repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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EDGY | EDGY-master/Training/VQ-VAE/Preprocessing/preprocess.py | import hydra
from hydra import utils
from pathlib import Path
import librosa
import scipy
import json
import numpy as np
from multiprocessing import cpu_count
from concurrent.futures import ProcessPoolExecutor
from functools import partial
from tqdm import tqdm
def preemphasis(x, preemph):
return scipy.signal.lfi... | 3,174 | 35.918605 | 99 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/incremental_train_and_eval_AMR_LF.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 8,384 | 45.071429 | 121 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/compute_confusion_matrix.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 3,725 | 43.357143 | 122 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/incremental_train_and_eval_MS.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 5,759 | 41.666667 | 107 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/incremental_train_and_eval.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 5,014 | 41.5 | 107 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/compute_accuracy.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 3,097 | 40.306667 | 116 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/__init__.py | #!/usr/bin/env python
# coding=utf-8
# for incremental train and eval
| 70 | 16.75 | 32 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/compute_features.py | #!/usr/bin/env python
# coding=utf-8
#!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import... | 1,503 | 33.181818 | 99 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/incremental_train_and_eval_LF.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 5,489 | 39.970149 | 107 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/utils_incremental/incremental_train_and_eval_MR_LF.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 8,171 | 44.149171 | 107 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/gen_imagenet_subset.py | #!/usr/bin/env python
# coding=utf-8
import argparse
import os
import random
import shutil
import time
import warnings
import numpy as np
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import t... | 1,499 | 26.777778 | 79 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/resnet.py | import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152']
model_urls = {
'resnet18': 'https://download.pytorch.org/models/resnet18-5c106cde.pth',
'resnet34': 'https://download.pytorch.org/models/r... | 6,582 | 29.906103 | 90 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/utils_pytorch.py | #!/usr/bin/env python
# coding=utf-8
from __future__ import print_function, division
import torch
import torch.nn as nn
import torch.nn.init as init
from collections import OrderedDict
import numpy as np
import os
import os.path as osp
import sys
import time
import math
import subprocess
try:
import cPickle as pi... | 4,102 | 26.172185 | 96 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/eval_cumul_acc.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 6,830 | 45.469388 | 128 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/class_incremental_imagenet.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 22,015 | 52.307506 | 132 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/modified_resnet.py | import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
import modified_linear
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False)
class BasicBloc... | 3,850 | 32.198276 | 88 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/cbf_class_incremental_cosine_imagenet.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 47,336 | 60.08 | 136 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/class_incremental_cosine_imagenet.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 30,418 | 53.809009 | 132 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/gen_resized_imagenet.py | #!/usr/bin/env python
# coding=utf-8
import argparse
import os
import random
import shutil
import time
import warnings
import numpy as np
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import t... | 1,507 | 28 | 75 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/modified_linear.py | import math
import torch
from torch.nn.parameter import Parameter
from torch.nn import functional as F
from torch.nn import Module
class CosineLinear(Module):
def __init__(self, in_features, out_features, sigma=True):
super(CosineLinear, self).__init__()
self.in_features = in_features
self... | 2,235 | 36.898305 | 78 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/utils_imagenet/train_and_eval.py | import argparse
import os
import shutil
import time
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torchvision.transforms as transforms
import torchvi... | 2,629 | 30.309524 | 75 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/utils_imagenet/__init__.py | #!/usr/bin/env python
# coding=utf-8
# for incremental-class train and eval
| 76 | 18.25 | 38 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/utils_imagenet/utils_dataset.py | import argparse
import os
import shutil
import time
import numpy as np
#split trainset.imgs
def split_images_labels(imgs):
images = []
labels = []
for item in imgs:
images.append(item[0])
labels.append(item[1])
return np.array(images), np.array(labels)
#merge into trainset.imgs
def me... | 576 | 19.607143 | 45 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/imagenet-class-incremental/utils_imagenet/utils_train.py | import argparse
import os
import shutil
import time
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.distributed as dist
import torch.optim
import torch.utils.data
import torch.utils.data.distributed
import torchvision.transforms as transforms
import torchvi... | 2,897 | 29.505263 | 78 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/cifar100-class-incremental/utils_pytorch.py | #!/usr/bin/env python
# coding=utf-8
from __future__ import print_function, division
import torch
import torch.nn as nn
import torch.nn.init as init
from collections import OrderedDict
import numpy as np
import os
import os.path as osp
import sys
import time
import math
import subprocess
try:
import cPickle as pi... | 4,102 | 26.172185 | 96 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/cifar100-class-incremental/eval_cumul_acc.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 5,687 | 43.4375 | 128 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/cifar100-class-incremental/class_incremental_cifar100.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 18,765 | 51.565826 | 130 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/cifar100-class-incremental/resnet_cifar.py | import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, stride=stride,
padding=1, bias=False)
class BasicBlock(nn.Module):
expans... | 4,525 | 29.375839 | 90 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/cifar100-class-incremental/modified_resnet_cifar.py | #remove ReLU in the last layer, and use cosine layer to replace nn.Linear
import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
import modified_linear
def conv3x3(in_planes, out_planes, stride=1):
"""3x3 convolution with padding"""
return nn.Conv2d(in_planes, out_planes, kernel_size=3, st... | 3,716 | 31.893805 | 87 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/cifar100-class-incremental/class_incremental_cosine_cifar100.py | #!/usr/bin/env python
# coding=utf-8
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.optim import lr_scheduler
import torchvision
from torchvision import datasets, models, transforms
from torch.autograd import Variable
import numpy as np
import time
import os
im... | 26,967 | 53.370968 | 131 | py |
CVPR19_Incremental_Learning | CVPR19_Incremental_Learning-master/cifar100-class-incremental/modified_linear.py | import math
import torch
from torch.nn.parameter import Parameter
from torch.nn import functional as F
from torch.nn import Module
class CosineLinear(Module):
def __init__(self, in_features, out_features, sigma=True):
super(CosineLinear, self).__init__()
self.in_features = in_features
self... | 2,235 | 36.898305 | 78 | py |
BarchartReverseEngineering | BarchartReverseEngineering-master/generate_random_bar_chart.py | #!/usr/bin/env python
# coding: utf-8
# In[1]:
import os
import matplotlib
matplotlib.use("Agg")
import random
import string
import itertools
import argparse
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import font_manager
from matplotlib import cm
from tqdm import tqdm
# In[2]:
### random ... | 14,987 | 35.556098 | 117 | py |
TRSSL | TRSSL-main/train.py | import argparse
import os
import shutil
import time
import random
import math
import numpy as np
from datetime import datetime
from tqdm import tqdm
import torch
import torch.backends.cudnn as cudnn
import torch.optim as optim
import torch.utils.data as data
import torch.nn.functional as F
from utils.utils import Bar... | 19,121 | 40.934211 | 183 | py |
TRSSL | TRSSL-main/models/build_model.py | import torch
def build_model(args, ema=False):
if args.dataset in ['cifar10', 'cifar100']:
from . import resnet_cifar as models
elif args.dataset == 'tinyimagenet':
from . import resnet_tinyimagenet as models
else:
from . import resnet as models
if args.arch == 'resnet18':
... | 692 | 24.666667 | 55 | py |
TRSSL | TRSSL-main/models/resnet.py | import torch
from torch import Tensor
import torch.nn as nn
# from .._internally_replaced_utils import load_state_dict_from_url
from typing import Type, Any, Callable, Union, List, Optional
import torch.nn.functional as F
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152', 'r... | 15,539 | 38.846154 | 111 | py |
TRSSL | TRSSL-main/models/resnet_tinyimagenet.py | """
This code is based on the Torchvision repository, which was licensed under the BSD 3-Clause.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, in_planes, planes, stride=1, is_last=False):
super(BasicBlock, self).__... | 5,141 | 37.088889 | 104 | py |
TRSSL | TRSSL-main/models/resnet_cifar.py | """
This code is based on the Torchvision repository, which was licensed under the BSD 3-Clause.
"""
import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicBlock(nn.Module):
expansion = 1
def __init__(self, in_planes, planes, stride=1, is_last=False):
super(BasicBlock, self).__... | 5,073 | 36.865672 | 104 | py |
TRSSL | TRSSL-main/datasets/datasets.py | import numpy as np
from PIL import Image, ImageFilter, ImageOps
import random
from torchvision import datasets, transforms
import torch
import pickle
import os
import math
# normalization parameters
cifar10_mean, cifar10_std = (0.4914, 0.4822, 0.4465), (0.2471, 0.2435, 0.2616)
cifar100_mean, cifar100_std = (0.5071, 0... | 29,457 | 41.203438 | 214 | py |
TRSSL | TRSSL-main/utils/utils.py | import os
import torch
import numpy as np
import random
from progress.bar import Bar as Bar
import torch.nn.functional as F
import shutil
import matplotlib.pyplot as plt
def accuracy(output, target, topk=(1,)):
"""Computes the precision@k for the specified values of k"""
maxk = max(topk)
batch_size = targ... | 4,886 | 30.127389 | 95 | py |
TRSSL | TRSSL-main/utils/evaluate_utils.py | import numpy as np
import torch
import torch.nn.functional as F
from sklearn import metrics
from scipy.optimize import linear_sum_assignment
@torch.no_grad()
def hungarian_evaluate(predictions, targets, offset=0):
# Hungarian matching
targets = targets - offset
predictions = predictions - offset
predi... | 2,269 | 36.213115 | 161 | py |
TRSSL | TRSSL-main/utils/uncr_util.py | import random
import time
import pickle
import numpy as np
import torch
import torch.nn.functional as F
from tqdm import tqdm
from .utils import AverageMeter
def uncr_generator(args, data_loader, model):
batch_time = AverageMeter()
data_time = AverageMeter()
end = time.time()
pseudo_idx = []
pseud... | 3,161 | 31.265306 | 158 | py |
TRSSL | TRSSL-main/utils/sinkhorn_knopp.py | import torch
import numpy as np
def shoot_infs(inp_tensor):
"""Replaces inf by maximum of tensor"""
mask_inf = torch.isinf(inp_tensor)
ind_inf = torch.nonzero(mask_inf)
if len(ind_inf) > 0:
for ind in ind_inf:
if len(ind) == 2:
inp_tensor[ind[0], ind[1]] = 0
... | 2,410 | 32.957746 | 105 | py |
dropmax | dropmax-master/run.py | from __future__ import print_function
import tensorflow as tf
import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
from lenet import base_softmax, dropmax
from accumulator import Accumulator
from mnist import mnist_input
import time
import os
import argparse
parser = argparse.ArgumentParser()
... | 4,155 | 33.92437 | 90 | py |
dropmax | dropmax-master/layers.py | import tensorflow as tf
import numpy as np
exp = tf.exp
log = lambda x: tf.log(x + 1e-20)
logit = lambda x: log(x) - log(1-x)
sigmoid = tf.nn.sigmoid
softmax = tf.nn.softmax
relu = tf.nn.relu
tau = 0.1
eps = 1e-20
dense = tf.layers.dense
flatten = tf.contrib.layers.flatten
# network components
def conv(x, filters, k... | 1,936 | 28.348485 | 78 | py |
dropmax | dropmax-master/accumulator.py | from __future__ import print_function
class Accumulator():
def __init__(self, *args):
self.args = args
self.argdict = {}
for i, arg in enumerate(args):
self.argdict[arg] = i
self.sums = [0]*len(args)
self.cnt = 0
def accum(self, val):
val = [val] if ... | 1,876 | 29.770492 | 68 | py |
dropmax | dropmax-master/lenet.py | from layers import *
def base_softmax(x, y, training, name='base_softmax', reuse=None):
x = tf.reshape(x, [-1, 1, 28, 28])
x = conv(x, 20, 5, name=name+'/conv1', reuse=reuse)
x = relu(x)
x = pool(x, name=name+'/pool1')
x = conv(x, 50, 5, name=name+'/conv2', reuse=reuse)
x = relu(x)
x = pool... | 1,968 | 31.816667 | 71 | py |
dropmax | dropmax-master/mnist.py | import numpy as np
from tensorflow.examples.tutorials.mnist import input_data
def mnist_input(path, nlist):
mnist = input_data.read_data_sets(path, one_hot=True, validation_size=0)
x, y = mnist.train.images, mnist.train.labels
y_ = np.argmax(y, axis=1)
xtr = [x[y_==k][:nlist[k],:] for k in range(10)]
... | 737 | 37.842105 | 76 | py |
BiRTE | BiRTE-main/main.py | from transformers import WEIGHTS_NAME,AdamW, get_linear_schedule_with_warmup
from bert4keras.tokenizers import Tokenizer
from model import BiRTE
from util import *
from tqdm import tqdm
import random
import os
import torch.nn as nn
import torch
from transformers.modeling_bert import BertConfig
import json
def search(p... | 18,791 | 39.32618 | 126 | py |
BiRTE | BiRTE-main/model.py | from transformers.modeling_bert import BertModel,BertPreTrainedModel
import torch.nn as nn
import torch
from torch.autograd import Variable
import numpy as np
class Biaffine(nn.Module):
'''
Args:
in1_features: size of each first input sample
in2_features: size of each second input sample
... | 7,229 | 36.46114 | 100 | py |
BiRTE | BiRTE-main/run.py | import argparse
from main import *
import torch
parser = argparse.ArgumentParser(description='Model Controller')
parser.add_argument('--cuda_id', default="0", type=str)
parser.add_argument('--base_path', default="./dataset", type=str)
parser.add_argument('--dataset', default='WebNLG', type=str)
parser.add_argument('--... | 1,383 | 45.133333 | 108 | py |
BiRTE | BiRTE-main/util.py | #! -*- coding:utf-8 -*-
import numpy as np
import random
from copy import deepcopy
import os
import pickle
import torch
import json
def get_more_data(all_data):
s_more = []
o_more = []
for ex in all_data:
all_s = set()
all_o = set()
for s, p, o in ex["triple_list"]:
all... | 12,507 | 32.354667 | 114 | py |
BiRTE | BiRTE-main/bert4keras/optimizers.py | # -*- coding: utf-8 -*-
# 优化相关
import numpy as np
import tensorflow as tf
from bert4keras.backend import keras, K, is_tf_keras
from bert4keras.snippets import is_string, string_matching
from bert4keras.snippets import is_one_of, insert_arguments
from bert4keras.backend import piecewise_linear
import re
class Adam(ke... | 34,935 | 34.360324 | 83 | py |
BiRTE | BiRTE-main/bert4keras/tokenizers.py | #! -*- coding: utf-8 -*-
# 工具函数
import unicodedata, re
from bert4keras.snippets import is_string, is_py2
from bert4keras.snippets import open
def load_vocab(dict_path, encoding='utf-8', simplified=False, startswith=None):
"""从bert的词典文件中读取词典
"""
token_dict = {}
with open(dict_path, encoding=encoding) ... | 15,186 | 31.450855 | 502 | py |
BiRTE | BiRTE-main/bert4keras/layers.py | #! -*- coding: utf-8 -*-
# 自定义层
import numpy as np
import tensorflow as tf
from bert4keras.backend import keras, K
from bert4keras.backend import search_layer
from bert4keras.backend import sequence_masking
from bert4keras.backend import pool1d
from bert4keras.backend import divisible_temporal_padding
from bert4keras.... | 31,362 | 33.464835 | 80 | py |
BiRTE | BiRTE-main/bert4keras/snippets.py | #! -*- coding: utf-8 -*-
# 代码合集
import six
import logging
import numpy as np
import re
import sys
_open_ = open
is_py2 = six.PY2
if not is_py2:
basestring = str
def is_string(s):
"""判断是否是字符串
"""
return isinstance(s, basestring)
def strQ2B(ustring):
"""全角符号转对应的半角符号
"""
rstring = ''
... | 15,499 | 28.807692 | 80 | py |
BiRTE | BiRTE-main/bert4keras/backend.py | # -*- coding: utf-8 -*-
# 分离后端函数，主要是为了同时兼容原生keras和tf.keras
# 通过设置环境变量TF_KERAS=1来切换tf.keras
import os, sys
from distutils.util import strtobool
import numpy as np
import tensorflow as tf
# 判断是tf.keras还是纯keras的标记
is_tf_keras = strtobool(os.environ.get('TF_KERAS', '0'))
if is_tf_keras:
import tensorflow.keras as ke... | 5,182 | 23.799043 | 73 | py |
BiRTE | BiRTE-main/bert4keras/models.py | #! -*- coding: utf-8 -*-
# 主要模型
import numpy as np
from bert4keras.layers import *
from bert4keras.snippets import delete_arguments
from keras.models import Model
import json
class Transformer(object):
"""模型基类
"""
def __init__(
self,
vocab_size, # 词表大小
hidden_size, # 编码维度
... | 62,335 | 32.157447 | 87 | py |
BiRTE | BiRTE-main/bert4keras/__init__.py | #! -*- coding: utf-8 -*-
__version__ = '0.7.2'
| 48 | 11.25 | 24 | py |
rnn-seq2seq-learning | rnn-seq2seq-learning-main/scripts/visualization.py | '''
Author: Zhengxiang (Jack) Wang
GitHub: https://github.com/jaaack-wang
Website: https://jaaack-wang.eu.org
About: visualization function.
'''
import matplotlib.pyplot as plt
def plot_training_log(log, show_plot=True, saved_plot_fp=None):
log = log.copy()
if "Best eval accu" in log:
log.pop("Best e... | 3,737 | 31.789474 | 77 | py |
rnn-seq2seq-learning | rnn-seq2seq-learning-main/scripts/dataloader.py | '''
Author: Zhengxiang (Jack) Wang
GitHub: https://github.com/jaaack-wang
Website: https://jaaack-wang.eu.org
About: Code for creating dataloader in PyTorch
'''
import torch
from functools import partial
from torch.utils.data import Dataset, DataLoader
import sys
import pathlib
# import from local script
sys.path.ins... | 6,202 | 32.711957 | 75 | py |
rnn-seq2seq-learning | rnn-seq2seq-learning-main/scripts/utils.py | '''
- Author: Zhengxiang (Jack) Wang
- GitHub: https://github.com/jaaack-wang
- Website: https://jaaack-wang.eu.org
- About: General utility functions for handling files.
'''
import os
from os import listdir, walk
from os.path import isfile, join, exists
import random
import json
def read_data(filepath, skip=0, sep... | 2,324 | 25.724138 | 90 | py |
rnn-seq2seq-learning | rnn-seq2seq-learning-main/scripts/model.py | '''
Author: Zhengxiang (Jack) Wang
GitHub: https://github.com/jaaack-wang
Website: https://jaaack-wang.eu.org
About: RNN Seq2Seq models (Simple RNN, GRU, LSTM)
in PyTorch. Allows: attention, bidirectional RNN,
as well as multilayered RNN etc.
'''
import random
import torch
import torch.nn as nn
import torch.nn.functio... | 7,864 | 38.522613 | 80 | py |
rnn-seq2seq-learning | rnn-seq2seq-learning-main/scripts/data.py | '''
- Author: Zhengxiang (Jack) Wang
- GitHub: https://github.com/jaaack-wang
- Website: https://jaaack-wang.eu.org
- About: Code for generating train, dev, test, and gen sets
containing string pairs applying the following string transducation
functions: identity (w --> w), reveral (w --> w^R), total reduplication
... | 4,819 | 32.013699 | 86 | py |
rnn-seq2seq-learning | rnn-seq2seq-learning-main/scripts/pytorch_utils.py | '''
Author: Zhengxiang (Jack) Wang
GitHub: https://github.com/jaaack-wang
Website: https://jaaack-wang.eu.org
About: Utility functions for training, evaluation,
and deployment (i.e., prediction).
'''
import torch
import torch.nn as nn
import torch.nn.init as init
from functools import partial
import matplotlib.pyplot ... | 13,983 | 35.511749 | 89 | py |
libai | libai-main/setup.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 3,998 | 26.770833 | 96 | py |
libai | libai-main/libai/__init__.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 1,062 | 30.264706 | 74 | py |
libai | libai-main/libai/scheduler/lr_scheduler.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 10,480 | 39.624031 | 99 | py |
libai | libai-main/libai/scheduler/__init__.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 828 | 32.16 | 74 | py |
libai | libai-main/libai/scheduler/build.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 845 | 34.25 | 74 | py |
libai | libai-main/libai/evaluation/reg_evaluator.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 2,094 | 29.362319 | 74 | py |
libai | libai-main/libai/evaluation/utils.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 3,505 | 36.297872 | 98 | py |
libai | libai-main/libai/evaluation/evaluator.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www... | 11,242 | 36.983108 | 99 | py |
libai | libai-main/libai/evaluation/bleu_evaluator.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 1,888 | 28.061538 | 82 | py |
libai | libai-main/libai/evaluation/ppl_evaluator.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 1,794 | 28.42623 | 74 | py |
libai | libai-main/libai/evaluation/__init__.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 903 | 40.090909 | 74 | py |
libai | libai-main/libai/evaluation/cls_evaluator.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 2,773 | 31.635294 | 88 | py |
libai | libai-main/libai/config/arguments.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 2,877 | 34.530864 | 96 | py |
libai | libai-main/libai/config/config.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www... | 6,972 | 34.040201 | 100 | py |
libai | libai-main/libai/config/__init__.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 958 | 30.966667 | 74 | py |
libai | libai-main/libai/config/lazy.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www... | 17,312 | 36.3125 | 96 | py |
libai | libai-main/libai/config/instantiate.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www... | 6,348 | 30.430693 | 99 | py |
libai | libai-main/libai/models/gpt_model.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 16,017 | 39.045 | 100 | py |
libai | libai-main/libai/models/t5_model.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 22,776 | 42.88632 | 100 | py |
libai | libai-main/libai/models/swin_transformer.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 29,510 | 37.177232 | 100 | py |
libai | libai-main/libai/models/bert_model.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 24,272 | 40.001689 | 100 | py |
libai | libai-main/libai/models/vision_transformer.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 10,057 | 36.529851 | 85 | py |
libai | libai-main/libai/models/resmlp.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 10,622 | 34.888514 | 94 | py |
libai | libai-main/libai/models/__init__.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 1,466 | 31.6 | 82 | py |
libai | libai-main/libai/models/roberta_model.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 21,479 | 40.871345 | 99 | py |
libai | libai-main/libai/models/swin_transformer_v2.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 34,295 | 37.064373 | 100 | py |
libai | libai-main/libai/models/build.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 2,277 | 41.185185 | 93 | py |
libai | libai-main/libai/models/utils/weight_init.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 1,119 | 28.473684 | 74 | py |
libai | libai-main/libai/models/utils/graph_base.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 6,034 | 38.966887 | 123 | py |
libai | libai-main/libai/models/utils/__init__.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 1,271 | 49.88 | 84 | py |
libai | libai-main/libai/models/utils/model_loader/gpt_loader.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 7,937 | 44.36 | 100 | py |
libai | libai-main/libai/models/utils/model_loader/bert_loader.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 12,335 | 45.727273 | 100 | py |
libai | libai-main/libai/models/utils/model_loader/swin_loader.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 12,908 | 42.173913 | 99 | py |
libai | libai-main/libai/models/utils/model_loader/vit_loader.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 9,666 | 41.774336 | 96 | py |
libai | libai-main/libai/models/utils/model_loader/base_loader.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 22,702 | 36.964883 | 100 | py |
libai | libai-main/libai/models/utils/model_loader/swinv2_loader.py | # coding=utf-8
# Copyright 2021 The OneFlow Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 14,228 | 43.886435 | 100 | py |
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