Last Updated on 2021-07-05 by Clay
Python is a simple and beautiful program language. Today I will record how to learn Python quickly. The cost time, I think it’s just only one hour.
Read More »Easy Python Tutorial Speed Run —— Only one hour
Last Updated on 2021-07-05 by Clay
When we using the famous Python framework: PyTorch, to build our model, if we can visualize our model, that's a cool idea.
In this way, we can check our model layer, output shape, and avoid our model mismatch.
Read More »[PyTorch] Using "torchsummary" to plot your model structureLast Updated on 2021-07-05 by Clay
Today when I use Python to process a NLP task, I get a error message:
OSError: [E050] Can't find model 'en'. It doesn't seem to be a shortcut link, a Python package or a valid path to a data directory.Last Updated on 2021-07-01 by Clay
I think if we use Pytorch framework to train a model, the commonly error messages are "Model mismatch" and the following error:
Read More »[Solved][PyTorch] RuntimeError: Expected object of scalar type Float but got scalar type Long for argument
Last Updated on 2021-07-01 by Clay
Recently, I encountered a bottleneck in the training of deep learning models. The most important aspect is the speed of training.
Read More »[Linux] Store the data into RAM disk to speed up the program
Last Updated on 2021-06-28 by Clay
Jupyter Notebook is a Python Editor (?) or you may think it is like an IDE, which is implemented by IPython.
Read More »[Linux] How to use remote Jupyter Notebook via SSHLast Updated on 2021-06-28 by Clay
Today, when I using PyTorch to build a LSTM model, I got an error occured:
LSTM RuntimeError: input must have 3 dimensions, got 2Last Updated on 2021-06-28 by Clay
Today, when I load a model I trained with PyTorch and I want to use it to process some new data, I got a error report:
Read More »[Solved] RuntimeError: Input and parameter tensors are not at the same device, found input tensor at cpu and parameter tensor at cuda:0Last Updated on 2021-06-28 by Clay
Today, if we need to split our data for training our model —— we need to split training data and test data. We use "training data" to train our model and check it never peep our "test data", it is very important, because our "test data" can assess the quality of our model.
Read More »[Scikit-Learn] Using "train_test_split()" to split your data
Last Updated on 2021-06-02 by Clay
Cifar-10 is dataset like "MNIST", it have 60000 pictures, 10 types. One of types have 6000 pictures. 50000 training data and 10000 test data.
Read More »[Keras] Build a CNN model to classify Cifar-10