | chavarera/Cinfo | refs/heads/master | /lib/windows/SystemInfo.py | from lib.windows.common.CommandHandler import CommandHandler
from lib.windows.common.RegistryHandler import RegistryHandler
from lib.windows.common import Utility as utl
from datetime import datetime
import platform
class SystemInfo:
'''
Class Name:SystemInfo
Desciption:this class used to fetch the opera... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,238 | chavarera/Cinfo | refs/heads/master | /lib/windows/common/RegistryHandler.py | try:
import _winreg as reg
except:
import winreg as reg
class RegistryHandler:
def __init__(self,key,path):
self.Hkey=self.getRootKey(key)
self.path=path
self.key = reg.OpenKey(self.Hkey, self.path)
def getRootKey(self,key):
ROOTS={'HCR':reg.HKEY... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,239 | chavarera/Cinfo | refs/heads/master | /linuxUI.py | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'MainUi.ui'
#
# Created by: PyQt5 UI code generator 5.13.2
#
# WARNING! All changes made in this file will be lost!
import os
import pandas as pd
from PyQt5 import QtCore, QtGui, QtWidgets
from lib.linux import get_browsers,get_drives,get_hw... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,240 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_drives.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
from tabulate import tabulate
class get_drives:
'''
********* THIS SCRIPT RETURNS A VARIABLE CONTAINING DISK INFO IN HUMAN READABLE FORMT *********
CLASS get_drives DOCINFO:
get_drives HAVE TWO F... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,241 | chavarera/Cinfo | refs/heads/master | /LinuxInfo.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
import threading
from timeit import default_timer as timer
from tabulate import tabulate
from lib.linux import get_browsers
from lib.linux import get_drives
from lib.linux import get_hw_info
from lib.... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,242 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_startup_list.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
class get_startup_list:
def __init__(self):
'''
__init__ DOCFILE:
__init__ BLOCK CONTAINS INITIALISED VARIABLES FOR LATER USE.
'''
self.data = "" # TO SAVE FETCHED D... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,243 | chavarera/Cinfo | refs/heads/master | /Cinfo.py | import os
if __name__=="__main__":
#check platform type and Run File(if Windows It will Import from WindowsInfo)
if os.name=='nt':
import WindowsInfo
else:
import LinuxInfo
| {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,244 | chavarera/Cinfo | refs/heads/master | /lib/linux/get_ports.py | '''
Author : Deepak Chauhan
GitHub : https://github.com/royaleagle73
Email : 2018PGCACA63@nitjsr.ac.in
'''
import os
import re
class get_ports:
'''
********* THIS SCRIPT RETURNS A LIST OF TUPLE CONTAINING PORTS AND PROTOCOLS OPEN ON USER'S LINUX SYSTEM *********
CLASS get_ports DOCINFO:
get_ports HAVE TWO FUNCT... | {"/lib/windows/NetworkInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/HardwareInfo.py": ["/lib/windows/common/CommandHandler.py", "/lib/windows/common/RegistryHandler.py"], "/lib/windows/ServiceInfo.py": ["/lib/windows/common/CommandHandler.py"], "/lib/windows/MiscInfo.py": ["/lib/windows/common/Comm... |
21,262 | kazi-arafat/custometfeedbackapp | refs/heads/master | /app.py | from flask import Flask,flash,render_template,request
from flask_sqlalchemy import SQLAlchemy
from send_mail import send_email
app = Flask(__name__)
ENV = "prod"
if (ENV == "dev"):
app.debug = True
app.config['SQLALCHEMY_DATABASE_URI'] = 'postgresql://postgres:abc123@localhost/CustomerFeedback'
else:
app.... | {"/app.py": ["/send_mail.py"]} |
21,263 | kazi-arafat/custometfeedbackapp | refs/heads/master | /send_mail.py | import smtplib
from email.mime.text import MIMEText
def send_email(customer, dealer, rating, comments):
port = 587
userid = "40dc44b7a3fe59"
pwd = "b7183feda5fb84"
host = "smtp.mailtrap.io"
to_email = "arafatkazi2448@gmail.com"
from_email = "noReply@example.com"
mail_body = f"<h3>Customer... | {"/app.py": ["/send_mail.py"]} |
21,277 | deekshati/GetADoc-Flask | refs/heads/master | /migrations/versions/cbe32a1e2540_doctor_patients_table.py | """Doctor & Patients table
Revision ID: cbe32a1e2540
Revises:
Create Date: 2020-08-24 19:11:23.284040
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = 'cbe32a1e2540'
down_revision = None
branch_labels = None
depends_on = None
def upgrade():
# ### commands... | {"/getadoc.py": ["/app/models.py"], "/app/routes.py": ["/app/forms.py", "/app/models.py"], "/app/forms.py": ["/app/models.py"]} |
21,278 | deekshati/GetADoc-Flask | refs/heads/master | /getadoc.py | from app import app, db
from app.models import Patient, Doctor, Appointment
@app.shell_context_processor
def make_shell_context():
return {'db': db, 'Patient': Patient, 'Doctor': Doctor, 'Appointment': Appointment} | {"/getadoc.py": ["/app/models.py"], "/app/routes.py": ["/app/forms.py", "/app/models.py"], "/app/forms.py": ["/app/models.py"]} |
21,279 | deekshati/GetADoc-Flask | refs/heads/master | /app/models.py | from app import db, login
from werkzeug.security import generate_password_hash, check_password_hash
from flask_login import UserMixin
from datetime import datetime
@login.user_loader
def load_user(id):
if(id[0] == 'P'):
return Patient.query.get(id)
else:
return Doctor.query.get(id)
class Pati... | {"/getadoc.py": ["/app/models.py"], "/app/routes.py": ["/app/forms.py", "/app/models.py"], "/app/forms.py": ["/app/models.py"]} |
21,280 | deekshati/GetADoc-Flask | refs/heads/master | /app/routes.py | from secrets import token_hex
from flask import render_template, url_for, redirect, flash, request
from app import app, db
from flask_login import current_user, login_user, logout_user, login_required
from app.forms import LoginForm, DoctorRegister, PatientRegister, AppointmentForm, confirmAppointment, rejectAppointmen... | {"/getadoc.py": ["/app/models.py"], "/app/routes.py": ["/app/forms.py", "/app/models.py"], "/app/forms.py": ["/app/models.py"]} |
21,281 | deekshati/GetADoc-Flask | refs/heads/master | /app/forms.py | from flask_wtf import FlaskForm
from wtforms import StringField, PasswordField, BooleanField, SubmitField, SelectField, IntegerField, TextField
from wtforms.fields.html5 import DateField, TimeField, DateTimeField
from wtforms.validators import ValidationError, DataRequired, Email, Length, Optional
from app.models impor... | {"/getadoc.py": ["/app/models.py"], "/app/routes.py": ["/app/forms.py", "/app/models.py"], "/app/forms.py": ["/app/models.py"]} |
21,289 | elidiocampeiz/ArrowFieldTraversal | refs/heads/master | /GraphTraversal.py | import sys
from graph_utils import *
# DFS implementation that solves the Arrow Traversal problem
def dfs_arrows(graph, start, goal):
paths = {}
paths[start] = None
visited = set()
visited.add(start)
stack = []
stack.append(start)
while len(stack) != 0:
node = stack.pop()
if... | {"/GraphTraversal.py": ["/graph_utils.py"]} |
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