train_loader = DataLoader(my_dataset, batch_size=32, shuffle=True)在上面的示例代码中，MyDataset 是您自己定义的数据集类，您需要根据您的数据集类型来创建一个对应的数据集类。batch_size 参数指定了每个批次的数据量，shuffle 参数指定了是否对数据进行随机打乱。是的亲。这个错误提示通常是因为在...
%CUDA_VISIBLE_DEVICES='0,1,2,3' python3 -u train.py --network r50 --loss cosface --dataset emore gpu num: 4 prefix ./models/r50-cosface-emore/model image_size [112, 112] num_classes 85742 Called with argument: Namespace(batch_size=512, ckpt=3, ctx_num=4, dataset='emore', freq...
I followed the instructions in the README and executed the following command, but encountered an error: "ModuleNotFoundError: No module named 'src.model.Checkpointer'". Command executed: python src/training.py -c configs/models/t5_large...
orderStrmInterNum template struct xf::graph::internal::AggRAM_base template struct xf::graph::internal::CkKins struct xf::graph::internal::GetVout template struct xf::graph::internal::ValAddr template struct xf::graph::internal::unitCidGain struct xf::graph::internal::unitCidGain_d...
这个是刚遇到的问题，在LZ自己手打Inception net的时候，想赋一个名字的时候出错，其实这就是命名错误的问题，如果仔细看“×”是我在中文下打的符号，python是不认的，解决方案是使用英文字母”x“代替，错误即可解决，而且也能看到使用的卷积核的大小。
azureml-train-automl-runtime azureml-train-core azureml-training-tabular azureml-widgets azureml-contrib-automl-pipeline-steps azureml-contrib-dataset azureml-contrib-fairness azureml-contrib-functions azureml-contrib-notebook azureml-contrib-pipeline-steps azureml-contrib-reinforcementlearning...
参数： tensor（Tensor 或 list）– 四维批（batch）Tensor或列表。如果是Tensor，其形状应是（B x C...
batched_tensors, batch_index, id_t = gen_batch_ops.batch( args, num_batch_threads=num_batch_threads, max_batch_size=max_batch_size, batch_timeout_micros=batch_timeout_micros, max_enqueued_batches=max_enqueued_batches, allowed_batch_sizes=allowed_batch_sizes, ...
num_train_epochs=3.0, optim=adamw_hf, optim_args=None, output_dir=output/adgen-chatglm2-6b-pt-128-2e-2, overwrite_output_dir=True, past_index=-1, per_device_eval_batch_size=1, per_device_train_batch_size=1, predict_with_generate=True, prediction_loss_only=False, push_to_hub=False...
--train_batch_size=1 --gradient_accumulation_steps=1 --learning_rate=5e-6 --lr_scheduler="constant" --lr_warmup_steps=0 --num_class_images=100 --max_train_steps=200 --push_to_hub ` I did this after I downloaded the script using wget -q https://github.com/huggingface/...