repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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Instaboost | Instaboost-master/detectron/lib/roi_data/loader.py | import math
import numpy as np
import numpy.random as npr
import torch
import torch.utils.data as data
import torch.utils.data.sampler as torch_sampler
from torch.utils.data.dataloader import default_collate
from torch._six import int_classes as _int_classes
from core.config import cfg
from roi_data.minibatch import ... | 11,119 | 41.605364 | 108 | py |
AuxiLearn | AuxiLearn-master/auxilearn/implicit_diff.py | import torch
class Hypergrad:
"""Implicit differentiation for auxiliary parameters.
This implementation follows the Algs. in "Optimizing Millions of Hyperparameters by Implicit Differentiation"
(https://arxiv.org/pdf/1911.02590.pdf), with small differences.
"""
def __init__(self, learning_rate=.... | 2,338 | 29.776316 | 113 | py |
AuxiLearn | AuxiLearn-master/auxilearn/optim.py | from torch.nn.utils.clip_grad import clip_grad_norm_
from auxilearn.implicit_diff import Hypergrad
class MetaOptimizer:
def __init__(self, meta_optimizer, hpo_lr, truncate_iter=3, max_grad_norm=10):
"""Auxiliary parameters optimizer wrapper
:param meta_optimizer: optimizer for auxiliary paramet... | 1,706 | 30.036364 | 85 | py |
AuxiLearn | AuxiLearn-master/auxilearn/hypernet.py | from abc import abstractmethod
from torch import nn
from torch.nn.utils import weight_norm
class HyperNet(nn.Module):
"""This module is responsible for taking the losses from all tasks and return a single loss term.
We can think of this as our learnable loss criterion
"""
def __init__(self, main_tas... | 15,037 | 32.050549 | 118 | py |
AuxiLearn | AuxiLearn-master/experiments/utils.py | import logging
import random
import numpy as np
import torch
import argparse
def set_logger():
logging.basicConfig(
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
level=logging.INFO
)
def set_seed(seed):
"""for reproducibility
:param seed:
:return:
"""
np.... | 1,406 | 24.581818 | 95 | py |
AuxiLearn | AuxiLearn-master/experiments/weight_methods.py | from abc import abstractmethod
import numpy as np
import torch
from torch import nn
from experiments.utils import detach_to_numpy
class WeightingMethod:
@abstractmethod
def backward(self, losses, *args, **kwargs):
pass
class GradCosine(WeightingMethod):
"""Implementation of the unweighted ver... | 7,806 | 30.228 | 116 | py |
AuxiLearn | AuxiLearn-master/experiments/oxford_pet/data.py | import pandas as pd
import numpy as np
import os
import shutil
from pathlib import Path
from torch.utils.data import Subset
from torchvision.datasets import ImageFolder
from torchvision import models, transforms
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.utils.rand... | 6,879 | 39.470588 | 106 | py |
AuxiLearn | AuxiLearn-master/experiments/oxford_pet/models.py | import torch
import numpy as np
from torch import nn
import torchvision.models as models
class ResNet18(nn.Module):
def __init__(self, psi, pretrained=False, progress=True, num_classes=37, **kwargs):
super().__init__()
self.model = models.resnet18(pretrained=pretrained, progress=progress, **kwargs... | 2,083 | 31.061538 | 101 | py |
AuxiLearn | AuxiLearn-master/experiments/oxford_pet/trainer.py | import argparse
import logging
from io import BytesIO
import copy
import numpy as np
import torch
import torch.optim as optim
from sklearn.metrics import classification_report
import torch.nn.functional as F
from torchsummary import summary
from tqdm import trange
from torch.utils.data import DataLoader
from experimen... | 15,085 | 37.58312 | 123 | py |
AuxiLearn | AuxiLearn-master/experiments/nyuv2/trainer_cnn.py | import argparse
from collections import defaultdict
import logging
import copy
import numpy as np
import torch
import torch.optim as optim
from torch.nn import functional as F
from tqdm import trange
from torchsummary import summary
from experiments.nyuv2.data import nyu_dataloaders
from experiments.nyuv2.metrics imp... | 8,751 | 28.076412 | 117 | py |
AuxiLearn | AuxiLearn-master/experiments/nyuv2/model.py | import torch
import torch.nn as nn
from torch.nn import functional as F
class SegNetSplit(nn.Module):
"""Modification of the code in: https://github.com/lorenmt/mtan
SegNet with hard-parameter sharing
"""
def __init__(self, logsigma=True):
"""
:param logsigma: for uncert weighting
... | 5,534 | 45.512605 | 115 | py |
AuxiLearn | AuxiLearn-master/experiments/nyuv2/data.py | import fnmatch
import os
import json
import numpy as np
import torch
from torch.utils.data import Dataset
class NYUv2(Dataset):
"""Code from: https://github.com/lorenmt/mtan/blob/master/im2im_pred/create_dataset.py
The (pre-processed) data is available here: https://www.dropbox.com/s/p2nn02wijg7peiy/nyuv2.z... | 3,742 | 32.419643 | 113 | py |
AuxiLearn | AuxiLearn-master/experiments/nyuv2/trainer_baseline.py | import argparse
from collections import defaultdict
import logging
import copy
import numpy as np
import torch
import torch.optim as optim
from torch.nn import functional as F
from tqdm import trange
from torchsummary import summary
from experiments.nyuv2.data import nyu_dataloaders
from experiments.nyuv2.metrics imp... | 8,179 | 28.96337 | 118 | py |
AuxiLearn | AuxiLearn-master/experiments/nyuv2/metrics.py | import numpy as np
import torch
from sklearn.metrics import (accuracy_score, classification_report,
confusion_matrix, multilabel_confusion_matrix)
from sklearn.preprocessing import MultiLabelBinarizer
"""Source: https://github.com/lorenmt/mtan"""
def main_task_accuracy(pred, target, main... | 4,744 | 37.266129 | 115 | py |
AuxiLearn | AuxiLearn-master/experiments/nyuv2/trainer.py | import argparse
from collections import defaultdict
import logging
import copy
import numpy as np
import torch
import torch.optim as optim
from torch.nn import functional as F
from tqdm import trange
from torchsummary import summary
from experiments.nyuv2.data import nyu_dataloaders
from experiments.nyuv2.metrics imp... | 9,088 | 28.8 | 117 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/layers.py | # file: layers.py
# brief: A number of objects to wrap caffe layers for conversion
# author: Andrea Vedaldi
from collections import OrderedDict
from math import floor, ceil
from operator import mul
import numpy as np
from numpy import array
import scipy
import scipy.io
import scipy.misc
import copy
import collections
... | 43,934 | 36.519214 | 156 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/import-caffe.py | #! /usr/bin/python
# file: import-caffe.py
# brief: Caffe importer for DagNN and SimpleNN
# author: Karel Lenc and Andrea Vedaldi
# Requires Google Protobuf for Python and SciPy
import sys
import os
import argparse
import code
import re
import numpy as np
from math import floor, ceil
import numpy
from numpy import ar... | 33,156 | 36.213244 | 114 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/proto/caffe_0115_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
from google.protobuf import descriptor
from google.protobuf import message
from google.protobuf import reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = descriptor.FileDescriptor(
name='caffe.proto',
... | 148,708 | 41.163028 | 17,413 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/proto/caffe_fastrcnn_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: caffe_fastrcnn.proto
from google.protobuf.internal import enum_type_wrapper
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protob... | 194,370 | 42.777252 | 22,943 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/proto/caffe_6e3916_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
from google.protobuf import descriptor
from google.protobuf import message
from google.protobuf import reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = descriptor.FileDescriptor(
name='caffe_6e3916.pro... | 218,004 | 42.349572 | 26,073 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/proto/caffe_old_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
from google.protobuf import descriptor
from google.protobuf import message
from google.protobuf import reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = descriptor.FileDescriptor(
name='caffe-old.proto'... | 39,691 | 43.348603 | 4,364 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/proto/caffe_b590f1d_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
from google.protobuf import descriptor
from google.protobuf import message
from google.protobuf import reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = descriptor.FileDescriptor(
name='caffe_b590f1d.pr... | 232,112 | 42.264306 | 27,801 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/proto/caffe_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
from google.protobuf import descriptor
from google.protobuf import message
from google.protobuf import reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = descriptor.FileDescriptor(
name='caffe.proto',
... | 91,458 | 42.407214 | 10,562 | py |
Eigenvectors-of-Proximal-Operators-and-Neural-Networks | Eigenvectors-of-Proximal-Operators-and-Neural-Networks-main/code_FFDnet/FFDnet_code/matconvnet-1.0-beta25/utils/proto/vgg_caffe_pb2.py | # Generated by the protocol buffer compiler. DO NOT EDIT!
from google.protobuf import descriptor
from google.protobuf import message
from google.protobuf import reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = descriptor.FileDescriptor(
name='vgg_caffe.proto'... | 44,873 | 42.865103 | 4,761 | py |
ADFNet | ADFNet-main/ADFNet_Real/losses.py | import torch
import torch.nn as nn
import torch.nn.functional as F
def tv_loss(x, beta = 0.5, reg_coeff = 5):
'''Calculates TV loss for an image `x`.
Args:
x: image, torch.Variable of torch.Tensor
beta: See https://arxiv.org/abs/1412.0035 (fig. 2) to see effect of `beta`
'''
... | 1,618 | 29.54717 | 93 | py |
ADFNet | ADFNet-main/ADFNet_Real/test_sidd_val_png.py | import argparse
import torch.nn as nn
import os
import torch
import numpy as np
import utils
import scipy.io as sio
from dataloaders.data_rgb import get_validation_data
from networks.adfnet import Net
from torch.utils.data import DataLoader
from skimage import img_as_ubyte
from tqdm import tqdm
'''
从文件夹中读取数据集，测试后... | 3,850 | 36.754902 | 117 | py |
ADFNet | ADFNet-main/ADFNet_Real/test_dnd_png.py | import numpy as np
import os
import argparse
import torch.nn as nn
import torch
import utils
from tqdm import tqdm
import scipy.io as sio
from skimage import img_as_ubyte
from networks.adfnet import Net
from torch.utils.data import DataLoader
from dataloaders.data_rgb import get_test_data
from utils.bundle_submissions ... | 3,219 | 40.818182 | 146 | py |
ADFNet | ADFNet-main/ADFNet_Real/train_denoising.py | import os
import torch
import random
import time
import utils
import torch.nn as nn
import torch.optim as optim
import numpy as np
from thop import profile
from torch.utils.data import DataLoader
from dataloaders.data_rgb import get_training_data, get_validation_data
from networks.adfnet import Net
from losses import ... | 7,499 | 37.461538 | 131 | py |
ADFNet | ADFNet-main/ADFNet_Real/test_sidd_benchmark_mat.py | import numpy as np
import os
import argparse
import scipy.io as sio
import torch
import torch.nn as nn
import utils
from tqdm import tqdm
from skimage import img_as_ubyte
from networks.adfnet import Net
parser = argparse.ArgumentParser(description='RGB denoising evaluation on SIDD benchmark dataset')
parser.add_argum... | 2,953 | 37.363636 | 133 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/adfnet.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import sys
import os
sys.path.append(os.pardir)
from networks.dcn.modules.modulated_deform_conv import ModulatedDeformConvPack as DCN
def make_model(args):
return Net()
# 促进特征全方位的融合
class Attention(nn.Module):
def __init__(self):
supe... | 10,737 | 34.674419 | 131 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/test.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import time
import torch
import torch.nn as nn
from torch.autograd import gradcheck
from modules.deform_conv import DeformConv, _DeformConv, DeformConvPack
from modules.modulated_deform_c... | 21,977 | 33.775316 | 154 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/setup.py | #!/usr/bin/env python
import os
import glob
import torch
from torch.utils.cpp_extension import CUDA_HOME
from torch.utils.cpp_extension import CppExtension
from torch.utils.cpp_extension import CUDAExtension
from setuptools import find_packages
from setuptools import setup
requirements = ["torch", "torchvision"]
... | 2,028 | 28.838235 | 73 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/functions/deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,398 | 41.087719 | 82 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/functions/deform_psroi_pooling_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,654 | 39.846154 | 85 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/functions/modulated_deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,484 | 42.596491 | 83 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/modules/deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.deform_conv_func import DeformConvFunction
class DeformCon... | 4,282 | 41.83 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/modules/deform_psroi_pooling.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn.modules.utils import _pair
from functions.deform_psroi_pooling_func import DeformRoIPoolingFunction
class DeformRoIPooling(nn.... | 5,586 | 41.648855 | 72 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/modules/modulated_deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import logging
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.modulated_deform_conv_func import ModulatedD... | 7,545 | 44.185629 | 147 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.7/functions/deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,398 | 41.087719 | 82 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.7/functions/deform_psroi_pooling_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,654 | 39.846154 | 85 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.7/functions/modulated_deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,484 | 42.596491 | 83 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.7/modules/deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.deform_conv_func import DeformConvFunction
class DeformCon... | 4,282 | 41.83 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.7/modules/deform_psroi_pooling.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn.modules.utils import _pair
from functions.deform_psroi_pooling_func import DeformRoIPoolingFunction
class DeformRoIPooling(nn.... | 5,586 | 41.648855 | 72 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.7/modules/modulated_deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import logging
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.modulated_deform_conv_func import ModulatedD... | 7,199 | 42.902439 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.6/functions/deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,398 | 41.087719 | 82 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.6/functions/deform_psroi_pooling_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,654 | 39.846154 | 85 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.6/functions/modulated_deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,484 | 42.596491 | 83 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.6/modules/deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.deform_conv_func import DeformConvFunction
class DeformCon... | 4,282 | 41.83 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.6/modules/deform_psroi_pooling.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn.modules.utils import _pair
from functions.deform_psroi_pooling_func import DeformRoIPoolingFunction
class DeformRoIPooling(nn.... | 5,586 | 41.648855 | 72 | py |
ADFNet | ADFNet-main/ADFNet_Real/networks/dcn/build/lib.linux-x86_64-3.6/modules/modulated_deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import logging
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.modulated_deform_conv_func import ModulatedD... | 7,545 | 44.185629 | 147 | py |
ADFNet | ADFNet-main/ADFNet_Real/utils/dataset_utils.py | import torch
class Augment_RGB_torch:
def __init__(self):
pass
def transform0(self, torch_tensor):
return torch_tensor
def transform1(self, torch_tensor):
torch_tensor = torch.rot90(torch_tensor, k=1, dims=[-1,-2])
return torch_tensor
def transform2(self, torch_tensor... | 1,632 | 33.744681 | 91 | py |
ADFNet | ADFNet-main/ADFNet_Real/utils/image_utils.py | import numpy as np
import pickle
import cv2
import math
import torch
def is_numpy_file(filename):
return any(filename.endswith(extension) for extension in [".npy"])
def is_image_file(filename):
return any(filename.endswith(extension) for extension in [".jpg"])
def is_png_file(filename):
return any(fil... | 3,699 | 25.618705 | 89 | py |
ADFNet | ADFNet-main/ADFNet_Real/utils/model_utils.py | import torch
import os
from collections import OrderedDict
def freeze(model):
for p in model.parameters():
p.requires_grad = False
def unfreeze(model):
for p in model.parameters():
p.requires_grad = True
def is_frozen(model):
x = [p.requires_grad for p in model.parameters()]
return... | 5,392 | 29.642045 | 94 | py |
ADFNet | ADFNet-main/ADFNet_Real/utils/antialias.py | # Copyright (c) 2019, Adobe Inc. All rights reserved.
#
# This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike
# 4.0 International Public License. To view a copy of this license, visit
# https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.
######## https://github.com/adobe/a... | 4,580 | 35.648 | 143 | py |
ADFNet | ADFNet-main/ADFNet_Real/pytorch-gradual-warmup-lr/setup.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import setuptools
_VERSION = '0.3'
REQUIRED_PACKAGES = [
]
DEPENDENCY_LINKS = [
]
setuptools.setup(
name='warmup_scheduler',
version=_VERSION,
description='Gradually Warm-up LR Scheduler for Pyt... | 578 | 21.269231 | 64 | py |
ADFNet | ADFNet-main/ADFNet_Real/pytorch-gradual-warmup-lr/warmup_scheduler/run.py | import torch
from torch.optim.lr_scheduler import StepLR, ExponentialLR
from torch.optim.sgd import SGD
from warmup_scheduler import GradualWarmupScheduler
if __name__ == '__main__':
model = [torch.nn.Parameter(torch.randn(2, 2, requires_grad=True))]
optim = SGD(model, 0.1)
# scheduler_warmup is chained... | 817 | 31.72 | 115 | py |
ADFNet | ADFNet-main/ADFNet_Real/pytorch-gradual-warmup-lr/warmup_scheduler/scheduler.py | from torch.optim.lr_scheduler import _LRScheduler
from torch.optim.lr_scheduler import ReduceLROnPlateau
class GradualWarmupScheduler(_LRScheduler):
""" Gradually warm-up(increasing) learning rate in optimizer.
Proposed in 'Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour'.
Args:
optimi... | 3,069 | 46.96875 | 152 | py |
ADFNet | ADFNet-main/ADFNet_Real/pytorch-gradual-warmup-lr/build/lib/warmup_scheduler/run.py | import torch
from torch.optim.lr_scheduler import StepLR, ExponentialLR
from torch.optim.sgd import SGD
from warmup_scheduler import GradualWarmupScheduler
if __name__ == '__main__':
model = [torch.nn.Parameter(torch.randn(2, 2, requires_grad=True))]
optim = SGD(model, 0.1)
# scheduler_warmup is chained... | 817 | 31.72 | 115 | py |
ADFNet | ADFNet-main/ADFNet_Real/pytorch-gradual-warmup-lr/build/lib/warmup_scheduler/scheduler.py | from torch.optim.lr_scheduler import _LRScheduler
from torch.optim.lr_scheduler import ReduceLROnPlateau
class GradualWarmupScheduler(_LRScheduler):
""" Gradually warm-up(increasing) learning rate in optimizer.
Proposed in 'Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour'.
Args:
optimi... | 3,069 | 46.96875 | 152 | py |
ADFNet | ADFNet-main/ADFNet_Gray/main.py | import torch
import random
import numpy as np
import utility
import data
import model
import loss
from option import args
from trainer import Trainer
def print_network(net):
num_params = 0
for param in net.parameters():
num_params += param.numel()
# print(net)
# print('Total number of parameter... | 1,239 | 21.962963 | 74 | py |
ADFNet | ADFNet-main/ADFNet_Gray/test.py | import argparse
import glob
import os
import torch
import cv2
import numpy as np
import time
import torch.nn as nn
from option import args
from torch.autograd import Variable
from utils import logger, batch_PSNR_SSIM_v1, forward_chop
from skimage import img_as_ubyte
from model.adfnet import Net
torch.manual_seed(args... | 4,168 | 37.601852 | 121 | py |
ADFNet | ADFNet-main/ADFNet_Gray/utility.py | import os
import math
import time
import datetime
from functools import reduce
from collections import OrderedDict
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
# import scipy.misc as misc
import torch
import torch.optim as optim
import torch.optim.lr_scheduler as lrs
imp... | 9,505 | 32.95 | 155 | py |
ADFNet | ADFNet-main/ADFNet_Gray/dataloader.py | import sys
import threading
import queue
import random
import collections
import torch
import torch.multiprocessing as multiprocessing
from torch._C import _set_worker_signal_handlers, _update_worker_pids, \
_remove_worker_pids, _error_if_any_worker_fails
from torch.utils.data.dataloader import DataLoader
from to... | 5,271 | 34.621622 | 111 | py |
ADFNet | ADFNet-main/ADFNet_Gray/utils.py | import math
import cv2
import torch
import numpy as np
from skimage import img_as_ubyte
from skimage.measure.simple_metrics import compare_psnr
import logging
import os
import os.path as osp
def logger(name, filepath):
dir_path = osp.dirname(filepath)
if not osp.exists(dir_path):
os.mkdir(dir_path)
... | 8,328 | 33.27572 | 122 | py |
ADFNet | ADFNet-main/ADFNet_Gray/trainer.py | import os
import math
from decimal import Decimal
import numpy as np
import utility
import torch
from torch.autograd import Variable
from tqdm import tqdm
class Trainer():
def __init__(self, args, loader, my_model, my_loss, ckp):
self.args = args
self.scale = args.scale
self.ckp = ckp
... | 7,022 | 39.595376 | 189 | py |
ADFNet | ADFNet-main/ADFNet_Gray/loss/adversarial.py | import utility
from model import common
from loss import discriminator
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.autograd import Variable
class Adversarial(nn.Module):
def __init__(self, args, gan_type):
super(Adversarial, self).__init__()
... | 3,320 | 36.738636 | 78 | py |
ADFNet | ADFNet-main/ADFNet_Gray/loss/discriminator.py | from model import common
import torch.nn as nn
class Discriminator(nn.Module):
def __init__(self, args, gan_type='GAN'):
super(Discriminator, self).__init__()
in_channels = 3
out_channels = 64
depth = 7
#bn = not gan_type == 'WGAN_GP'
bn = True
act = nn.Lea... | 1,287 | 27 | 77 | py |
ADFNet | ADFNet-main/ADFNet_Gray/loss/vgg.py | from model import common
import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.models as models
from torch.autograd import Variable
class VGG(nn.Module):
def __init__(self, conv_index, rgb_range=1):
super(VGG, self).__init__()
vgg_features = models.vgg19(pretrained=... | 1,093 | 28.567568 | 75 | py |
ADFNet | ADFNet-main/ADFNet_Gray/loss/__init__.py | import os
from importlib import import_module
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class Loss(nn.modules.loss._Loss):
def __init__(self, args, ckp):
super(Loss, self).__init__()
... | 4,833 | 31.884354 | 80 | py |
ADFNet | ADFNet-main/ADFNet_Gray/data/srdata.py | import os
import numpy as np
import imageio
import torch
import torch.utils.data as data
import cv2
from data import common
'''
只输入HQ 图像,LQ图像直接在HQ图像上加入噪声
'''
class SRData(data.Dataset):
def __init__(self, args, train=True, benchmark=False):
self.args = args
self.train = train
self.split = '... | 2,854 | 27.55 | 68 | py |
ADFNet | ADFNet-main/ADFNet_Gray/data/myimage.py | import os
from data import common
import imageio
import torch.utils.data as data
# 测试的时候输入HQ图片，直接进行测试PSNR和SSIM的值
class MyImage(data.Dataset):
def __init__(self, args, train=False):
self.args = args
self.name = 'MyImage'
self.scale = args.scale
self.idx_scale = 0
self.train =... | 1,290 | 29.023256 | 70 | py |
ADFNet | ADFNet-main/ADFNet_Gray/data/demo.py | import os
from data import common
import scipy.misc as misc
import torch.utils.data as data
class Demo(data.Dataset):
def __init__(self, args, train=False):
self.args = args
self.name = 'Demo'
self.scale = args.scale
self.idx_scale = 0
self.train = False
self.benchm... | 1,014 | 27.194444 | 75 | py |
ADFNet | ADFNet-main/ADFNet_Gray/data/common.py | import random
import numpy as np
import skimage.io as sio
import skimage.color as sc
import torch
from torchvision import transforms
def get_patch(img_tar, patch_size):
h, w = img_tar.shape[:2]
x = random.randrange(0, w - patch_size + 1)
y = random.randrange(0, h - patch_size + 1)
img_tar = img_tar... | 1,574 | 24 | 69 | py |
ADFNet | ADFNet-main/ADFNet_Gray/data/__init__.py | from importlib import import_module
from dataloader import MSDataLoader
from torch.utils.data.dataloader import default_collate
class Data:
def __init__(self, args):
kwargs = {}
if not args.cpu:
kwargs['collate_fn'] = default_collate
kwargs['pin_memory'] = True
else... | 1,658 | 31.529412 | 78 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/adfnet.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import sys
import os
sys.path.append(os.pardir)
from model.dcn.modules.modulated_deform_conv import ModulatedDeformConvPack as DCN
def make_model(args):
return Net()
class Attention(nn.Module):
def __init__(self):
super(Attention, sel... | 10,696 | 34.656667 | 131 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/__init__.py | import os
import numpy as np
import torch
import torch.nn as nn
from importlib import import_module
class Model(nn.Module):
def __init__(self, args, ckp):
super(Model, self).__init__()
print('Making model...')
self.scale = args.scale
self.idx_scale = 0
self.self_ensemble =... | 7,241 | 34.326829 | 97 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/test.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import time
import torch
import torch.nn as nn
from torch.autograd import gradcheck
from modules.deform_conv import DeformConv, _DeformConv, DeformConvPack
from modules.modulated_deform_c... | 21,977 | 33.775316 | 154 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/setup.py | #!/usr/bin/env python
import os
import glob
import torch
from torch.utils.cpp_extension import CUDA_HOME
from torch.utils.cpp_extension import CppExtension
from torch.utils.cpp_extension import CUDAExtension
from setuptools import find_packages
from setuptools import setup
requirements = ["torch", "torchvision"]
... | 2,028 | 28.838235 | 73 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/functions/deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,398 | 41.087719 | 82 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/functions/deform_psroi_pooling_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,654 | 39.846154 | 85 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/functions/modulated_deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,484 | 42.596491 | 83 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/modules/deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.deform_conv_func import DeformConvFunction
class DeformCon... | 4,282 | 41.83 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/modules/deform_psroi_pooling.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn.modules.utils import _pair
from functions.deform_psroi_pooling_func import DeformRoIPoolingFunction
class DeformRoIPooling(nn.... | 5,586 | 41.648855 | 72 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/modules/modulated_deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import logging
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.modulated_deform_conv_func import ModulatedD... | 7,545 | 44.185629 | 147 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.7/functions/deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,398 | 41.087719 | 82 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.7/functions/deform_psroi_pooling_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,654 | 39.846154 | 85 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.7/functions/modulated_deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,484 | 42.596491 | 83 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.7/modules/deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.deform_conv_func import DeformConvFunction
class DeformCon... | 4,282 | 41.83 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.7/modules/deform_psroi_pooling.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn.modules.utils import _pair
from functions.deform_psroi_pooling_func import DeformRoIPoolingFunction
class DeformRoIPooling(nn.... | 5,586 | 41.648855 | 72 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.7/modules/modulated_deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import logging
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.modulated_deform_conv_func import ModulatedD... | 7,199 | 42.902439 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.6/functions/deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,398 | 41.087719 | 82 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.6/functions/deform_psroi_pooling_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,654 | 39.846154 | 85 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.6/functions/modulated_deform_conv_func.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import math
import torch
from torch import nn
from torch.autograd import Function
from torch.nn.modules.utils import _pair
from torch.autograd.function import once_differentiable
import D... | 2,484 | 42.596491 | 83 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.6/modules/deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.deform_conv_func import DeformConvFunction
class DeformCon... | 4,282 | 41.83 | 119 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.6/modules/deform_psroi_pooling.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import torch
import math
from torch import nn
from torch.nn.modules.utils import _pair
from functions.deform_psroi_pooling_func import DeformRoIPoolingFunction
class DeformRoIPooling(nn.... | 5,586 | 41.648855 | 72 | py |
ADFNet | ADFNet-main/ADFNet_Gray/model/dcn/build/lib.linux-x86_64-3.6/modules/modulated_deform_conv.py | #!/usr/bin/env python
from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
import logging
import torch
import math
from torch import nn
from torch.nn import init
from torch.nn.modules.utils import _pair
from functions.modulated_deform_conv_func import ModulatedD... | 7,545 | 44.185629 | 147 | py |
ADFNet | ADFNet-main/ADFNet_RGB/main.py | import torch
import random
import numpy as np
import utility
import data
import model
import loss
from option import args
from trainer import Trainer
def print_network(net):
num_params = 0
for param in net.parameters():
num_params += param.numel()
# print(net)
# print('Total number of paramete... | 1,221 | 22.960784 | 76 | py |
ADFNet | ADFNet-main/ADFNet_RGB/test.py | import torch.nn.functional as F
import argparse
import glob
import os
import torch
import cv2
import numpy as np
from skimage import img_as_ubyte
from torch.autograd import Variable
import torch.nn as nn
from utils import logger, batch_PSNR_SSIM_v1, forward_chop
from model.adfnet import Net
parser = argparse.Argument... | 4,568 | 37.394958 | 126 | py |
ADFNet | ADFNet-main/ADFNet_RGB/utility.py | import os
import math
import time
import datetime
from functools import reduce
from collections import OrderedDict
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
# import scipy.misc as misc
import torch
import torch.optim as optim
import torch.optim.lr_scheduler as lrs
imp... | 9,508 | 33.082437 | 155 | py |
ADFNet | ADFNet-main/ADFNet_RGB/dataloader.py | import sys
import threading
import queue
import random
import collections
import torch
import torch.multiprocessing as multiprocessing
from torch._C import _set_worker_signal_handlers, _update_worker_pids, \
_remove_worker_pids, _error_if_any_worker_fails
from torch.utils.data.dataloader import DataLoader
from to... | 5,271 | 34.621622 | 111 | py |
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