repo stringlengths 2 99 | file stringlengths 14 239 | code stringlengths 20 3.99M | file_length int64 20 3.99M | avg_line_length float64 9.73 128 | max_line_length int64 11 86.4k | extension_type stringclasses 1
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ColBERT | ColBERT-master/colbert/ranking/reranking.py | import os
import time
import faiss
import random
import torch
from colbert.utils.runs import Run
from multiprocessing import Pool
from colbert.modeling.inference import ModelInference
from colbert.evaluation.ranking_logger import RankingLogger
from colbert.utils.utils import print_message, batch
from colbert.ranking.... | 2,042 | 31.951613 | 91 | py |
ColBERT | ColBERT-master/colbert/ranking/faiss_index.py | import os
import time
import faiss
import random
import torch
from multiprocessing import Pool
from colbert.modeling.inference import ModelInference
from colbert.utils.utils import print_message, flatten, batch
from colbert.indexing.loaders import load_doclens
class FaissIndex():
def __init__(self, index_path, ... | 4,820 | 38.195122 | 101 | py |
ColBERT | ColBERT-master/colbert/ranking/rankers.py | import torch
from functools import partial
from colbert.ranking.index_part import IndexPart
from colbert.ranking.faiss_index import FaissIndex
from colbert.utils.utils import flatten, zipstar
class Ranker():
def __init__(self, args, inference, faiss_depth=1024):
self.inference = inference
self.f... | 1,520 | 33.568182 | 122 | py |
ColBERT | ColBERT-master/colbert/modeling/inference.py | import torch
from colbert.modeling.colbert import ColBERT
from colbert.modeling.tokenization import QueryTokenizer, DocTokenizer
from colbert.utils.amp import MixedPrecisionManager
from colbert.parameters import DEVICE
class ModelInference():
def __init__(self, colbert: ColBERT, amp=False):
assert colber... | 3,132 | 34.602273 | 117 | py |
ColBERT | ColBERT-master/colbert/modeling/colbert.py | import string
import torch
import torch.nn as nn
from transformers import BertPreTrainedModel, BertModel, BertTokenizerFast
from colbert.parameters import DEVICE
class ColBERT(BertPreTrainedModel):
def __init__(self, config, query_maxlen, doc_maxlen, mask_punctuation, dim=128, similarity_metric='cosine'):
... | 2,458 | 34.637681 | 112 | py |
ColBERT | ColBERT-master/colbert/modeling/tokenization/doc_tokenization.py | import torch
from transformers import BertTokenizerFast
from colbert.modeling.tokenization.utils import _split_into_batches, _sort_by_length
class DocTokenizer():
def __init__(self, doc_maxlen):
self.tok = BertTokenizerFast.from_pretrained('bert-base-uncased')
self.doc_maxlen = doc_maxlen
... | 2,248 | 34.140625 | 104 | py |
ColBERT | ColBERT-master/colbert/modeling/tokenization/query_tokenization.py | import torch
from transformers import BertTokenizerFast
from colbert.modeling.tokenization.utils import _split_into_batches
class QueryTokenizer():
def __init__(self, query_maxlen):
self.tok = BertTokenizerFast.from_pretrained('bert-base-uncased')
self.query_maxlen = query_maxlen
self.Q_... | 2,449 | 36.692308 | 115 | py |
ColBERT | ColBERT-master/colbert/modeling/tokenization/utils.py | import torch
def tensorize_triples(query_tokenizer, doc_tokenizer, queries, positives, negatives, bsize):
assert len(queries) == len(positives) == len(negatives)
assert bsize is None or len(queries) % bsize == 0
N = len(queries)
Q_ids, Q_mask = query_tokenizer.tensorize(queries)
D_ids, D_mask = d... | 1,833 | 34.269231 | 116 | py |
cili | cili-master/make-tsv.py |
"""
Script to produce a TSV file for a release of CILI.
The mappings to the Princeton WordNet generally don't need to be
released regularly as they are unlikely to change and are already
included in WN-LMF releases of the PWN, so this script reduces the
ili.ttl file to a two-column tab-separated-value file containing... | 1,284 | 26.934783 | 70 | py |
cili | cili-master/make-html.py |
"""
Requirements:
- Python 3.6+
- rdflib
Usage:
python3 make-html.py OUTDIR
"""
from typing import Dict
import sys
from pathlib import Path
from rdflib import Graph
from rdflib.namespace import RDF, DC, SKOS, Namespace
if len(sys.argv) != 2:
sys.exit('usage: python3 make-html.py OUTDIR')
OUTDIR = P... | 4,438 | 22.363158 | 105 | py |
gate-teamware | gate-teamware-master/version.py | import json
import yaml
import sys
PACKAGE_JSON_FILE_PATH = "package.json"
DOCS_PACKAGE_JSON_FILE_PATH = "docs/package.json"
CITATION_FILE_PATH = "CITATION.cff"
MASTER_VERSION_FILE = "VERSION"
def check():
"""
Intended for use in CI pipelines, checks versions in files and exits with non-zero exit code if they... | 2,693 | 30.325581 | 117 | py |
gate-teamware | gate-teamware-master/manage.py | """Django's command-line utility for administrative tasks."""
import os
import sys
def main():
"""Run administrative tasks."""
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'teamware.settings.base')
try:
from django.core.management import execute_from_command_line
except ImportError as exc:
... | 669 | 28.130435 | 77 | py |
gate-teamware | gate-teamware-master/backend/views.py | import tempfile
import json
import math
import csv
from zipfile import ZipFile
from django.conf import settings
from django.http import StreamingHttpResponse, HttpResponse
from django.shortcuts import render
from django.views import View
from backend.models import Project, Document, DocumentType
class MainView(View)... | 7,294 | 34.585366 | 164 | py |
gate-teamware | gate-teamware-master/backend/signals.py | from django.db.models.signals import pre_delete
from django.dispatch import receiver
from backend.models import ServiceUser, Annotation
| 137 | 26.6 | 50 | py |
gate-teamware | gate-teamware-master/backend/errors.py | class AuthError(PermissionError):
pass
| 43 | 13.666667 | 33 | py |
gate-teamware | gate-teamware-master/backend/rpcserver.py | import json
import logging
import inspect
from json.decoder import JSONDecodeError
from django.http import JsonResponse, HttpRequest
from django.views import View
from backend.errors import AuthError
log = logging.getLogger(__name__)
REGISTERED_RPC_METHODS = {}
PARSE_ERROR = -32700
INVALID_REQUEST = -32600
METHOD_... | 7,035 | 32.826923 | 127 | py |
gate-teamware | gate-teamware-master/backend/rpc.py | import secrets
import logging
import datetime
import json
import os
from urllib.parse import urljoin
from django.conf import settings
from django.contrib.auth import authenticate, get_user_model, login as djlogin, logout as djlogout
from django.contrib.auth.decorators import permission_required
from django.contrib.adm... | 36,144 | 33.754808 | 147 | py |
gate-teamware | gate-teamware-master/backend/admin.py | from django.contrib import admin
from django.contrib.auth import get_user_model
from .models import Project, Document, Annotation
# Register your models here.
@admin.register(get_user_model())
class UserAdmin(admin.ModelAdmin):
pass
@admin.register(Project)
class ProjectAdmin(admin.ModelAdmin):
pass
@admin.r... | 466 | 20.227273 | 49 | py |
gate-teamware | gate-teamware-master/backend/models.py | import math
import uuid
from django.conf import settings
import logging
import django
from datetime import timedelta
from django.contrib.auth.models import AbstractUser
from django.contrib.auth import get_user_model
from django.core.exceptions import ObjectDoesNotExist
from django.db import models
from django.utils im... | 50,946 | 40.931687 | 138 | py |
gate-teamware | gate-teamware-master/backend/apps.py | from django.apps import AppConfig
import logging
log = logging.getLogger(__name__)
class BackendConfig(AppConfig):
default_auto_field = 'django.db.models.BigAutoField'
name = 'backend'
def ready(self):
# This needs to be imported in order to
# pick up all the registered rpc methods
... | 343 | 20.5 | 56 | py |
gate-teamware | gate-teamware-master/backend/migrations/0020a_training_score_not_null.py | from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('backend', '0020_auto_20220330_2021'),
]
operations = [
migrations.AlterField(
model_name='annotatorproject',
name='training_score',
field=models.FloatFie... | 353 | 18.666667 | 47 | py |
gate-teamware | gate-teamware-master/backend/management/commands/check_create_superuser.py | import sys, os
from django.contrib.auth import get_user_model
from django.core.management.base import BaseCommand, CommandError
class Command(BaseCommand):
help = "If no superusers in database, create one from credentials supplied in environment variables"
def handle(self, *args, **options):
User = ... | 1,211 | 35.727273 | 114 | py |
gate-teamware | gate-teamware-master/backend/management/commands/build_api_docs.py | import json
from django.core.management.base import BaseCommand, CommandError
from django.template.loader import render_to_string
from backend.rpcserver import JSONRPCEndpoint
class Command(BaseCommand):
help = "Generate a JSON file listing API endpoints"
def add_arguments(self, parser):
parser.add_a... | 788 | 24.451613 | 70 | py |
gate-teamware | gate-teamware-master/backend/utils/telemetry.py | import json
import logging
from threading import Thread
import requests
from urllib.parse import urljoin
from django.conf import settings
log = logging.getLogger(__name__)
class TelemetrySender:
def __init__(self, status: str, data: dict) -> None:
self.url = urljoin(settings.TELEMETRY_BASE_URL, settings.T... | 1,165 | 34.333333 | 113 | py |
gate-teamware | gate-teamware-master/backend/utils/misc.py | import string
import random
def get_value_from_key_path(obj_dict, key_path, delimiter="."):
"""
Gets value from a dictionary following a delimited key_path. Does not work for path with array elements.
:returns: None if path does not exist.
"""
if key_path is None:
return None
key_path_... | 2,038 | 29.893939 | 110 | py |
gate-teamware | gate-teamware-master/backend/utils/serialize.py | import logging
import json
from datetime import datetime
from django.db import models
from django.db.models import Model, ManyToOneRel, ManyToManyRel, ForeignKey
from django.utils import timezone
from backend.models import Project
log = logging.getLogger(__name__)
def dsl_val(attr_name, obj, data):
"""
Ins... | 6,068 | 35.125 | 155 | py |
gate-teamware | gate-teamware-master/teamware/wsgi.py | """
WSGI config for teamware project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/3.2/howto/deployment/wsgi/
"""
import os
from django.core.wsgi import get_wsgi_application
os.environ.setdefault('DJANGO_SETT... | 404 | 22.823529 | 79 | py |
gate-teamware | gate-teamware-master/teamware/urls.py | """teamware URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-base... | 1,121 | 39.071429 | 182 | py |
gate-teamware | gate-teamware-master/teamware/asgi.py | """
ASGI config for teamware project.
It exposes the ASGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/3.2/howto/deployment/asgi/
"""
import os
from django.core.asgi import get_asgi_application
os.environ.setdefault('DJANGO_SETT... | 393 | 22.176471 | 78 | py |
gate-teamware | gate-teamware-master/teamware/settings/docker-integration.py | """
Settings for integration testing
Uses a clean database every time
"""
from .deployment import *
DATABASES['default']['NAME'] = "teamware_integration_db"
# Turn off e-mail activation for testing
ACTIVATION_WITH_EMAIL = False
TELEMETRY_ON = False
FRONTEND_DEV_SERVER_USE = False
| 285 | 18.066667 | 56 | py |
gate-teamware | gate-teamware-master/teamware/settings/deployment.py | import logging
import sys
import os
from .base import *
# Enable csrf in production
MIDDLEWARE.append(
'django.middleware.csrf.CsrfViewMiddleware'
)
DEBUG = (os.environ.get('DJANGO_DEBUG', "false").lower() in ['true', 'yes', 'on', '1'])
if 'DJANGO_ALLOWED_HOSTS' in os.environ:
# This looks a bit horrible, but th... | 1,550 | 25.741379 | 117 | py |
gate-teamware | gate-teamware-master/teamware/settings/integration.py | """
Settings for local integration testing
Uses a clean database every time
"""
from .base import *
DATABASES['default']['NAME'] = "teamware_integration_db"
# Turn off e-mail activation for testing
ACTIVATION_WITH_EMAIL = False
TELEMETRY_ON = False
| 253 | 17.142857 | 56 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/setup.py | import os
import os.path as osp
import shutil
import subprocess
import sys
import warnings
from setuptools import find_packages, setup
def readme():
with open('README.md', encoding='utf-8') as f:
content = f.read()
return content
version_file = 'mmedit/version.py'
def get_git_hash():
def _min... | 8,503 | 34.286307 | 125 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/evaluate_comp1k.py | import argparse
import os.path as osp
import re
import mmcv
import numpy as np
from mmedit.core.evaluation import connectivity, gradient_error, mse, sad
from mmedit.utils import modify_args
def evaluate_one(args):
"""Function to evaluate one sample of data.
Args:
args (tuple): Information needed to... | 5,073 | 36.585185 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/get_flops.py | import argparse
from mmcv import Config
from mmcv.cnn.utils import get_model_complexity_info
from mmedit.models import build_model
def parse_args():
parser = argparse.ArgumentParser(description='Train a editor')
parser.add_argument('config', help='train config file path')
parser.add_argument(
'-... | 1,956 | 29.578125 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/onnx2tensorrt.py | import argparse
import os
import os.path as osp
import warnings
from typing import Iterable, Optional
import cv2
import mmcv
import numpy as np
import onnxruntime as ort
import torch
from mmcv.ops import get_onnxruntime_op_path
from mmcv.tensorrt import (TRTWrapper, is_tensorrt_plugin_loaded, onnx2trt,
... | 9,445 | 34.115242 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/publish_model.py | import argparse
import subprocess
import torch
from packaging import version
def parse_args():
parser = argparse.ArgumentParser(
description='Process a checkpoint to be published')
parser.add_argument('in_file', help='input checkpoint filename')
parser.add_argument('out_file', help='output checkp... | 1,256 | 29.658537 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/pytorch2onnx.py | import argparse
import warnings
import cv2
import mmcv
import numpy as np
import onnx
import onnxruntime as rt
import torch
from mmcv.onnx import register_extra_symbolics
from mmcv.runner import load_checkpoint
from mmedit.datasets.pipelines import Compose
from mmedit.models import build_model
def pytorch2onnx(mode... | 7,975 | 35.420091 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/train.py | import argparse
import copy
import os
import os.path as osp
import time
import mmcv
import torch
import torch.distributed as dist
from mmcv import Config, DictAction
from mmcv.runner import init_dist
from mmedit import __version__
from mmedit.apis import init_random_seed, set_random_seed, train_model
from mmedit.data... | 5,738 | 32.758824 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/deployment/mmedit_handler.py | import os
import random
import string
from io import BytesIO
import PIL.Image as Image
import torch
from ts.torch_handler.base_handler import BaseHandler
from mmedit.apis import init_model, restoration_inference
from mmedit.core import tensor2img
class MMEditHandler(BaseHandler):
def initialize(self, context):... | 2,099 | 34 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/tools/deployment/mmedit2torchserve.py | from argparse import ArgumentParser, Namespace
from pathlib import Path
from tempfile import TemporaryDirectory
import mmcv
try:
from model_archiver.model_packaging import package_model
from model_archiver.model_packaging_utils import ModelExportUtils
except ImportError:
package_model = None
def mmedit2... | 3,725 | 32.567568 | 76 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/.dev_scripts/github/update_model_index.py |
# This tool is used to update model-index.yml which is required by MIM, and
# will be automatically called as a pre-commit hook. The updating will be
# triggered if any change of model information (.md files in configs/) has been
# detected before a commit.
import glob
import os
import posixpath as osp # Even on win... | 11,096 | 33.039877 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/demo/restoration_video_demo.py | import argparse
import os
import cv2
import mmcv
import numpy as np
import torch
from mmedit.apis import init_model, restoration_video_inference
from mmedit.core import tensor2img
from mmedit.utils import modify_args
VIDEO_EXTENSIONS = ('.mp4', '.mov')
def parse_args():
modify_args()
parser = argparse.Argu... | 2,938 | 32.781609 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/version.py |
__version__ = '0.14.0'
def parse_version_info(version_str):
ver_info = []
for x in version_str.split('.'):
if x.isdigit():
ver_info.append(int(x))
elif x.find('rc') != -1:
patch_version = x.split('rc')
ver_info.append(int(patch_version[0]))
ver_... | 482 | 24.421053 | 52 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/restoration_face_inference.py | import numpy as np
import torch
from mmcv.parallel import collate, scatter
from mmedit.datasets.pipelines import Compose
try:
from facexlib.utils.face_restoration_helper import FaceRestoreHelper
has_facexlib = True
except ImportError:
has_facexlib = False
def restoration_face_inference(model, img, upsca... | 3,069 | 33.494382 | 77 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/generation_inference.py | import numpy as np
import torch
from mmcv.parallel import collate, scatter
from mmedit.core import tensor2img
from mmedit.datasets.pipelines import Compose
def generation_inference(model, img, img_unpaired=None):
"""Inference image with the model.
Args:
model (nn.Module): The loaded model.
i... | 2,229 | 34.967742 | 74 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/inpainting_inference.py | import torch
from mmcv.parallel import collate, scatter
from mmedit.datasets.pipelines import Compose
def inpainting_inference(model, masked_img, mask):
"""Inference image with the model.
Args:
model (nn.Module): The loaded model.
masked_img (str): File path of image with mask.
mask ... | 1,546 | 29.94 | 70 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/restoration_inference.py | import torch
from mmcv.parallel import collate, scatter
from mmedit.datasets.pipelines import Compose
def restoration_inference(model, img, ref=None):
"""Inference image with the model.
Args:
model (nn.Module): The loaded model.
img (str): File path of input image.
ref (str | None): ... | 1,606 | 33.191489 | 72 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/matting_inference.py | import mmcv
import torch
from mmcv.parallel import collate, scatter
from mmcv.runner import load_checkpoint
from mmedit.datasets.pipelines import Compose
from mmedit.models import build_model
def init_model(config, checkpoint=None, device='cuda:0'):
"""Initialize a model from config file.
Args:
conf... | 2,659 | 33.545455 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/video_interpolation_inference.py | import math
import os
import os.path as osp
import cv2
import mmcv
import numpy as np
import torch
from mmcv.fileio import FileClient
from mmcv.parallel import collate
from mmedit.datasets.pipelines import Compose
VIDEO_EXTENSIONS = ('.mp4', '.mov', '.avi')
FILE_CLIENT = FileClient('disk')
def read_image(filepath)... | 6,978 | 33.043902 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/train.py | import os
import os.path as osp
import random
import warnings
import mmcv
import numpy as np
import torch
import torch.distributed as dist
from mmcv.parallel import MMDataParallel
from mmcv.runner import HOOKS, IterBasedRunner, get_dist_info
from mmcv.utils import build_from_cfg
from mmedit.core import DistEvalIterHo... | 12,897 | 34.629834 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/apis/restoration_video_inference.py | import glob
import os.path as osp
import re
from functools import reduce
import mmcv
import numpy as np
import torch
from mmedit.datasets.pipelines import Compose
VIDEO_EXTENSIONS = ('.mp4', '.mov')
def pad_sequence(data, window_size):
padding = window_size // 2
data = torch.cat([
data[:, 1 + padd... | 4,669 | 34.923077 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/distributed_wrapper.py | import torch
import torch.nn as nn
from mmcv.parallel import MODULE_WRAPPERS, MMDistributedDataParallel
from mmcv.parallel.scatter_gather import scatter_kwargs
from torch.cuda._utils import _get_device_index
@MODULE_WRAPPERS.register_module()
class DistributedDataParallelWrapper(nn.Module):
"""A DistributedDataPa... | 5,720 | 39.864286 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/misc.py | import math
import numpy as np
import torch
from torchvision.utils import make_grid
def tensor2img(tensor, out_type=np.uint8, min_max=(0, 1)):
"""Convert torch Tensors into image numpy arrays.
After clamping to (min, max), image values will be normalized to [0, 1].
For different tensor shapes, this fun... | 2,898 | 37.653333 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/mask.py | import math
import cv2
import mmcv
import numpy as np
from PIL import Image, ImageDraw
def random_bbox(img_shape, max_bbox_shape, max_bbox_delta=40, min_margin=20):
"""Generate a random bbox for the mask on a given image.
In our implementation, the max value cannot be obtained since we use
`np.random.ra... | 12,928 | 39.785489 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/scheduler/lr_updater.py | from mmcv.runner import HOOKS, LrUpdaterHook
@HOOKS.register_module()
class LinearLrUpdaterHook(LrUpdaterHook):
"""Linear learning rate scheduler for image generation.
In the beginning, the learning rate is 'base_lr' defined in mmcv.
We give a target learning rate 'target_lr' and a start point 'start'
... | 1,880 | 34.490566 | 77 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/evaluation/metric_utils.py | import cv2
import numpy as np
def gaussian(x, sigma):
"""Gaussian function.
Args:
x (array_like): The independent variable.
sigma (float): Standard deviation of the gaussian function.
Return:
ndarray or scalar: Gaussian value of `x`.
"""
return np.exp(-x**2 / (2 * sigma**... | 2,273 | 26.731707 | 75 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/evaluation/eval_hooks.py | import os.path as osp
from mmcv.runner import Hook
from torch.utils.data import DataLoader
class EvalIterHook(Hook):
"""Non-Distributed evaluation hook for iteration-based runner.
This hook will regularly perform evaluation in a given interval when
performing in non-distributed environment.
Args:
... | 3,766 | 33.87963 | 75 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/evaluation/metrics.py | import math
import cv2
import mmcv
import numpy as np
from scipy.ndimage import convolve
from scipy.special import gamma
from mmedit.datasets.pipelines.matlab_like_resize import MATLABLikeResize
from .metric_utils import gauss_gradient
def sad(alpha, trimap, pred_alpha):
if alpha.ndim != 2 or trimap.ndim != 2 o... | 20,691 | 38.413333 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/export/wrappers.py | import os.path as osp
import warnings
import numpy as np
import onnxruntime as ort
import torch
from torch import nn
from mmedit.models import BaseMattor, BasicRestorer, build_model
def inference_with_session(sess, io_binding, output_names, input_tensor):
device_type = input_tensor.device.type
device_id = i... | 4,767 | 34.318519 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/hooks/visualization.py | import os.path as osp
import mmcv
import torch
from mmcv.runner import HOOKS, Hook
from mmcv.runner.dist_utils import master_only
from torchvision.utils import save_image
@HOOKS.register_module()
class VisualizationHook(Hook):
"""Visualization hook.
In this hook, we use the official api `save_image` in torc... | 3,050 | 34.894118 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/hooks/ema.py | import warnings
from copy import deepcopy
from functools import partial
import mmcv
import torch
from mmcv.parallel import is_module_wrapper
from mmcv.runner import HOOKS, Hook
@HOOKS.register_module()
class ExponentialMovingAverageHook(Hook):
"""Exponential Moving Average Hook.
Exponential moving average i... | 4,719 | 40.403509 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/utils/dist_utils.py | import numpy as np
import torch
import torch.distributed as dist
from mmcv.runner import get_dist_info
def sync_random_seed(seed=None, device='cuda'):
"""Make sure different ranks share the same seed.
All workers must call this function, otherwise it will deadlock.
This method is generally used in `Distri... | 1,108 | 29.805556 | 73 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/core/optimizer/builder.py | from mmcv.runner import build_optimizer
def build_optimizers(model, cfgs):
"""Build multiple optimizers from configs.
If `cfgs` contains several dicts for optimizers, then a dict for each
constructed optimizers will be returned.
If `cfgs` only contains one optimizer config, the constructed optimizer
... | 1,679 | 27.474576 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/base.py | from abc import ABCMeta, abstractmethod
from collections import OrderedDict
import torch
import torch.nn as nn
class BaseModel(nn.Module, metaclass=ABCMeta):
"""Base model.
All models should subclass it.
All subclass should overwrite:
``init_weights``, supporting to initialize models.
... | 2,948 | 26.820755 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/registry.py | from mmcv.cnn import MODELS as MMCV_MODELS
from mmcv.utils import Registry
MODELS = Registry('model', parent=MMCV_MODELS)
BACKBONES = MODELS
COMPONENTS = MODELS
LOSSES = MODELS
| 226 | 24.222222 | 47 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/builder.py | import torch.nn as nn
from mmcv import build_from_cfg
from .registry import BACKBONES, COMPONENTS, LOSSES, MODELS
def build(cfg, registry, default_args=None):
"""Build module function.
Args:
cfg (dict): Configuration for building modules.
registry (obj): ``registry`` object.
default_... | 1,482 | 23.311475 | 75 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/restorers/basicvsr.py | import numbers
import os.path as osp
import mmcv
import numpy as np
import torch
from mmedit.core import tensor2img
from ..registry import MODELS
from .basic_restorer import BasicRestorer
@MODELS.register_module()
class BasicVSR(BasicRestorer):
"""BasicVSR model for video super-resolution.
Note that this m... | 8,430 | 36.471111 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/restorers/basic_restorer.py | import numbers
import os.path as osp
import mmcv
from mmcv.runner import auto_fp16
from mmedit.core import psnr, ssim, tensor2img
from ..base import BaseModel
from ..builder import build_backbone, build_loss
from ..registry import MODELS
@MODELS.register_module()
class BasicRestorer(BaseModel):
"""Basic model f... | 6,558 | 30.085308 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/flow_warp.py | import torch
import torch.nn.functional as F
def flow_warp(x,
flow,
interpolation='bilinear',
padding_mode='zeros',
align_corners=True):
"""Warp an image or a feature map with optical flow.
Args:
x (Tensor): Tensor with size (n, c, h, w).
... | 1,781 | 36.125 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/aspp.py | import torch
from mmcv.cnn import ConvModule
from torch import nn
from torch.nn import functional as F
from .separable_conv_module import DepthwiseSeparableConvModule
class ASPPPooling(nn.Sequential):
def __init__(self, in_channels, out_channels, conv_cfg, norm_cfg, act_cfg):
super().__init__(
... | 3,861 | 29.650794 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/sr_backbone_utils.py | import torch.nn as nn
from mmcv.cnn import constant_init, kaiming_init
from mmcv.utils.parrots_wrapper import _BatchNorm
def default_init_weights(module, scale=1):
"""Initialize network weights.
Args:
modules (nn.Module): Modules to be initialized.
scale (float): Scale initialized weights, es... | 2,919 | 28.795918 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/model_utils.py | import numpy as np
import torch
def set_requires_grad(nets, requires_grad=False):
"""Set requires_grad for all the networks.
Args:
nets (nn.Module | list[nn.Module]): A list of networks or a single
network.
requires_grad (bool): Whether the networks require gradients or not
""... | 4,502 | 31.868613 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/separable_conv_module.py | import torch.nn as nn
from mmcv.cnn import ConvModule
class DepthwiseSeparableConvModule(nn.Module):
"""Depthwise separable convolution module.
See https://arxiv.org/pdf/1704.04861.pdf for details.
This module can replace a ConvModule with the conv block replaced by two
conv block: depthwise conv bl... | 3,907 | 38.877551 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/linear_module.py | import torch.nn as nn
from mmcv.cnn import build_activation_layer, kaiming_init
class LinearModule(nn.Module):
"""A linear block that contains linear/norm/activation layers.
For low level vision, we add spectral norm and padding layer.
Args:
in_features (int): Same as nn.Linear.
out_feat... | 3,204 | 34.611111 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/contextual_attention.py | from functools import partial
import torch
import torch.nn as nn
import torch.nn.functional as F
class ContextualAttentionModule(nn.Module):
"""Contexture attention module.
The details of this module can be found in:
Generative Image Inpainting with Contextual Attention
Args:
unfold_raw_ker... | 15,214 | 39.039474 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/gated_conv_module.py | import copy
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, build_activation_layer
class SimpleGatedConvModule(nn.Module):
"""Simple Gated Convolutional Module.
This module is a simple gated convolutional module. The detailed formula
is:
.. math::
y = \\phi(conv1(x)) * \... | 2,423 | 32.205479 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/conv.py | from mmcv.cnn import CONV_LAYERS
from torch import nn
CONV_LAYERS.register_module('Deconv', module=nn.ConvTranspose2d)
# TODO: octave conv
| 188 | 26 | 64 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/downsample.py | def pixel_unshuffle(x, scale):
"""Down-sample by pixel unshuffle.
Args:
x (Tensor): Input tensor.
scale (int): Scale factor.
Returns:
Tensor: Output tensor.
"""
b, c, h, w = x.shape
if h % scale != 0 or w % scale != 0:
raise AssertionError(
f'Invali... | 613 | 25.695652 | 69 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/generation_model_utils.py | import numpy as np
import torch
import torch.nn as nn
from mmcv.cnn import ConvModule, kaiming_init, normal_init, xavier_init
from torch.nn import init
def generation_init_weights(module, init_type='normal', init_gain=0.02):
"""Default initialization of network weights for image generation.
By default, we us... | 10,699 | 34.430464 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/ensemble.py | import torch
import torch.nn as nn
class SpatialTemporalEnsemble(nn.Module):
""" Apply spatial and temporal ensemble and compute outputs
Args:
is_temporal_ensemble (bool, optional): Whether to apply ensemble
temporally. If True, the sequence will also be flipped temporally.
If... | 3,541 | 32.415094 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/upsample.py | import torch.nn as nn
import torch.nn.functional as F
from .sr_backbone_utils import default_init_weights
class PixelShufflePack(nn.Module):
""" Pixel Shuffle upsample layer.
Args:
in_channels (int): Number of input channels.
out_channels (int): Number of output channels.
scale_facto... | 1,517 | 28.192308 | 76 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/img_normalize.py | import torch
import torch.nn as nn
class ImgNormalize(nn.Conv2d):
"""Normalize images with the given mean and std value.
Based on Conv2d layer, can work in GPU.
Args:
pixel_range (float): Pixel range of feature.
img_mean (Tuple[float]): Image mean of each channel.
img_std (Tuple[... | 1,063 | 31.242424 | 68 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/mask_conv_module.py | from mmcv.cnn import ConvModule
class MaskConvModule(ConvModule):
"""Mask convolution module.
This is a simple wrapper for mask convolution like: 'partial conv'.
Convolutions in this module always need a mask as extra input.
Args:
in_channels (int): Same as nn.Conv2d.
out_channels (i... | 3,649 | 40.011236 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/common/partial_conv.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import CONV_LAYERS
@CONV_LAYERS.register_module(name='PConv')
class PartialConv2d(nn.Conv2d):
"""Implementation for partial convolution.
Image Inpainting for Irregular Holes Using Partial Convolutions
[htt... | 3,605 | 34.009709 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/losses/pixelwise_loss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from ..registry import LOSSES
from .utils import masked_loss
_reduction_modes = ['none', 'mean', 'sum']
@masked_loss
def l1_loss(pred, target):
"""L1 loss.
Args:
pred (Tensor): Prediction Tensor with shape (n, c, h, w).
targ... | 7,356 | 32.13964 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/losses/utils.py | import functools
import torch.nn.functional as F
def reduce_loss(loss, reduction):
"""Reduce loss as specified.
Args:
loss (Tensor): Elementwise loss tensor.
reduction (str): Options are "none", "mean" and "sum".
Returns:
Tensor: Reduced loss tensor.
"""
reduction_enum =... | 3,743 | 31.275862 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/losses/gan_loss.py | import torch
import torch.autograd as autograd
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.functional import conv2d
from ..registry import LOSSES
@LOSSES.register_module()
class GANLoss(nn.Module):
"""Define GAN loss.
Args:
gan_type (str): Support 'vanilla', 'lsgan', 'wgan', ... | 11,506 | 32.353623 | 86 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/losses/perceptual_loss.py | import torch
import torch.nn as nn
import torchvision.models.vgg as vgg
from mmcv.runner import load_checkpoint
from torch.nn import functional as F
from mmedit.utils import get_root_logger
from ..registry import LOSSES
class PerceptualVGG(nn.Module):
"""VGG network used in calculating perceptual loss.
In t... | 10,350 | 34.940972 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/backbones/sr_backbones/basicvsr_pp.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import constant_init
from mmcv.ops import ModulatedDeformConv2d, modulated_deform_conv2d
from mmcv.runner import load_checkpoint
from mmedit.models.backbones.sr_backbones.basicvsr_net import (
ResidualBlocksWithInputConv, SPyNet)
from... | 16,773 | 37.56092 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/models/backbones/sr_backbones/basicvsr_net.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from mmcv.cnn import ConvModule
from mmcv.runner import load_checkpoint
from mmedit.models.common import (PixelShufflePack, ResidualBlockNoBN,
flow_warp, make_layer)
from mmedit.models.registry import BACKBONES
from mm... | 14,148 | 32.608076 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/sr_vimeo90k_multiple_gt_dataset.py | import os
import os.path as osp
from .base_sr_dataset import BaseSRDataset
from .registry import DATASETS
@DATASETS.register_module()
class SRVimeo90KMultipleGTDataset(BaseSRDataset):
"""Vimeo90K dataset for video super resolution for recurrent networks.
The dataset loads several LQ (Low-Quality) frames and... | 2,608 | 30.059524 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/sr_folder_multiple_gt_dataset.py | import glob
import os
import os.path as osp
import mmcv
from .base_sr_dataset import BaseSRDataset
from .registry import DATASETS
@DATASETS.register_module()
class SRFolderMultipleGTDataset(BaseSRDataset):
"""General dataset for video super resolution, used for recurrent networks.
The dataset loads several... | 4,220 | 33.884298 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/registry.py | from mmcv.utils import Registry
DATASETS = Registry('dataset')
PIPELINES = Registry('pipeline')
| 145 | 23.333333 | 47 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/base_dataset.py | import copy
from abc import ABCMeta, abstractmethod
from torch.utils.data import Dataset
from .pipelines import Compose
class BaseDataset(Dataset, metaclass=ABCMeta):
"""Base class for datasets.
All datasets should subclass it.
All subclasses should overwrite:
``load_annotations``, supporting ... | 2,006 | 24.405063 | 73 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/dataset_wrappers.py | from .registry import DATASETS
@DATASETS.register_module()
class RepeatDataset:
"""A wrapper of repeated dataset.
The length of repeated dataset will be `times` larger than the original
dataset. This is useful when the data loading time is long but the dataset
is small. Using RepeatDataset can reduce... | 1,034 | 24.875 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/sr_reds_multiple_gt_dataset.py | from .base_sr_dataset import BaseSRDataset
from .registry import DATASETS
@DATASETS.register_module()
class SRREDSMultipleGTDataset(BaseSRDataset):
"""REDS dataset for video super resolution for recurrent networks.
The dataset loads several LQ (Low-Quality) frames and GT (Ground-Truth)
frames. Then it ap... | 3,194 | 36.151163 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/base_sr_dataset.py | import copy
import os.path as osp
from collections import defaultdict
from pathlib import Path
from mmcv import scandir
from .base_dataset import BaseDataset
IMG_EXTENSIONS = ('.jpg', '.JPG', '.jpeg', '.JPEG', '.png', '.PNG', '.ppm',
'.PPM', '.bmp', '.BMP', '.tif', '.TIF', '.tiff', '.TIFF')
class... | 2,779 | 30.590909 | 79 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/builder.py | import copy
import platform
import random
from functools import partial
import numpy as np
import torch
from mmcv.parallel import collate
from mmcv.runner import get_dist_info
from mmcv.utils import build_from_cfg
from packaging import version
from torch.utils.data import ConcatDataset, DataLoader
from .dataset_wrapp... | 6,177 | 32.945055 | 78 | py |
BasicVSR_PlusPlus | BasicVSR_PlusPlus-master/mmedit/datasets/samplers/distributed_sampler.py | from __future__ import division
import math
import torch
from torch.utils.data import DistributedSampler as _DistributedSampler
from mmedit.core.utils import sync_random_seed
class DistributedSampler(_DistributedSampler):
"""DistributedSampler inheriting from `torch.utils.data.DistributedSampler`.
In pytor... | 2,892 | 39.180556 | 80 | py |
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