创建文件:utils/fix_random_seed.py: import torch import numpy as np import random import os def setup_seed(seed=3407): random.seed(seed) # Python的随机性 os.environ['PYTHONHASHSEED'] = str(seed) # 设置Python哈希种子,为了禁
2)固定random seeds: 训练开始前要先固定numpy和torch的random seed,如果使用CUDA还要固定torch.manual_seed等,尤其设定cudnn.deterministic=True,这些是为了消除计算过程中的随机性,从而避免在参数相同、训练次数相同的情况下每次训练结果却都不同的问题。 # fix random seeds and fix CUDA seeds if using CUDA to ...
AI代码解释 importtorchimporttorchvision.transformsasT# to fix random seed,use torch.manual_seed # insteadofrandom.seed torch.manual_seed(12)transforms=torch.nn.Sequential(T.RandomCrop(224),T.RandomHorizontalFlip(p=0.3),T.ConvertImageDtype(torch.float),T.Normalize([0.485,0.456,0.406],[0.229,0.224...
import torch from torch import nn from torch.nn import init import torch.utils.data as Data import matplotlib.pyplot as plt import numpy as np # torch.manual_seed(1) # reproducible # np.random.seed(1) # Hyper parameters N_SAMPLES = 2000 BATCH_SIZE = 64 EPOCH = 12 LR = 0.03 N_HIDDE...
(train, tokenizer) seed_everything(42) # Kfold nfold = 5 folds = [0, 1, 2, 3, 4] kfold = StratifiedGroupKFold(nfold, shuffle=True, random_state=42) groups = train['pn_num'].values cases = train['case_num'].values # Parameters epochs = 5 batch_size = 6 batch_size_val ...
To make computations deterministic, let's fix random seeds. torch.manual_seed(123)np.random.seed(123) Let's define our input and baseline tensors. Baselines are used in some interpretability algorithms such asIntegratedGradients, DeepLift, GradientShap, NeuronConductance, LayerConductance, InternalInfl...
Fixed a bug to use generator instead of self.generator in the RandomSampler (#52956).C++ APIFixed the lifetime of PyTensorType (#51649). Fixed linker failure with ambiguous namespaces (#45736). Fix Scalar output formatting (#53229) Fix printing of optional string arguments in schemas (#...
(f))x,y,tx,ty,allx,ally,graph=tuple(objects)test_idx_reorder=parse_index_file("data/ind.{}.test.index".format(dataset_str))test_idx_range=np.sort(test_idx_reorder)ifdataset_str=='citeseer':# Fix citeseerdataset(there are some isolated nodesinthe graph)# Find isolated nodes,add the...
Tianshou(天授)是纯基于 PyTorch 的强化学习平台,与现有的主要基于 TensorFlow 的强化学习库不同,Tianshou 没有繁杂的嵌套类、不友好的 API 和
import torch import random import torch.nn as nn class Encoder(nn.Module): def __init__(self, input_size, embed_size, hidden_size, dropout, seed=0): super().__init__() self.hidden_size = hidden_size self.embedding = nn.Embedding(input_size, embed_size) self.rnn = nn.GRU(embed...