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shuishen112/pairwise-rnn
refs/heads/master
{"/run.py": ["/data_helper.py", "/config.py"], "/test.py": ["/data_helper.py", "/config.py"], "/models/__init__.py": ["/models/QA_CNN_pairwise.py"]}
└── ├── config.py ├── data_helper.py ├── main.py ├── models │ ├── QA_CNN_pairwise.py │ ├── __init__.py │ └── my │ └── nn.py ├── run.py └── test.py
/config.py
class Singleton(object): __instance=None def __init__(self): pass def getInstance(self): if Singleton.__instance is None: # Singleton.__instance=object.__new__(cls,*args,**kwd) Singleton.__instance=self.get_test_flag() print("build FLAGS over") ret...
/data_helper.py
#-*- coding:utf-8 -*- import os import numpy as np import tensorflow as tf import string from collections import Counter import pandas as pd from tqdm import tqdm import random from functools import wraps import time import pickle def log_time_delta(func): @wraps(func) def _deco(*args, **kwargs): star...
/main.py
import data_helper import time import datetime import os import tensorflow as tf import numpy as np import evaluation now = int(time.time()) timeArray = time.localtime(now) timeStamp = time.strftime("%Y%m%d%H%M%S", timeArray) timeDay = time.strftime("%Y%m%d", timeArray) print (timeStamp) def main(args): ar...
/models/QA_CNN_pairwise.py
#coding:utf-8 import tensorflow as tf import numpy as np from tensorflow.contrib import rnn import models.blocks as blocks # model_type :apn or qacnn class QA_CNN_extend(object): # def __init__(self,max_input_left,max_input_right,batch_size,vocab_size,embedding_size,filter_sizes,num_filters,hidden_size, # dro...
/models/__init__.py
from .QA_CNN_pairwise import QA_CNN_extend as CNN from .QA_RNN_pairwise import QA_RNN_extend as RNN from .QA_CNN_quantum_pairwise import QA_CNN_extend as QCNN def setup(opt): if opt["model_name"]=="cnn": model=CNN(opt) elif opt["model_name"]=="rnn": model=RNN(opt) elif opt['model_name']=='qcnn': model=QCNN(opt...
/models/my/nn.py
from my.general import flatten, reconstruct, add_wd, exp_mask import numpy as np import tensorflow as tf _BIAS_VARIABLE_NAME = "bias" _WEIGHTS_VARIABLE_NAME = "kernel" def linear(args, output_size, bias, bias_start=0.0, scope=None, squeeze=False, wd=0.0, input_keep_prob=1.0, is_train=None):#, name_w='',...
/run.py
from tensorflow import flags import tensorflow as tf from config import Singleton import data_helper import datetime,os import models import numpy as np import evaluation import sys import logging import time now = int(time.time()) timeArray = time.localtime(now) timeStamp = time.strftime("%Y%m%d%H%M%S", timeArray)...
/test.py
# -*- coding: utf-8 -*- from tensorflow import flags import tensorflow as tf from config import Singleton import data_helper import datetime import os import models import numpy as np import evaluation from data_helper import log_time_delta,getLogger logger=getLogger() args = Singleton().get_rnn_flag() #args...
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Sssssbo/SDCNet
refs/heads/master
"{\"/SDCNet.py\": [\"/model.py\", \"/datasets.py\", \"/misc.py\"], \"/infer_SDCNet.py\": [\"/model.p(...TRUNCATED)
"└── \n ├── SDCNet.py\n ├── count_dataset.py\n ├── create_free.py\n(...TRUNCATED)
/SDCNet.py
"import datetime\nimport os\nimport time\n\nimport torch\nfrom torch import nn\nfrom torch import op(...TRUNCATED)
/count_dataset.py
"import numpy as np\nimport os\n\nimport torch\nfrom PIL import Image\nfrom torch.autograd import Va(...TRUNCATED)
/create_free.py
"import numpy as np\nimport os\n\nimport torch\nfrom PIL import Image\nfrom torch.autograd import Va(...TRUNCATED)
/datasets.py
"import os\nimport os.path\n\nimport torch.utils.data as data\nfrom PIL import Image\n\n\nclass Imag(...TRUNCATED)
/infer_SDCNet.py
"import numpy as np\nimport os\n\nimport torch\nimport torch.nn.functional as F\nfrom PIL import Ima(...TRUNCATED)
/misc.py
"import numpy as np\nimport os\nimport pylab as pl\n\n#import pydensecrf.densecrf as dcrf\n\n\nclass(...TRUNCATED)
/model.py
"import torch\nimport torch.nn.functional as F\nfrom torch import nn\n\nfrom resnext import ResNeXt1(...TRUNCATED)
/model/backbones/resnet.py
"import math\n\nimport torch\nfrom torch import nn\n\n\ndef conv3x3(in_planes, out_planes, stride=1)(...TRUNCATED)
/model/make_model.py
"import torch\nimport torch.nn as nn\nfrom .backbones.resnet import ResNet, Comb_ResNet, Pure_ResNet(...TRUNCATED)
/resnet/__init__.py
from .make_model import ResNet50, ResNet50_BIN, ResNet50_LowIN
/resnet/config.py
resnet50_path = './resnet/resnet50-19c8e357.pth'
/resnet/make_model.py
"from .resnet import ResNet, BasicBlock, Bottleneck\nimport torch\nfrom torch import nn\nfrom .confi(...TRUNCATED)
/resnext/__init__.py
from .resnext101 import ResNeXt101
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riadghorra/whiteboard-oop-project
refs/heads/master
"{\"/src/tools.py\": [\"/src/figures.py\"], \"/src/white_board.py\": [\"/src/figures.py\", \"/src/to(...TRUNCATED)
"└── \n └── src\n ├── client.py\n ├── figures.py\n (...TRUNCATED)
/src/client.py
"import socket\nimport json\nimport sys\nimport math\nfrom white_board import WhiteBoard, binary_to_(...TRUNCATED)
/src/figures.py
"\"\"\"\nModule contenant toutes les figures et opérations de base\n\"\"\"\n\nimport pygame\nimport(...TRUNCATED)
/src/main.py
"from white_board import WhiteBoard\nimport json\n\n'''\nThis file is used to run locally or to debu(...TRUNCATED)
/src/serveur.py
"import socket\nimport sys\nimport time\nfrom threading import Thread\nimport json\n\n'''\nLes deux (...TRUNCATED)
/src/tools.py
"\"\"\"\nModule contenant les differents outils de gestion du tableau\n\"\"\"\nimport pygame\nimport(...TRUNCATED)
/src/white_board.py
"import pygame\nimport pygame.draw\nimport json\nimport sys\nfrom functools import reduce\nimport op(...TRUNCATED)
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pyfaddist/yafcorse
refs/heads/main
"{\"/tests/conftest.py\": [\"/src/yafcorse/__init__.py\"], \"/tests/test_ceate_extensions.py\": [\"/(...TRUNCATED)
"└── \n ├── src\n │ └── yafcorse\n │ └── __init__.py\n (...TRUNCATED)
/src/yafcorse/__init__.py
"import re\nfrom typing import Callable, Iterable\nfrom flask import Flask, Response, request\n\n# Y(...TRUNCATED)
/tests/conftest.py
"import pytest\nfrom flask import Flask\n\nfrom yafcorse import Yafcorse\n\n\n@pytest.fixture()\ndef(...TRUNCATED)
/tests/test_ceate_extensions.py
"from flask.app import Flask\n\nfrom yafcorse import Yafcorse\n\n\ndef test_extension(app: Flask):\n(...TRUNCATED)
/tests/test_default_configuration.py
# def test_no_cors_enabled(): # assert False
/tests/test_origins_function.py
"import pytest\nfrom flask import Flask, Response\nfrom flask.testing import FlaskClient\n\nfrom yaf(...TRUNCATED)
/tests/test_preflight_request.py
"from flask import Response\nfrom flask.testing import FlaskClient\n\n\n# def test_with_origin(clien(...TRUNCATED)
/tests/test_simple_request.py
"from flask import Flask, Response\nfrom flask.testing import FlaskClient\n\n\ndef test_simple_reque(...TRUNCATED)
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ericfourrier/auto-clean
refs/heads/develop
"{\"/test.py\": [\"/autoc/utils/helpers.py\", \"/autoc/outliersdetection.py\", \"/autoc/explorer.py\(...TRUNCATED)
"└── \n ├── autoc\n │ ├── __init__.py\n │ ├── exceptions.py(...TRUNCATED)
/autoc/__init__.py
"__all__ = [\"explorer\", \"naimputer\"]\nfrom .explorer import DataExploration\nfrom .naimputer imp(...TRUNCATED)
/autoc/exceptions.py
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n@author: efourrier\n\nPurpose : File with a(...TRUNCATED)
/autoc/explorer.py
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n@author: efourrier\n\nPurpose : This is a f(...TRUNCATED)
/autoc/naimputer.py
"from autoc.explorer import DataExploration, pd\nfrom autoc.utils.helpers import cserie\nimport seab(...TRUNCATED)
/autoc/outliersdetection.py
"\"\"\"\n@author: efourrier\n\nPurpose : This is a simple experimental class to detect outliers. Thi(...TRUNCATED)
/autoc/preprocess.py
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n@author: efourrier\n\nPurpose : The purpose(...TRUNCATED)
/autoc/utils/corrplot.py
"import seaborn as sns\nimport matplotlib.pyplot as plt\n\n\ndef plot_corrmatrix(df, square=True, li(...TRUNCATED)
/autoc/utils/getdata.py
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\"\"\"\n@author: efourrier\n\nPurpose : Get data fr(...TRUNCATED)
/autoc/utils/helpers.py
"# -*- coding: utf-8 -*-\n\"\"\"\n@author: efourrier\n\nPurpose : Create toolbox functions to use fo(...TRUNCATED)
/setup.py
"from setuptools import setup, find_packages\n\n\ndef readme():\n with open('README.md') as f:\n (...TRUNCATED)
/test.py
"# -*- coding: utf-8 -*-\n\"\"\"\n\n@author: efourrier\n\nPurpose : Automated test suites with unitt(...TRUNCATED)
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thinkAmi-sandbox/AWS_CDK-sample
refs/heads/master
{"/step_functions/app.py": ["/step_functions/step_functions/step_functions_stack.py"]}
"└── \n └── step_functions\n ├── app.py\n └── step_function(...TRUNCATED)
/step_functions/app.py
"#!/usr/bin/env python3\n\nfrom aws_cdk import core\n\nfrom step_functions.step_functions_stack impo(...TRUNCATED)
/step_functions/step_functions/lambda_function/error/lambda_function.py
"import json\n\n\ndef lambda_handler(event, context):\n # {\n # \"resource\": \"arn:aws:lamb(...TRUNCATED)
/step_functions/step_functions/lambda_function/first/lambda_function.py
"import os\nimport boto3\nfrom numpy.random import rand\n\n\ndef lambda_handler(event, context):\n (...TRUNCATED)
/step_functions/step_functions/lambda_function/second/lambda_function.py
"def lambda_handler(event, context):\n if event['parallel_no'] % 2 == 0:\n raise Exception(...TRUNCATED)
/step_functions/step_functions/lambda_function/third/lambda_function.py
"def lambda_handler(event, context):\n if event['parallel_no'] == 1:\n raise Exception('(...TRUNCATED)
/step_functions/step_functions/settings.example.py
AWS_SCIPY_ARN = 'arn:aws:lambda:region:account_id:layer:AWSLambda-Python37-SciPy1x:2'
/step_functions/step_functions/step_functions_stack.py
"import pathlib\n\nfrom aws_cdk import core\nfrom aws_cdk.aws_iam import PolicyStatement, Effect, Ma(...TRUNCATED)
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greenmato/slackline-spots
refs/heads/master
"{\"/spots-api/map/urls.py\": [\"/spots-api/map/api.py\", \"/spots-api/map/views.py\"], \"/spots-api(...TRUNCATED)
"└── \n └── spots-api\n └── map\n ├── api.py\n (...TRUNCATED)
/spots-api/map/api.py
"from abc import ABC, ABCMeta, abstractmethod\nfrom django.forms.models import model_to_dict\nfrom d(...TRUNCATED)
/spots-api/map/forms.py
"from django import forms\nfrom django.forms import ModelForm, Textarea\n\nfrom map.models import Sp(...TRUNCATED)
/spots-api/map/migrations/0001_initial.py
"# Generated by Django 2.0 on 2017-12-17 18:04\n\nfrom django.db import migrations, models\n\n\nclas(...TRUNCATED)
/spots-api/map/migrations/0005_auto_20180305_2131.py
"# Generated by Django 2.0.1 on 2018-03-05 21:31\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/spots-api/map/migrations/0007_auto_20180305_2139.py
"# Generated by Django 2.0.1 on 2018-03-05 21:39\n\nfrom django.db import migrations\n\n\nclass Migr(...TRUNCATED)
/spots-api/map/migrations/0008_auto_20180305_2211.py
"# Generated by Django 2.0.1 on 2018-03-05 22:11\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/spots-api/map/migrations/0009_auto_20180305_2215.py
"# Generated by Django 2.0.1 on 2018-03-05 22:15\n\nfrom django.db import migrations, models\nimport(...TRUNCATED)
/spots-api/map/migrations/0010_auto_20180306_2119.py
"# Generated by Django 2.0.1 on 2018-03-06 21:19\n\nfrom django.db import migrations\n\n\nclass Migr(...TRUNCATED)
/spots-api/map/models.py
"from django.db import models\nfrom django.core.validators import MaxValueValidator, MinValueValidat(...TRUNCATED)
/spots-api/map/urls.py
"from django.urls import path\nfrom django.conf import settings\nfrom django.conf.urls.static import(...TRUNCATED)
/spots-api/map/views.py
"from django.shortcuts import render\nfrom django.views import View\n\nclass MapView(View):\n def(...TRUNCATED)
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katrii/ohsiha
refs/heads/master
{"/ohjelma/views.py": ["/ohjelma/models.py"]}
"└── \n └── ohjelma\n ├── apps.py\n ├── migrations\n (...TRUNCATED)
/ohjelma/apps.py
from django.apps import AppConfig class OhjelmaConfig(AppConfig): name = 'ohjelma'
/ohjelma/migrations/0002_song.py
"# Generated by Django 3.0.2 on 2020-03-13 17:36\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/ohjelma/migrations/0003_song_release_year.py
"# Generated by Django 3.0.2 on 2020-03-15 16:01\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/ohjelma/migrations/0004_track.py
"# Generated by Django 3.0.2 on 2020-03-28 23:19\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/ohjelma/migrations/0005_auto_20200329_1313.py
"# Generated by Django 3.0.2 on 2020-03-29 10:13\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/ohjelma/migrations/0006_auto_20200329_1329.py
"# Generated by Django 3.0.2 on 2020-03-29 10:29\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/ohjelma/migrations/0007_track_track_id.py
"# Generated by Django 3.0.2 on 2020-04-11 18:42\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/ohjelma/migrations/0009_auto_20200411_2211.py
"# Generated by Django 3.0.2 on 2020-04-11 19:11\n\nfrom django.db import migrations, models\n\n\ncl(...TRUNCATED)
/ohjelma/models.py
"from django.db import models\nfrom django.urls import reverse\n\nclass Question(models.Model):\n (...TRUNCATED)
/ohjelma/urls.py
"from django.urls import path\nfrom . import views\n\nurlpatterns = [\n\n path('', views.index, n(...TRUNCATED)
/ohjelma/views.py
"from django.shortcuts import render\nfrom django.http import HttpResponse\nfrom django.views.generi(...TRUNCATED)
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lukasld/Flask-Video-Editor
refs/heads/main
"{\"/app/api/VideoProcessing.py\": [\"/app/api/decorators.py\", \"/app/api/errors.py\"], \"/app/api/(...TRUNCATED)
"└── \n ├── app\n │ ├── __init__.py\n │ ├── api\n │ (...TRUNCATED)
/app/__init__.py
"from flask import Flask\nfrom config import config\nfrom flask_caching import Cache\n\nfrom flask_s(...TRUNCATED)
/app/api/VideoProcessing.py
"from werkzeug.utils import secure_filename\nfrom functools import partial\nimport subprocess as sp\(...TRUNCATED)
/app/api/__init__.py
"from flask import Blueprint\n\napi = Blueprint('videoApi', __name__)\n\nfrom . import videoApi, err(...TRUNCATED)
/app/api/decorators.py
"from flask import request, jsonify\nfrom functools import wraps\n\nfrom .errors import InvalidAPIUs(...TRUNCATED)
/app/api/errors.py
"import sys\nimport traceback\nfrom flask import jsonify, request\n\nfrom . import api\n\nclass Inva(...TRUNCATED)
/app/api/help.py
"from flask import jsonify, request, send_from_directory\nfrom . decorators import parameter_check\n(...TRUNCATED)
/app/api/utils.py
"import cv2\nimport math\nimport string\nimport random\nimport numpy as np\nimport skvideo.io\nfrom (...TRUNCATED)
/app/api/videoApi.py
"import os\nfrom flask import Flask, request, redirect, \\\n url_for, session, json(...TRUNCATED)
/app/docs/__init__.py
"from flask_swagger_ui import get_swaggerui_blueprint\n\n\nswagger_ui = get_swaggerui_blueprint(\n (...TRUNCATED)
/app/main/errors.py
"from flask import redirect, url_for, jsonify\nfrom . import main\n\n@main.app_errorhandler(404)\nde(...TRUNCATED)
/config.py
"import os\nbasedir = os.path.abspath(os.path.dirname(__file__))\n\n\nclass Config:\n\n \"\"\"\n (...TRUNCATED)
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junprog/contrastive-baseline
refs/heads/main
"{\"/linear_eval.py\": [\"/models/create_linear_eval_model.py\", \"/utils/visualizer.py\", \"/datase(...TRUNCATED)
"└── \n ├── datasets\n │ ├── cifar10.py\n │ └── spatial.py\(...TRUNCATED)
/datasets/cifar10.py
"from typing import Callable, Optional\nimport random\n\nfrom PIL import Image\nimport numpy as np\n(...TRUNCATED)
/datasets/spatial.py
"# in : original image\n# out : cropped img1 (anchor)\n# cropped img2 (compete)\n# targ(...TRUNCATED)
/exp.py
"import torch\nimport torchvision\nfrom PIL import Image\nfrom matplotlib import pyplot as plt\nimpo(...TRUNCATED)
/linear_eval.py
"import os\nimport argparse\nimport logging\nimport numpy as np\n\nimport torch\nimport torch.nn as (...TRUNCATED)
/models/cosine_contrastive_loss.py
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F \n\n\ndef D(p, z, version='sim(...TRUNCATED)
/models/create_linear_eval_model.py
"import os\nfrom collections import OrderedDict\n\nimport torch\nimport torch.nn as nn\nimport torch(...TRUNCATED)
/models/l2_contrastive_loss.py
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nclass L2ContrastiveLoss(nn.(...TRUNCATED)
/models/siamese_net.py
"import torch\nimport torch.nn as nn\n\nclass SiameseNetwork(nn.Module):\n def __init__(self, mod(...TRUNCATED)
/models/simple_siamese_net_tmp.py
"import torch\nimport torch.nn as nn\n\nclass projection_MLP(nn.Module):\n def __init__(self, in_(...TRUNCATED)
/train.py
"from utils.contrastive_trainer import CoTrainer\nfrom utils.simsiam_trainer import SimSiamTrainer\n(...TRUNCATED)
/train_val_split.py
"import os\nfrom glob import glob\n\nimport numpy as np\nimport argparse\n\ndef parse_args():\n p(...TRUNCATED)
/utils/contrastive_trainer.py
"import os\nimport sys\nimport time\nimport logging\n\nimport numpy as np\n\nimport torch\nfrom torc(...TRUNCATED)
/utils/helper.py
"import os\nimport numpy as np\nimport torch\n\ndef worker_init_fn(worker_id): (...TRUNCATED)
/utils/simsiam_trainer.py
"import os\nimport sys\nimport time\nimport logging\n\nimport numpy as np\n\nimport torch\nfrom torc(...TRUNCATED)
/utils/visualizer.py
"import os\nimport numpy as np\nfrom PIL import Image\n\nimport torch\n\nimport matplotlib\nmatplotl(...TRUNCATED)
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