我有特征和标签x的维度数据。(n_samples, time_steps, n_features)(n_samples, 1, n_labels)y
由此我创建了一个训练、开发和测试 pytorch 数据集。
我想使用 GridSearchCV 对超参数进行网格搜索。那是我写的：
'Define the network'
sampling_interval = 0.1
net = ConvNet(time_window, ny)
net.float()
'Split test training set'
# trainin test. In this case we take some experiements as test and some as trainint
train_set_split = 0.9
dev_set_split = 0.05
test_set_split = 0.05
# Creating data indices for training and validation splits:
dataset_size = x.shape[0]
indices = list(range(dataset_size))
np.random.shuffle(indices)
split1 = int(np.floor(train_set_split * dataset_size))
split2 = int(np.floor(dev_set_split …当我尝试在 Ubuntu 上运行 Python 3.6 时遇到此问题：
/lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.25' not found
造成这种情况的原因是什么？
我可以运行 jupyter 笔记本，但是当我尝试打开 jupyter 文件时，我的浏览器上出现以下错误
500内部服务器错误
在控制台中，我收到此错误消息
To access the notebook, open this file in a browser:
file:///C:/Users/Bruno/AppData/Roaming/jupyter/runtime/nbserver-23164-open.html
Or copy and paste one of these URLs:
http://localhost:8888/?token=1e5a289e6fd9b36cab176131f1e3d0b673921c1a76258552
or http://127.0.0.1:8888/?token=1e5a289e6fd9b36cab176131f1e3d0b673921c1a76258552
[W 16:19:04.850 NotebookApp] 404 GET /ipyparallel/clusters?_=1649168344196 (::1) 16.95ms referer=http://localhost:8888/tree
[E 16:19:24.938 NotebookApp] Uncaught exception GET /notebooks/examples/jupyter_notebooks/greenhouse.ipynb (::1)
HTTPServerRequest(protocol='http', host='localhost:8888', method='GET', uri='/notebooks/examples/jupyter_notebooks/greenhouse.ipynb', version='HTTP/1.1', remote_ip='::1')
Traceback (most recent call last):
File "c:\users\...\tornado\web.py", line 1697, in _execute
result = method(*self.path_args, **self.path_kwargs)
File "c:\users\..\tornado\web.py", line 3174, in wrapper
return method(self, *args, **kwargs)
File "c:\users\..\notebook\notebook\handlers.py", line …我需要从 pytorch 中经过训练的神经网络中提取权重、偏差和至少激活函数的类型。
我知道要提取权重和偏差，命令是：
model.parameters()
但我不知道如何提取层上使用的激活函数。这是我的网络
class NetWithODE(torch.nn.Module):
def __init__(self, n_feature, n_hidden, n_output, sampling_interval, scaler_features):
super(NetWithODE, self).__init__()
self.hidden = torch.nn.Linear(n_feature, n_hidden) # hidden layer
self.predict = torch.nn.Linear(n_hidden, n_output) # output layer
self.sampling_interval = sampling_interval
self.device = torch.device("cpu")
self.dtype = torch.float
self.scaler_features = scaler_features
def forward(self, x):
x0 = x.clone().requires_grad_(True)
# activation function for hidden layer
x = F.relu(self.hidden(x))
# linear output, here r should be the output
r = self.predict(x)
# Now the r enters the integrator
x = self.integrate(r, …我正在尝试使用熊猫。当我导入为
import panda as pd
我得到这个错误
File "/usr/local/lib/python3.5/dist-packages/panda/__init__.py", line 1, in <module>
from request import PandaRequest ImportError: No module named 'request'
'request'似乎已经安装：
Requirement already satisfied: request in /usr/local/lib/python3.5/dist-packages
我正在使用Python 3.5。我看了看，问题似乎只存在于2.7。您是否知道为什么它不起作用？
谢谢
布鲁诺