(https://github.com/NeuroBench/neurobench/tree/main/neurobench/examples/) In general, the design flow for using the framework is as follows: Train a network using the train split from a particular dataset. Wrap the network in a NeuroBenchModel. Pass the model, evaluation split dataloader, ...
lgb_train = lgb.Dataset(x_train, y_train, free_raw_data = False) lgb_valid = lgb.Dataset(x_valid, y_valid, reference=lgb_train,free_raw_data=False) # 设置初始参数 params = { "boosting_type":"gbdt", "objective":"regression", "metric":"mae", "nthread":4, "learning_rate":0.1...
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SSIG [17] and UFPR [3] captured images by cameras on the road. These images were collected on a sunny day and rarely had tilted LPs. Before we introducing CCPD, ReId [15] is the largest dataset for LP recognition with 76k extracted LPs...