action = torch.zeros([model.number_of_actions], dtype=torch.float32) action[0] =1image_data, reward, terminal = game_state.frame_step(action) image_data = resize_and_bgr2gray(image_data) image_data = image_to_tensor(image_data) state = torch.cat((image_data, image_data, image_data...
- [Configure the Viewer through code](howto/configure-viewer-through-code.md) - [Create a fixed-window plot](howto/fixed-window-plot.md) - [Limit memory usage](howto/limit-ram.md) - [Share recordings across multiple processes](howto/shared-recordings.md) - [Clear out already logged dat...
. . . . 6-21 tensorprod Function: Calculate tensor products between two arrays . . . . 6-21 round Function: Control tiebreak behavior . . . . . . . . . . . . . . . . . . . . . . . 6-21 null and orth Functions: Specify tolerance to treat singular values below a ...
Tip here: know the difference between tensor dimensions at train time vs tensor dimensions at inference time. Although at train time, you can expect your tensor dimensions to match your model parameters closely, eg batch.shape = (config['batch_size'], config['context_window'], config['d_mod...
Here’s the first clue: not everything is right with the training of ADM. Tracking the magnitude of the values seen in the activations propagating in the network and the learned weight tensors stored at the layers shows a steady growth throughout the training (the lines correspond to a sele...
We present a neural network structure, ControlNet, to control pretrained large diffusion models to support additional input conditions. 我们提出了一个神经网络结构,ControlNet,以控制预训练的大型扩散模型,以支持额外的输入条件。 其实就是在大型扩散生成模型的基础上,再加上一个结构,使得扩散生成模型能够接受一...
How to plot E11 & S11 in comsol Posted 2012年6月5日 GMT+8 20:36Results & Visualization, Structural Mechanics1 Reply Husain Kanchwala Send Private MessageFlag post as spam Actually my problem statement is that I am modelling a unit cell with spherical inclusions. i have modeled whole problem...
For classification problems, a Shapley summary plot can be created for each output class. In that case, the shap variable could be a tensor ("3-D matrix") with indices as: (query-point-index, predictor-index, output-class-index) Function to create CoolBlueToWarmRedColormap 테마복사...
plt.plot(losses); These codes are quite self-explanatory. We used thefast.ailibrary for this project. Download the MNIST pickle file and unzip it, transfer it into a PyTorch tensor, then stuff it into a fast.ai DataBunch object for further training. Then we created a simple neural...
We can plot our keypoints on an image using the following code (in Google Colab): from PIL import Image r = results[0] im_array = r.plot() # plot a BGR numpy array of predictions im = Image.fromarray(im_array[..., ::-1]) # RGB PIL image display(im) Here is the output fro...