Webfrom utils import DGraphFin from utils.utils import prepare_folder from utils.evaluator import Evaluator from models import MLP, MLPLinear, GCN, SAGE, GAT, GATv2 from … WebApr 12, 2024 · Create the model, and load the pre-trained checkpoint. Optimize the model for eval, and move the model to the Gaudi Accelerator (“hpu”) model = Net() checkpoint = torch.load('mnist-epoch_20.pth') model.load_state_dict(checkpoint) model = model.eval() Wrap the model with HPU graph, and move it to HPU Here we are using …

Networkx - python - No shorter path found even if it exist

Webdef mask_nodes_by_property (property_values, part_ratios, random_seed = None): """Provide the split masks for a node split with distributional shift based on a given ... WebSource code for torch_geometric.datasets.dgraph. Source code for. torch_geometric.datasets.dgraph. import os from typing import Callable, Optional … crooks character of mice and men

spinup.utils.logx — Spinning Up documentation - OpenAI

WebDataLoader is an iterable that abstracts this complexity for us in an easy API. from torch.utils.data import DataLoader train_dataloader = DataLoader(training_data, batch_size=64, shuffle=True) test_dataloader = DataLoader(test_data, batch_size=64, shuffle=True) Iterate through the DataLoader WebThe goal is to create a graph of python module’s imports in a package. graphviz ’s dot tool will be used to generate the graph. As an example, the requests package will be used. The result is the image below: In the image an arrow represents an import from one module to another. For example in the left side of image you can see an arrow ... WebSep 11, 2024 · from keras.models import Sequential from keras.layers import Dense from keras.utils.vis_utils import plot_model model = Sequential() model.add(Dense(2, input_dim=1, activation='relu')) … crooks character traits of mice and men