python launch.py --config configs/nerf-blender.yaml --gpu 0 --train dataset.scene=lego tag=iter50k seed=0 trainer.max_steps=50000 Training on DTU Download preprocessed DTU data provided by NeuS or IDR. In the provided config files we assume using NeuS DTU data. If you are using IDR DTU...
This is a third party implementation of RA-CNN in pytorch. - RACNN-pytorch/trainer.py at master · vickisy/RACNN-pytorch
git clone https://github.com/PaddlePaddle/PaddleRec/ cd PaddleRec 快速运行 我们以排序模型中的dnn模型为例介绍PaddleRec的一键启动。训练数据来源为Criteo数据集,我们从中截取了100条数据: python -u tools/trainer.py -m models/rank/dnn/config.yaml # 动态图训练 python -u tools/static_trainer.py -m ...
# filter by class_idkeep_class_id= [1,2]bbox_res= [e for e in bbox_res if int(e[0]) in keep_class_id] https://github.com/PaddlePaddle/PaddleDetection/blob/b87a1ea86fa18ce69e44a17ad1b49c1326f19ff9/ppdet/engine/trainer.py#L438 Q:用户自定义数据集训练,预测结果标签错误 A:此类...
https://github.com/PaddlePaddle/PaddleDetection/blob/b87a1ea86fa18ce69e44a17ad1b49c1326f19ff9/ppdet/engine/trainer.py#L438 Q:用户自定义数据集训练,预测结果标签错误 A:此类情况往往是用户在设置数据集路径时候,并没有关注TestDataset中anno_path的路径问题。需要用户将anno_path设置成自己的路径。
Trainer at Java Campus Bootcamp, Telkom University Topic: "Skill Shaping To Meet Industrial Requirement" Trainer at PT. Daya Indosa Pratama for new employee bootcamp training Topic: "Java Spring Framework for Industrial Requirement" Learn More 🏅 Certificates Certified Blockchain Architecture IBM Block...
We support Huggingface's TRL, Trainer, Seq2SeqTrainer or even Pytorch code! We're in 🤗Hugging Face's official docs! Check out the SFT docs and DPO docs!from unsloth import FastLanguageModel from unsloth import is_bfloat16_supported import torch from trl import SFTTrainer from transformers...
PyTorch implementation of the paper Guiding attention in Sequence-to-sequence models for Dialogue Act prediction for dialogue act classification with a generic dataset class and PyTorch-Lightning trainer. This implementation has following differences compare to the actual paper In this implementation contextu...
Total estimated model params size (MB) Validation sanity check: 0it [00:00, ?it/s]/usr/local/lib/python3.6/dist-packages/pytorch_lightning/trainer/data_loading.py:373: UserWarning: Your val_dataloader has `shuffle=True`, it is best practice to turn this off for val/test/predict data...
class SimpleTrainer(Trainer): def __init__(self, model: nn.Module, loss: str, loss_args: Optional[Dict[str, Any]] = None, optimizer: Union[str, Optimizer] = 'adam', optimizer_args: Optional[Dict[str, Any]] = None, log_interval: Optional[int] = None): Trainer.__init__(self, ...